Agronomy

20 pages, 4652 KB

Open AccessEditor’s ChoiceArticle

Optimizing Tomato Seedling Production in the Tropics: Effects of Trichoderma, Arbuscular Mycorrhizal Fungi, and Key Agronomical Factors

by Teresa Leuratti, Lorenzo Fellin, Nicola Michelon, Juan Bosco Palacios Tario, Jaime Ernesto Santamaria Gutiérrez, Giorgio Gianquinto, Francesco Orsini and Giampaolo Zanin

Agronomy 2025, 15(2), 392; https://doi.org/10.3390/agronomy15020392 - 31 Jan 2025

Cited by 1 | Viewed by 1004

Abstract

Agriculture remains a key contributor to Central America’s economy, despite climate change posing a significant threat to the sector. In the Trifinio region, already afflicted by arid summers, temperatures are expected to rise in the near future, potentially exacerbating the vulnerability of smallholder [...] Read more.

Agriculture remains a key contributor to Central America’s economy, despite climate change posing a significant threat to the sector. In the Trifinio region, already afflicted by arid summers, temperatures are expected to rise in the near future, potentially exacerbating the vulnerability of smallholder farmers. This study investigates the effects of two fungal symbionts, Trichoderma asperellum (TR) and the Arbuscular mycorrhiza fungi (AMF) Glomus cubense, and agronomic choices and practices such as cultivar selection, substrate type, and fertigation management on tomato (Solanum lycopersicum L.) seedling growth and quality. Results showed that nutrient solution and the adoption of forest topsoil as substrate significantly enhanced morphological, physiological, and quality parameters. Modifying the nutrient solution to allow for an increase in plant height of 170% and a dry weight of 163% and enhancing Dickson’s quality index (DQI) by 64.5%, while the use of forest topsoil resulted in plants 58.6% higher, with an increase of 101% in dry weight and of 90.1% in the DQI. Both T. asperellum and G. cubense had positive effects on specific growth parameters; for instance, TR increased leaf number (+6.95%), while AMF increased stem diameter (+3.56%) and root length (+19.1%), although they did not, overall, significantly increase the seedling’s biomass and quality. These findings underscore the importance of agronomic practices in mitigating the impacts of climate change on tomato production, offering valuable insights for farmers in semi-arid regions. Full article

(This article belongs to the Section Horticultural and Floricultural Crops)

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20 pages, 7239 KB

Open AccessEditor’s ChoiceArticle

Annual Garden Rocket and Radish as Microgreens: Seed Germination Response to Thermal and Salt Stress

by Stefania Toscano, Daniela Romano, Valeria Cafaro and Cristina Patanè

Agronomy 2025, 15(2), 361; https://doi.org/10.3390/agronomy15020361 - 30 Jan 2025

Cited by 1 | Viewed by 1852

Abstract

Temperature and salinity level of the imbibition medium play a crucial role in regulating seed germination and seedling emergence, which is also true in microgreen production, where temperature and water potential may influence seed germination alone and/or in combination. In this study, the [...] Read more.

Temperature and salinity level of the imbibition medium play a crucial role in regulating seed germination and seedling emergence, which is also true in microgreen production, where temperature and water potential may influence seed germination alone and/or in combination. In this study, the effects of different temperatures and water potentials in NaCl, alone or in combination, upon germination and early radicle growth, were assessed in two species for microgreen production (Eruca sativa-rocket, and Raphanus sativus-radish). Seeds were germinated at eight constant temperatures (from 5 to 35 °C) and five water potentials (ψ) in NaCl (from 0 to −1.2 MPa). Final germination percentage (FGP) was maximized at 15–20 °C in rocket, and at 20–25 °C in radish. As the temperature increased or decreased, germination was reduced and became less uniform, to a greater extent, at suboptimal temperatures in both species. Across water potentials, FGP values exceeding 50% at the highest temperature in radish indicated a greater tolerance than rocket to supraoptimal temperatures during germination. Across temperatures, FGP and germination speed in both species were progressively depressed as the water potential decreased. The adverse effects of NaCl progressively increased as the temperature moved away from its optimal value. Overall, rocket seeds were able to germinate well (>80%) at 20 °C at salinity levels down to −0.9 MPa, while radish seeds were able to germinate well (≥90%) at 25 °C at salinity levels down to −0.9 MPa. Salt stress tolerance was higher in rocket and radish at low and high temperatures, respectively. Both thermal time and hydrotime requirements were higher in radish because its seeds took longer to germinate. Thermal time and hydrotime may help to predict the germination capacity and time, once the temperature or water potential of the imbibition substrate is known. The findings of this study have important implications for the large-scale industrial production of microgreens. Full article

(This article belongs to the Section Horticultural and Floricultural Crops)

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16 pages, 1873 KB

Open AccessEditor’s ChoiceArticle

Satureja kitaibelii Essential Oil and Extracts: Bioactive Compounds and Pesticide Properties

by Milena Nikolova, Aneta Lyubenova, Elina Yankova-Tsvetkova, Borislav Georgiev, Genadi Gavrilov and Anna Gavrilova

Agronomy 2025, 15(2), 357; https://doi.org/10.3390/agronomy15020357 - 30 Jan 2025

Cited by 2 | Viewed by 2437

Abstract

In recent years, the essential oil of Satureja species has been studied as a source of biocidal activity with potential applications in organic farming such as bio-pesticides. The present study aims to determine the potential of essential oil (EO), exudate fraction (EF) and [...] Read more.

In recent years, the essential oil of Satureja species has been studied as a source of biocidal activity with potential applications in organic farming such as bio-pesticides. The present study aims to determine the potential of essential oil (EO), exudate fraction (EF) and methanolic extract (ME) of Satureja kitaibelii Wierzb. ex Heuff. to inhibit the mycelial growth of phytopathogenic fungi and acetylcholinesterase (AChE). Additionally, ME was tested for inhibitory activity on seed germination and root elongation. Phytochemical analysis was conducted using gas chromatography–mass spectrometry (GC–MS) and thin-layer chromatography (TLC). Biological activities were studied using in vitro methods. p-Cymene, limonene, geraniol, carvacrol and borneol were identified as the main components of EO. Oleanolic and ursolic acid, carvacrol and flavonoid aglycones were determined as the most abundant bioactive compounds of EF, whereas rosmarinic acid and flavonoid glycosides were found in ME. EO reduced the growth of all tested plant pathogens, indicated by 40% to 84% inhibition of mycelial growth (IMG). The growth rates of oomycetes Phytophthora cryptogea Pethybr. & Laff. and Phytophthora nicotianae Breda de Haan were affected to the greatest extent with 84% and 68% IMG. EF showed the most potent AChE inhibitory activity with IC₅₀ value of 0.18 mg/mL. Aqueous solutions of the ME with a concentration above 5 mg/mL were found to inhibit seed germination by more than 90%, whereas a reduction in root elongation was observed at 3 mg/mL. The present study provides for the first time data for the pesticidal properties of EO, EF and ME of S. kitaibelii. Full article

(This article belongs to the Special Issue Pests, Pesticides, Pollinators and Sustainable Farming)

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27 pages, 8048 KB

Open AccessEditor’s ChoiceArticle

Research and Development of an IoT Smart Irrigation System for Farmland Based on LoRa and Edge Computing

by Ying Zhang, Xingchen Wang, Liyong Jin, Jun Ni, Yan Zhu, Weixing Cao and Xiaoping Jiang

Agronomy 2025, 15(2), 366; https://doi.org/10.3390/agronomy15020366 - 30 Jan 2025

Cited by 7 | Viewed by 6487

Abstract

In response to the current key issues in the field of smart irrigation for farmland, such as the lack of data sources and insufficient integration, a low degree of automation in drive execution and control, and over-reliance on cloud platforms for analyzing and [...] Read more.

In response to the current key issues in the field of smart irrigation for farmland, such as the lack of data sources and insufficient integration, a low degree of automation in drive execution and control, and over-reliance on cloud platforms for analyzing and calculating decision making processes, we have developed nodes and gateways for smart irrigation. These developments are based on the EC-IOT edge computing IoT architecture and long range radio (LoRa) communication technology, utilizing STM32 MCU, WH-101-L low-power LoRa modules, 4G modules, high-precision GPS, and other devices. An edge computing analysis and decision model for smart irrigation in farmland has been established by collecting the soil moisture and real-time meteorological information in farmland in a distributed manner, as well as integrating crop growth period and soil properties of field plots. Additionally, a mobile mini-program has been developed using WeChat Developer Tools that interacts with the cloud via the message queuing telemetry transport (MQTT) protocol to realize data visualization on the mobile and web sides and remote precise irrigation control of solenoid valves. The results of the system wireless communication tests indicate that the LoRa-based sensor network has stable data transmission with a maximum communication distance of up to 4 km. At lower communication rates, the signal-to-noise ratio (SNR) and received signal strength indication (RSSI) values measured at long distances are relatively higher, indicating better communication signal quality, but they take longer to transmit. It takes 6 s to transmit 100 bytes at the lowest rate of 0.268 kbps to a distance of 4 km, whereas, at 10.937 kbps, it only takes 0.9 s. The results of field irrigation trials during the wheat grain filling stage have demonstrated that the irrigation amount determined based on the irrigation algorithm can maintain the soil moisture content after irrigation within the suitable range for wheat growth and above 90% of the upper limit of the suitable range, thereby achieving a satisfactory irrigation effect. Notably, the water content in the 40 cm soil layer has the strongest correlation with changes in crop evapotranspiration, and the highest temperature is the most critical factor influencing the water requirements of wheat during the grain-filling period in the test area. Full article

(This article belongs to the Section Water Use and Irrigation)

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17 pages, 2168 KB

Open AccessEditor’s ChoiceArticle

Effects of Long-Term Positioning Tillage Method and Straw Management on Crop Yield and Nutrient Accumulation and Utilization in Dryland Wheat–Maize Double-Cropping System

by Ming Huang, Huishu Xiao, Jun Zhang, Shuang Li, Yanmin Peng, Jin-Hua Guo, Peipei Jiang, Rongrong Wang, Yushu Chen, Chunxia Li, Hezheng Wang, Guozhan Fu, Muhammad Shaaban, Youjun Li, Jinzhi Wu and Guoqiang Li

Agronomy 2025, 15(2), 363; https://doi.org/10.3390/agronomy15020363 - 30 Jan 2025

Cited by 1 | Viewed by 1094

Abstract

The tillage method and straw returning are the two most important agronomic measures for crop production, but their combined effects on nutrient accumulation and utilization and grain yield in dryland winter wheat (Triticum aestivum L., namely wheat)–summer maize (Zea mays L., [...] Read more.

The tillage method and straw returning are the two most important agronomic measures for crop production, but their combined effects on nutrient accumulation and utilization and grain yield in dryland winter wheat (Triticum aestivum L., namely wheat)–summer maize (Zea mays L., namely maize) double-cropping system are still poorly understood. The present study delves into the impact of the tillage method and straw returning on yield and nutrient accumulation and utilization in wheat–maize double-cropping system based on a field split-plot positioning experiment (started in October 2009). Three tillage methods—plowing (PT, 30–35 cm in depth), rotary tillage (RT, 12–15 cm in depth), no-tillage (NT)—and two straw management—zero straw returning (S0) and straw returning (SR)—were assigned to the main plots and subplots, respectively, thus encompassing six distinct treatments of PTS0, PTSR, RTS0, RTSR, NTS0, and NTSR. The grain yield and its components; the nitrogen (N), phosphorus (P), and potassium (K) accumulation at maturity; and the internal efficiency of N, P, and K in wheat and maize from 2018 to 2022 were investigated. The results indicated that in the experimental years, tillage methods and straw management significantly affected wheat, maize, and annual yield. Compared with NT, RT significantly increased wheat yield by 9.5% and maize K accumulation by 5.8%, and PT significantly increased wheat K accumulation by 11.1% and the yield and N, P, and K accumulation of maize by 6.3%, 7.8%, 8.9%, and 5.3%. Compared with RT, PT significantly increased yield and K accumulation in wheat and yield and N and P accumulation in maize. Compared with NTSR, PTSR significantly increased the yield and N, P, and K accumulation in wheat, but it did not affect yield and nutrient accumulation in maize; RTSR significantly increased wheat yield while it significantly decreased yield and N, P, and K accumulation in maize. Compared with RTSR, PTSR significantly increased the yield and N, P, and K accumulation by 4.0%, 19.5%, 19.6%, and 7.0% in wheat, respectively, and 7.5%, 6.1%, 13.3% and 13.6% in maize. Under the same tillage method, compared with S0, SR significantly increased crop yield and N, P, and K accumulation by 2.4–25.4%, 8.5–43.3%, 12.9–37.8%, and 11.0–51.0%, but it significantly reduced wheat K internal efficiency and maize N, P, K internal efficiency. The effectiveness of straw management on crop yield and N, P, and K accumulation was greater than that of tillage methods. Therefore, the combination of plowing tillage with straw returning (PTSR) is an effective tactic to promote crop yield in dryland wheat–maize double-cropping system. This study offered insights for achieving high yield by regulating the accumulation and internal efficiency of plant N, P, and K nutrients in wheat–maize double-cropping system in drought-prone areas and environments similar to the study areas. Full article

(This article belongs to the Topic High-Efficiency Utilization of Water-Fertilizer Resources and Green Production of Crops)

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29 pages, 6516 KB

Open AccessEditor’s ChoiceArticle

Remote Sensing-Assisted Estimation of Water Use in Apple Orchards with Permanent Living Mulch

by Susana Ferreira, Juan Manuel Sánchez, José Manuel Gonçalves, Rui Eugénio and Henrique Damásio

Agronomy 2025, 15(2), 338; https://doi.org/10.3390/agronomy15020338 - 28 Jan 2025

Cited by 2 | Viewed by 2038

Abstract

Orchards are complex agricultural systems with various characteristics that influence crop evapotranspiration (ET_c), such as variety, tree height, planting density, irrigation methods, and inter-row management. The preservation of biodiversity and improvement of soil fertility have become important goals in modern orchard [...] Read more.

Orchards are complex agricultural systems with various characteristics that influence crop evapotranspiration (ET_c), such as variety, tree height, planting density, irrigation methods, and inter-row management. The preservation of biodiversity and improvement of soil fertility have become important goals in modern orchard management. Consequently, the traditional approach to weed control between rows, which relies on herbicides and soil mobilization, has gradually been replaced by the use of permanent living mulch (LM). This study explored the potential of a remote sensing (RS)-assisted method to monitor water use and water productivity in apple orchards with permanent mulch. The experimental data were obtained in the Lis Valley Irrigation District, on the Central Coast of Portugal, where the “Maçã de Alcobaça” (Alcobaça apple) is produced. The methodology was applied over three growing seasons (2019–2021), combining ground observations with RS tools, including drone flights and satellite images. The estimation of ET_a followed a modified version of the Food and Agriculture Organization of the United Nations (FAO) single crop coefficient approach, in which the crop coefficient (K_c) was derived from the normalized difference vegetation index (NDVI) calculated from satellite images and incorporated into a daily soil water balance. The average seasonal ET_a (FAO-56) was 824 ± 14 mm, and the water productivity (WP) was 3.99 ± 0.7 kg m⁻³. Good correlations were found between the K_c’s proposed by FAO and the NDVI evolution in the experimental plot, with an R² of 0.75 for the entire growing season. The results from the derived RS-assisted method were compared to the ET_a values obtained from the Mapping Evapotranspiration at High Resolution with Internalized Calibration (METRIC) surface energy balance model, showing a root mean square (RMSE) of ±0.3 mm day⁻¹ and a low bias of 0.6 mm day⁻¹. This study provided insights into mulch management, including cutting intensity, and its role in maintaining the health of the main crop. RS data can be used in this management to adjust cutting schedules, determine K_c, and monitor canopy management practices such as pruning, health monitoring, and irrigation warnings. Full article

(This article belongs to the Section Water Use and Irrigation)

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18 pages, 4474 KB

Open AccessEditor’s ChoiceArticle

Salt Tolerance Induced by Plant Growth-Promoting Rhizobacteria Is Associated with Modulations of the Photosynthetic Characteristics, Antioxidant System, and Rhizosphere Microbial Diversity in Soybean (Glycine max (L.) Merr.)

by Tong Lin, Fasih Ullah Haider, Tianhao Liu, Shuxin Li, Peng Zhang, Chunsheng Zhao and Xiangnan Li

Agronomy 2025, 15(2), 341; https://doi.org/10.3390/agronomy15020341 - 28 Jan 2025

Cited by 5 | Viewed by 1867

Abstract

Salinity stress poses a major obstacle to agricultural productivity. Employing plant growth-promoting rhizobacteria (PGPR) has attracted significant attention due to its potential to improve plant development in challenging conditions. Yet, additional investigation is essential to fully understand the potential of PGPR in mitigating [...] Read more.

Salinity stress poses a major obstacle to agricultural productivity. Employing plant growth-promoting rhizobacteria (PGPR) has attracted significant attention due to its potential to improve plant development in challenging conditions. Yet, additional investigation is essential to fully understand the potential of PGPR in mitigating salinity stress, especially in field applications. Hence, this study investigated the resistance mechanisms of soybean (Glycine max (L.) Merr.) under salt stress with PGPR application through a field experiment with four treatments: normal soybean planting (NN), normal planting + PGPR (NP), salt stress planting (SN), and salt stress planting + PGPR (SP). This research investigated how applying PGPR under salt stress influences soybean photosynthetic traits, osmotic regulation, rhizosphere microbial communities, and yield quality. The results demonstrated that salt stress enhanced leaf temperature and significantly reduced the leaf area index, SPAD value, stomatal conductance, photosynthetic rate, and transpiration rate of soybeans. Compared to SN treatment, SP treatment significantly improved the stomatal conductance, photosynthetic rate, and transpiration rate by 10.98%, 16.28%, and 35.59%, respectively. Salt stress substantially increased sodium (Na⁺) concentration and Na⁺/K⁺ ratio in leaves, roots, and grains while reducing potassium (K⁺) concentration in roots and leaves. Under salinity stress, PGPR application significantly minimized Na⁺ concentration in leaves and enhanced K⁺ concentration in leaves, roots, and grains by 47.05%, 25.72%, and 14.48%, respectively. PGPR application boosted carbon assimilation (starch synthesis) by enhancing the activities of sucrose synthase, fructokinase, and ADP-glucose pyrophosphorylase. It improved physiological parameters and increased soybean yield by 32.57% compared to SN treatment. Additionally, PGPR enhanced antioxidant enzyme activities, including glutathione reductase, peroxidase, ascorbate peroxidase, and monodehydroascorbate reductase, reducing oxidative damage from salt stress. Analysis of rhizosphere microbial communities revealed that PGPR application enriched beneficial bacterial phyla such as Bacteroidetes, Firmicutes, Nitrospirae, and Patescibacteria and fungal genera like Metarhizium. These microbial shifts likely contributed to improved nutrient cycling and plant–microbe interactions, further enhancing soybean resilience to salinity. This study demonstrates that PGPR enhances soybean growth, microbial diversity, and salt tolerance under salinity stress, while future efforts should optimize formulations, explore synergies, and scale up for sustainable productivity. Full article

(This article belongs to the Section Crop Breeding and Genetics)

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28 pages, 4133 KB

Open AccessEditor’s ChoiceArticle

A Dynamic Monitoring Framework for Spring Low-Temperature Disasters Affecting Winter Wheat: Exploring Environmental Coercion and Mitigation Mechanisms

by Meixuan Li, Zhiguo Huo, Qianchuan Mi, Lei Zhang, Jianying Yang, Fengyin Zhang, Rui Kong, Yi Wang and Yuxin Huo

Agronomy 2025, 15(2), 337; https://doi.org/10.3390/agronomy15020337 - 28 Jan 2025

Cited by 1 | Viewed by 822

Abstract

The implementation of real-time dynamic monitoring of disaster formation and severity is essential for the timely adoption of disaster prevention and mitigation measures, which in turn minimizes disaster-related losses and safeguards agricultural production safety. This study establishes a low-temperature disaster (LTD) monitoring system [...] Read more.

The implementation of real-time dynamic monitoring of disaster formation and severity is essential for the timely adoption of disaster prevention and mitigation measures, which in turn minimizes disaster-related losses and safeguards agricultural production safety. This study establishes a low-temperature disaster (LTD) monitoring system based on machine learning algorithms, which primarily consists of a module for identifying types of disasters and a module for simulating the evolution of LTDs. This study firstly employed the KNN model combined with a piecewise function to determine the daily dynamic minimum critical temperature for low-temperature stress (LTS) experienced by winter wheat in the Huang-Huai-Hai (HHH) region after regreening, with the fitting model’s R², RMSE, MAE, NRMSE, and MBE values being 0.95, 0.79, 0.53, 0.13, and 1.716 × 10⁻¹¹, respectively. This model serves as the foundation for determining the process by which winter wheat is subjected to LTS. Subsequently, using the XGBoost algorithm to analyze the differences between spring frost and cold damage patterns, a model for identifying types of spring LTDs was developed. The validation accuracy of the model reached 86.67%. In the development of the module simulating the evolution of LTDs, the XGBoost algorithm was initially employed to construct the Low-Temperature Disaster Index (LTDI), facilitating the daily identification of LTD occurrences. Subsequently, the Low-Temperature Disaster Process Accumulation Index (LDPI) is utilized to quantify the severity of the disaster. Validation results indicate that 79.81% of the test set samples exhibit a severity level consistent with historical records. An analysis of the environmental stress-mitigation mechanisms of LTDs reveals that cooling induced by cold air passage and ground radiation are the primary stress mechanisms in the formation of LTDs. In contrast, the release of latent heat from water vapor upon cooling and the transfer of sensible heat from soil moisture serve as the principal mitigation mechanisms. In summary, the developed monitoring framework for LTDs, based on environmental patterns of LTD formation, demonstrates strong generalization capabilities in the HHH region, enabling daily dynamic assessments of the evolution and severity of LTDs. Full article

(This article belongs to the Special Issue Crop Production in the Era of Climate Change)

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17 pages, 1079 KB

Open AccessEditor’s ChoiceReview

Effects of Hydrothermal Carbonization Conditions on the Characteristics of Hydrochar and Its Application as a Soil Amendment: A Review

by Xuyang Wang, Jia Duo, Zhengzhong Jin, Fan Yang, Tianyi Lai and Elendu Collins

Agronomy 2025, 15(2), 327; https://doi.org/10.3390/agronomy15020327 - 27 Jan 2025

Cited by 2 | Viewed by 2994

Abstract

Hydrochar (HC) has received increasing attention due to its potential impact on soil amendment. The process parameters of hydrothermal carbonization (HTC) have a significant impact on the characterization of HC, and HC as a soil amendment has effects on soil properties. Therefore, this [...] Read more.

Hydrochar (HC) has received increasing attention due to its potential impact on soil amendment. The process parameters of hydrothermal carbonization (HTC) have a significant impact on the characterization of HC, and HC as a soil amendment has effects on soil properties. Therefore, this work summarizes the effects of feedstock type, temperature, residence time, and solid–liquid ratio on the characteristics of HC, and analyzes the effects of HC on soil by HC addition. The feedstock type determined the characteristics of the HC. Temperature had the greatest effect on HC properties, while residence time had a similar but smaller effect than temperature had. The residence time did not affect the characteristics of the HC when HTC was carried out to a certain extent. Solid–liquid ratio determined the characteristics of HC, but research in this area is lacking. Moisture is a crucial factor in plant growth. Compared to other soils, HC significantly increased the water-holding capacity (WHC) in sandy soils. HC is rich in nutrients and micronutrients, making it potentially useful as a fertilizer. The toxicity of HC may inhibit plant growth but may be ignored for poor soil. This review aims to provide recommendations for HC as a soil amendment and to identify areas where further research is needed. Full article

(This article belongs to the Section Agricultural Biosystem and Biological Engineering)

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19 pages, 5634 KB

Open AccessEditor’s ChoiceArticle

Construction of Orchard Agricultural Machinery Dispatching Model Based on Improved Beetle Optimization Algorithm

by Lixing Liu, Hongjie Liu, Jianping Li, Pengfei Wang and Xin Yang

Agronomy 2025, 15(2), 323; https://doi.org/10.3390/agronomy15020323 - 27 Jan 2025

Cited by 2 | Viewed by 854

Abstract

In order to enhance orchard agricultural efficiency and lower fruit production expenses, we propose a BL-DBO (Beetle Optimization Algorithm introducing Bernoulli mapping and Lévy flights) to solve the agricultural machinery dispatching model within the orchard area. First, we analyze the agricultural machinery dispatching [...] Read more.

In order to enhance orchard agricultural efficiency and lower fruit production expenses, we propose a BL-DBO (Beetle Optimization Algorithm introducing Bernoulli mapping and Lévy flights) to solve the agricultural machinery dispatching model within the orchard area. First, we analyze the agricultural machinery dispatching problem in the orchard area and establish its mathematical model with the objective of minimizing dispatching costs as a constraint. To tackle the problems of uneven individual position distribution and the risk of becoming stuck in local optimal solutions in the traditional DBO algorithm, we introduce Bernoulli mapping during the initialization phase of the DBO. This method ensures a uniform distribution of the initialized population. Furthermore, during the iterative process of the algorithm, we incorporated the Lévy flight approach into the positional update equations for beetles involved in breeding, foraging, and theft activities within the DBO. This helps the beetles escape from local optimal solutions. Finally, we conduct experiments based on location information of Shunping Shunnong Orchard and fruit trees in Shijiazhuang. The results indicate that, compared to dispatching using human experience and the traditional DBO algorithm, the dispatching results generated by the BL-DBO not only reduce the number of agricultural machinery purchases but also decrease the energy loss from non-working distances of the machinery, effectively saving fruit production costs. Full article

(This article belongs to the Section Precision and Digital Agriculture)

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38 pages, 5464 KB

Open AccessEditor’s ChoiceArticle

Early-Stage Impacts of Irrigated Conservation Agriculture on Soil Physical Properties and Crop Performance in a French Mediterranean System

by Juan David Dominguez-Bohorquez, Claire Wittling, Bruno Cheviron, Sami Bouarfa, Nicolas Urruty, Jean-Marie Lopez and Cyril Dejean

Agronomy 2025, 15(2), 299; https://doi.org/10.3390/agronomy15020299 - 25 Jan 2025

Cited by 2 | Viewed by 1120

Abstract

The Mediterranean region faces intensified climate change effects, increasing irrigation demands to sustain crop yields and increasing pressure on water resources. Adaptive management strategies such as conservation agriculture (CA) offer potential benefits for soil quality and water use efficiency. However, there is limited [...] Read more.

The Mediterranean region faces intensified climate change effects, increasing irrigation demands to sustain crop yields and increasing pressure on water resources. Adaptive management strategies such as conservation agriculture (CA) offer potential benefits for soil quality and water use efficiency. However, there is limited research on the short-term effects of this farming system under irrigated Mediterranean climatic conditions. This study aimed to explore the short-term impacts of conservation agriculture (no tillage, cover crops and crop rotation) on the soil properties, water flows and crop and water productivity in a French Mediterranean agrosystem of irrigated field crops, using a multifactorial approach. From 2021 to 2023, maize, sorghum and soybean were grown successively under either conventional tillage (CT) or conservation agriculture (CA), combined with sprinkler irrigation, subsurface drip irrigation or non-irrigated conditions. The dynamics of the surface soil properties (bulk density, penetration resistance, soil temperature), water flows (infiltration, soil evaporation) and agronomic indicators (leaf area index, crop yield, water productivity) were measured across the three cropping seasons. In the pedoclimatic conditions of the study, CA was shown to clearly impact the soil properties, water flows and crop yields, from the first year of adoption. CA practices caused an increased bulk density and soil resistance penetration, leading to decreased quasi-steady ponded infiltration in the surface horizon, particularly in the CA–subsurface drip and CA–non-irrigated conditions. These effects were also reflected in the leaf area index, crop yield and water productivity, with CA showing lower values compared to CT. Crop residues in CA reduced soil evaporation, particularly under sprinkler irrigation. However, this benefit diminished as the residues decomposed, leading to soil evaporation rates comparable to those observed in CT. Agronomic indicators were better under sprinkler irrigation than under subsurface drip irrigation. Overall, compaction emerged as a significant challenge in the adoption of CA, considering its negative impact on crop yields. Full article

(This article belongs to the Special Issue Conservation Agricultural Practices for Improving Crop Production and Quality)

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18 pages, 667 KB

Open AccessEditor’s ChoiceArticle

Effects of Hexanal Supplementation on Volatile Compound Profiles and Quality Parameters of ‘Fuji Kiku’ Apples During Cold Storage and Shelf Life

by Erika Jesenko, Rajko Vidrih and Emil Zlatić

Agronomy 2025, 15(2), 292; https://doi.org/10.3390/agronomy15020292 - 24 Jan 2025

Cited by 1 | Viewed by 1689

Abstract

The effects of hexanal supplementation in the storage atmosphere of ‘Fuji Kiku’ apples were investigated. The contents of volatile compounds (VOCs) in the headspace emitted by apple fruit during cold storage and in the headspace of apple fruit and juice during shelf life [...] Read more.

The effects of hexanal supplementation in the storage atmosphere of ‘Fuji Kiku’ apples were investigated. The contents of volatile compounds (VOCs) in the headspace emitted by apple fruit during cold storage and in the headspace of apple fruit and juice during shelf life were determined. Hexanal treatment during storage significantly affected the VOC profile by stimulating the production or retention of key esters, including hexyl acetate, ethyl acetate, and butyl 2-methylbutanoate, during cold storage. Supplementation of hexanal also increased the production of linear esters, especially hexyl acetate, and promoted the formation of branched esters such as ethyl 2-methylbutanoate and hexyl 2-methylbutanoate during shelf life. Hexanal also increased the alcohol concentrations, with a significant increase in hexanol and 2-pentanol. Partial least squares discriminant analysis showed clear separation between control and hexanal-treated samples, with compounds like butyl hexanoate and 2-methyl-1-butanol being the most influential. Apple juice extracted from the flesh of hexanal-treated apples exhibited higher concentrations of key VOCs, including 2-methylbutyl acetate, hexyl acetate, and 2-methyl-1-butanol. No significant differences in firmness were observed; however, hexanal showed an inhibitory effect on the colour development of fruit. This study highlights the potential of hexanal in influencing aroma-related compounds and provides insight into strategies to improve postharvest aroma in apples. Full article

(This article belongs to the Section Horticultural and Floricultural Crops)

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26 pages, 1633 KB

Open AccessEditor’s ChoiceArticle

Sown Diversity Effects on the C and N Cycle and Interactions with Fertilization

by Salvador Aljazairi, Angela Ribas, Rosa Llurba, Juan Pedro Ferrio, Jordi Voltas, Salvador Nogués and Maria Teresa Sebastiá

Agronomy 2025, 15(2), 287; https://doi.org/10.3390/agronomy15020287 - 23 Jan 2025

Cited by 3 | Viewed by 3365

Abstract

A better understanding of the role of plant composition and N cycle on agroecosystems is necessary, as these will be affected by future developments in agriculture intensification. To explore the effect of plant diversity on yield and carbon (C) and nitrogen (N) balances [...] Read more.

A better understanding of the role of plant composition and N cycle on agroecosystems is necessary, as these will be affected by future developments in agriculture intensification. To explore the effect of plant diversity on yield and carbon (C) and nitrogen (N) balances in forage mixtures, identifying potential co-benefits between functions. We analyzed results from a field experiment where plants of three forage species (a grass, a legume, and a non-legume forb) were cultivated in monocultures and mixtures. Three years after sward establishment, dry matter yield, together with δ¹⁵N, δ¹³C, and C and N content in plant and soil material were measured. In addition, we analyzed a second scenario to investigate the effect of fertigation with pig slurry (δ¹⁵N = +8.4‰) on the C and N balances of forage species. Results support the hypothesis that C and N allocation is affected by plant diversity. Plant composition affected N source (% N derived from air, % N derived from soil, and % N transferred in mixtures). In addition, sown diversity increased yield and modulated C and N balances. The δ¹⁵N of samples was affected by both plant composition and fertigation. These results are consistent with previous work showing strong plant composition effects on N-balances, and the potential role that legumes play in enhancing nitrogen sources (derived from the atmosphere) into forage mixture systems. This study contributes to the prediction of suitable sown plant community composition and N management for the optimum agriculture with increased productivity and at the same time reduced environmental impact. Full article

(This article belongs to the Special Issue Enhancement of Grassland Function and Productivity with Legumes and Other Forbs)

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25 pages, 2051 KB

Open AccessEditor’s ChoiceReview

Biochar in the Bioremediation of Metal-Contaminated Soils

by Małgorzata Majewska and Agnieszka Hanaka

Agronomy 2025, 15(2), 273; https://doi.org/10.3390/agronomy15020273 - 22 Jan 2025

Cited by 5 | Viewed by 3433

Abstract

Biochar is produced from a wide variety of feedstocks (algal biomass, forest, agricultural and food residues, organic fraction of municipal waste, sewage sludge, manure) by thermochemical conversion. In general, it is a dark, porous material with a large surface area, low density, high [...] Read more.

Biochar is produced from a wide variety of feedstocks (algal biomass, forest, agricultural and food residues, organic fraction of municipal waste, sewage sludge, manure) by thermochemical conversion. In general, it is a dark, porous material with a large surface area, low density, high cation exchange capacity, and alkaline pH. By reducing the content of harmful substances in the soil, the application of biochar increases the activity, number, and diversity of microorganisms and improves plant growth in contaminated areas. The aim of the review was to explore the advantages and drawbacks of biochar use in soil bioremediation. General issues such as methods of biochar production, its physical and chemical properties, and various applications are presented. As biochar is an efficient adsorbent of heavy metals, the review focused on its benefits in (I) soil bioremediation, (II) improvement of soil parameters, (III) reduction of metal toxicity and bioaccumulation, (IV) positive interaction with soil microorganisms and soil enzymatic activity, and (V) promotion of plant growth. On the other hand, the potential risks of biochar formulation and utilization were also discussed, mainly related to the presence of heavy metals in biochar, dust hazard, and greenhouse gases emission. Full article

(This article belongs to the Special Issue Research Progress in Biochar and Microbial Remediation for Heavy Metal Agricultural Soil)

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23 pages, 6326 KB

Open AccessEditor’s ChoiceArticle

The Physiological Mechanism of Exogenous Melatonin Regulating Salt Tolerance in Eggplant Seedlings

by Yu Zhang, Li Jia, Han Wang, Haikun Jiang, Qiangqiang Ding, Dekun Yang, Congsheng Yan and Xiaomin Lu

Agronomy 2025, 15(2), 270; https://doi.org/10.3390/agronomy15020270 - 22 Jan 2025

Cited by 3 | Viewed by 1216

Abstract

There is little study on melatonin’s ability to prevent salt damage in eggplants, despite the fact that it is a strong antioxidant in plants that has been found to help mitigate a variety of adverse challenges. In this study, we used “Anhui Eggplant [...] Read more.

There is little study on melatonin’s ability to prevent salt damage in eggplants, despite the fact that it is a strong antioxidant in plants that has been found to help mitigate a variety of adverse challenges. In this study, we used “Anhui Eggplant No.8” as the test material and simulated salt stress by irrigating the roots with 150 mmol·L NaCl solution. Subsequently, we treated the eggplants with different concentrations of exogenous melatonin (0, 50, 100, 150, 200, 250 μmol·L) and assessed the plant traits and an array of physiological and biochemical indices following melatonin application to observe the impact of salt stress. Our study results indicate that exogenous melatonin at a concentration of 200 μmol·L can significantly alleviate the inhibition of eggplant photosynthesis under salt stress by increasing the content of chlorophyll in leaves and the activity of antioxidant enzymes. This leads to a notable increase in the levels of non-enzyme antioxidants and osmotic regulatory substances. As a result, the antioxidant capacity of the eggplants is enhanced, the degree of membrane lipid peroxidation is reduced, and the growth of eggplant seedlings under salt stress is effectively promoted, thereby strengthening the salt tolerance of eggplant seedlings. Fluorescence quantitative data analysis indicates that SmCAT4 is indeed a gene that positively regulates salt stress. However, in the SmPPO family, we did not find any genes that respond to salt stress. This research provides a theoretical foundation for improving the yield productivity and quality of eggplants under protected farming by clarifying the physiological mechanism by which melatonin controls the salt tolerance of eggplant seedlings. Full article

(This article belongs to the Special Issue Progress and Innovations in Breeding Objectives and Technologies for Solanaceae Crops Production)

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18 pages, 4900 KB

Open AccessEditor’s ChoiceArticle

Stem-Leaf Segmentation and Morphological Traits Extraction in Rapeseed Seedlings Using a Three-Dimensional Point Cloud

by Binqian Sun, Muhammad Zain, Lili Zhang, Dongwei Han and Chengming Sun

Agronomy 2025, 15(2), 276; https://doi.org/10.3390/agronomy15020276 - 22 Jan 2025

Cited by 3 | Viewed by 1338

Abstract

Developing accurate, non-destructive, and automated methods for monitoring the phenotypic traits of rapeseed is crucial for improving yield and quality in modern agriculture. We used a line laser binocular stereo vision technology system to obtain the three-dimensional (3D) point cloud data of different [...] Read more.

Developing accurate, non-destructive, and automated methods for monitoring the phenotypic traits of rapeseed is crucial for improving yield and quality in modern agriculture. We used a line laser binocular stereo vision technology system to obtain the three-dimensional (3D) point cloud data of different rapeseed varieties (namely Qinyou 7, Zheyouza 108, and Huyou 039) at the seedling stage, and the phenotypic traits of rapeseed were extracted from those point clouds. After pre-processing the rapeseed point clouds with denoising and segmentation, the plant height, leaf length, leaf width, and leaf area of the rapeseed in the seedling stage were extracted by a series of algorithms and were evaluated for accuracy with the manually measured values. The following results were obtained: the R² values for plant height data between the extracted values of the 3D point cloud and the manually measured values reached 0.934, and the RMSE was 0.351 cm. Similarly, the R² values for leaf length of the three kinds of rapeseed were all greater than 0.95, and the RMSEs for Qinyou 7, Zheyouza 108, and Huyou 039 were 0.134 cm, 0.131 cm, and 0.139 cm, respectively. Regarding leaf width, R² was greater than 0.92, and the RMSEs were 0.151 cm, 0.189 cm, and 0.150 cm, respectively. Further, the R² values for leaf area were all greater than 0.98 with RMSEs of 0.296 cm², 0.231 cm² and 0.259 cm², respectively. The results extracted from the 3D point cloud are reliable and have high accuracy. These results demonstrate the potential of 3D point cloud technology for automated, non-destructive phenotypic analysis in rapeseed breeding programs, which can accelerate the development of improved varieties. Full article

(This article belongs to the Special Issue Unmanned Farms in Smart Agriculture)

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20 pages, 4921 KB

Open AccessEditor’s ChoiceArticle

Drip Fertigation with Moderate Nitrogen Topdressing Rate Achieves High Nitrogen and Water Use Efficiencies for Irrigated Wheat

by Jin Tong, Yulei Xiong, Yu Lu, Wen Li, Wen Lin, Jianfu Xue, Min Sun, Yuechao Wang and Zhiqiang Gao

Agronomy 2025, 15(2), 259; https://doi.org/10.3390/agronomy15020259 - 21 Jan 2025

Cited by 2 | Viewed by 1110

Abstract

Drip fertigation (DF) can improve yield, water use efficiency (WUE), and nitrogen use efficiency (NUE, grain production per unit of the sum of soil inherent mineral N and fertilizer N), as well as reduce the risk of environmental pollution compared with flood irrigation [...] Read more.

Drip fertigation (DF) can improve yield, water use efficiency (WUE), and nitrogen use efficiency (NUE, grain production per unit of the sum of soil inherent mineral N and fertilizer N), as well as reduce the risk of environmental pollution compared with flood irrigation and N fertilizer broadcast (FB). Previously, we showed that DF enhanced the response of the yield to the N topdressing rate (NTR), but the underlying mechanisms associated with the soil N supply, root architecture, and N uptake remain unclear. We conducted a field experiment by testing six N treatments (no N applied, and NTRs of 0, 40, 80, 120, and 160 kg ha⁻¹, denoted as N0, T0, T40, T80, T120, and T160, respectively) under DF and FB from 2021 to 2023. Compared with FB, the NUE and WUE were 4.8–4.9% and 10.0–10.5% higher under DF. The higher NUE was due to an improvement in N uptake efficiency (6.1–7.7%) resulting from the enhanced aboveground N uptake (AGN). The greater AGN under DF was attributed to the higher soil N availability at the soil depth of 0–40 cm. DF decreased the residual soil NO₃⁻-N at a depth of 40–200 cm but increased the NO₃⁻-N at a depth of 0–40 cm. In addition, DF combined with T80 achieved high root length density, surface density, and dry weight density and improved NUE and WUE. DF combined with T80 achieved high yield and efficient utilization of water and N, and the NTR threshold was 61.75–119.50 kg ha⁻¹, in which the production conditions were similar to those of the experimental site. Our results provide a reference for high-efficiency water and N fertilizer usage for irrigated winter wheat production in North China. Full article

(This article belongs to the Topic High-Efficiency Utilization of Water-Fertilizer Resources and Green Production of Crops)

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16 pages, 1737 KB

Open AccessEditor’s ChoiceArticle

A Novel Large-Particle Slow-Release Fertilizer Improves Nutrient Use Efficiency and Yield of Cassava by Boundary Layer Limitation

by Cuicui He, Hua Wang, Guichun Li, Jie Huang, Dengfeng Wang, Xindao Qin, Wen Zhang, Dongming Wu, Yuanda Jiu, Min Zhao, Yi Xie, Qingmian Chen, Rongfei Zhou and Minggang Xu

Agronomy 2025, 15(2), 261; https://doi.org/10.3390/agronomy15020261 - 21 Jan 2025

Cited by 2 | Viewed by 1300

Abstract

Cassava is a crucial food and economic crop in tropical regions globally. In response to challenges in fertilizer use efficiency for cassava cultivation, which is traditionally compromised by extensive leaching and broad root zone distribution, a novel large-particle slow-release fertilizer (LPF) was developed [...] Read more.

Cassava is a crucial food and economic crop in tropical regions globally. In response to challenges in fertilizer use efficiency for cassava cultivation, which is traditionally compromised by extensive leaching and broad root zone distribution, a novel large-particle slow-release fertilizer (LPF) was developed in this study. This fertilizer was synthesized through solution polymerization using non-metallic minerals and seaweed extract. Compared to conventional SFs that release 99% of nutrients within 1 min, the LPF prolonged the release duration to 51 min under optimal synthesis conditions: drying temperature of 80 °C, total extrusion force of 40 t, drying air pressure of −0.40 bar, auxiliary mineral proportion of 50%, and water content of 15%. Microbeam characterization (e.g., FTIR) and kinetic modeling revealed that the superior performance of LPF resulted from mineral crystal enrichment in the outer layer of fertilizer granules, facilitating intra-particle diffusion processes and imposing boundary layer limitations on nutrient release (e.g., N, P, and K). Field experiments validated the slow-release performance of the fertilizer. Notably, soil treated with LPF exhibited superior nutrient retention in the topsoil layer (0–20 cm) both horizontally and vertically. Even with two-thirds of the nutrient content relative to conventional fertilizers, LPF also displayed significant improvements in crop yield, partial factor productivity, and agronomic efficiency by 33.56%, 200.01%, and 513.84%, respectively. These results indicate that LPF presents a promising solution for sustainable cassava cultivation. Full article

(This article belongs to the Topic High-Efficiency Utilization of Water-Fertilizer Resources and Green Production of Crops)

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27 pages, 6049 KB

Open AccessEditor’s ChoiceArticle

Global Trends in Conservation Agriculture and Climate Change Research: A Bibliometric Analysis

by Julio Román-Vázquez, Rosa M. Carbonell-Bojollo, Óscar Veroz-González, Ligia Maria Maraschi da Silva Piletti, Francisco Márquez-García, L. Javier Cabeza-Ramírez and Emilio J. González-Sánchez

Agronomy 2025, 15(1), 249; https://doi.org/10.3390/agronomy15010249 - 20 Jan 2025

Cited by 2 | Viewed by 2019

Abstract

This study provides a bibliometric analysis of global scientific production on Conservation Agriculture (CA) and its relationship with climate change mitigation. Using data from the Scopus and Web of Science databases, the research encompassed 650 articles published between 1995 and 2022. The analysis [...] Read more.

This study provides a bibliometric analysis of global scientific production on Conservation Agriculture (CA) and its relationship with climate change mitigation. Using data from the Scopus and Web of Science databases, the research encompassed 650 articles published between 1995 and 2022. The analysis revealed significant growth in the number of publications over the past three decades, driven by increasing global interest in sustainable agricultural practices. The findings highlight key themes, including no-tillage, soil organic carbon, and greenhouse gas emissions. Collaboration networks were mapped, identifying major contributors, such as the USA, Brazil, and China, alongside thematic clusters emphasizing carbon sequestration and soil management. Results indicate that CA research is increasingly focused on its potential to mitigate climate change, particularly through practices like no-tillage, vegetative cover, and crop rotation. While carbon sequestration has been central to CA research, recent studies have expanded to include nitrous oxide and methane emissions, indicating a broadening conceptual framework. This analysis underscores the importance of CA in addressing climate challenges and offers insights into emerging research areas, such as regional adaptations and the long-term effects of no-till systems. The findings aim to guide future research and policy development in sustainable agriculture and climate mitigation. Full article

(This article belongs to the Special Issue Climate-Smart Agriculture for a Changing World)

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19 pages, 2560 KB

Open AccessEditor’s ChoiceArticle

Evaluation of Rapeseed Leave Segmentation Accuracy Using Binocular Stereo Vision 3D Point Clouds

by Lili Zhang, Shuangyue Shi, Muhammad Zain, Binqian Sun, Dongwei Han and Chengming Sun

Agronomy 2025, 15(1), 245; https://doi.org/10.3390/agronomy15010245 - 20 Jan 2025

Cited by 3 | Viewed by 1299

Abstract

Point cloud segmentation is necessary for obtaining highly precise morphological traits in plant phenotyping. Although a huge development has occurred in point cloud segmentation, the segmentation of point clouds from complex plant leaves still remains challenging. Rapeseed leaves are critical in cultivation and [...] Read more.

Point cloud segmentation is necessary for obtaining highly precise morphological traits in plant phenotyping. Although a huge development has occurred in point cloud segmentation, the segmentation of point clouds from complex plant leaves still remains challenging. Rapeseed leaves are critical in cultivation and breeding, yet traditional two-dimensional imaging is susceptible to reduced segmentation accuracy due to occlusions between plants. The current study proposes the use of binocular stereo-vision technology to obtain three-dimensional (3D) point clouds of rapeseed leaves at the seedling and bolting stages. The point clouds were colorized based on elevation values in order to better process the 3D point cloud data and extract rapeseed phenotypic parameters. Denoising methods were selected based on the source and classification of point cloud noise. However, for ground point clouds, we combined plane fitting with pass-through filtering for denoising, while statistical filtering was used for denoising outliers generated during scanning. We found that, during the seedling stage of rapeseed, a region-growing segmentation method was helpful in finding suitable parameter thresholds for leaf segmentation, and the Locally Convex Connected Patches (LCCP) clustering method was used for leaf segmentation at the bolting stage. Furthermore, the study results show that combining plane fitting with pass-through filtering effectively removes the ground point cloud noise, while statistical filtering successfully denoises outlier noise points generated during scanning. Finally, using the region-growing algorithm during the seedling stage with a normal angle threshold set at 5.0/180.0* M_PI and a curvature threshold set at 1.5 helps to avoid the under-segmentation and over-segmentation issues, achieving complete segmentation of rapeseed seedling leaves, while the LCCP clustering method fully segments rapeseed leaves at the bolting stage. The proposed method provides insights to improve the accuracy of subsequent point cloud phenotypic parameter extraction, such as rapeseed leaf area, and is beneficial for the 3D reconstruction of rapeseed. Full article

(This article belongs to the Special Issue Unmanned Farms in Smart Agriculture)

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23 pages, 25322 KB

Open AccessEditor’s ChoiceArticle

Prediction of Winter Wheat Parameters with Planet SuperDove Imagery and Explainable Artificial Intelligence

by Gabriele De Carolis, Vincenzo Giannico, Leonardo Costanza, Francesca Ardito, Anna Maria Stellacci, Afwa Thameur, Sergio Ruggieri, Sabina Tangaro, Marcello Mastrorilli, Nicola Sanitate and Simone Pietro Garofalo

Agronomy 2025, 15(1), 241; https://doi.org/10.3390/agronomy15010241 - 19 Jan 2025

Cited by 1 | Viewed by 3088

Abstract

This study investigated the application of high-resolution satellite imagery from SuperDove satellites combined with machine learning algorithms to estimate the spatiotemporal variability of some winter wheat parameters, including the relative leaf chlorophyll content (RCC), relative water content (RWC), and aboveground dry matter (DM). [...] Read more.

This study investigated the application of high-resolution satellite imagery from SuperDove satellites combined with machine learning algorithms to estimate the spatiotemporal variability of some winter wheat parameters, including the relative leaf chlorophyll content (RCC), relative water content (RWC), and aboveground dry matter (DM). The research was carried out within an experimental field in Southern Italy during the 2024 growing season. Different machine learning (ML) algorithms were trained and compared using spectral band data and calculated vegetation indices (VIs) as predictors. Model performance was assessed using R² and RMSE. The ML models tested were random forest (RF), support vector regressor (SVR), and extreme gradient boosting (XGB). RF outperformed the other ML algorithms in the prediction of RCC when using VIs as predictors (R² = 0.81) and in the prediction of the RWC and DM when using spectral bands data as predictors (R² = 0.71 and 0.87, respectively). Model explainability was assessed with the SHAP method. A SHAP analysis highlighted that GNDVI, Cl1, and NDRE were the most important VIs for predicting RCC, while yellow and red bands were the most important for DM prediction, and yellow and nir bands for RWC prediction. The best model found for each target was used to model its seasonal trend and produce a variability map. This approach highlights the potential of integrating ML and high-resolution satellite imagery for the remote monitoring of wheat, which can support sustainable farming practices. Full article

(This article belongs to the Section Precision and Digital Agriculture)

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18 pages, 2409 KB

Open AccessEditor’s ChoiceArticle

Effects of Film-Bottomed Treatment on Absorbability and Translocation of Nitrogen in Spring Wheat in Arid Area

by Zizhen Li, Xiaolei Zhou, Qing Tian, Low Pak Sum, Yuee Yan and Xujiao Zhou

Agronomy 2025, 15(1), 240; https://doi.org/10.3390/agronomy15010240 - 19 Jan 2025

Cited by 1 | Viewed by 1145

Abstract

Plastic film-bottomed treatment (FBT) is a critical agricultural practice in arid regions, aimed at enhancing crop productivity by improving soil moisture retention and nutrient availability. However, the effects of different depths of film-bottomed treatment (DFBT) on nitrogen (N) absorption and translocation in spring [...] Read more.

Plastic film-bottomed treatment (FBT) is a critical agricultural practice in arid regions, aimed at enhancing crop productivity by improving soil moisture retention and nutrient availability. However, the effects of different depths of film-bottomed treatment (DFBT) on nitrogen (N) absorption and translocation in spring wheat remain inadequately understood. We conducted a field experiment on sandy soil to investigate the effects of different DFBT depths (60, 70, 80, 90, and 100 cm) and on total N absorption amount (TNAA), total N translocation amount (TNTA) in all nutritive organs, grain nitrogen content (GN), and grain yield (GY). Morphological measurements included GY, GN, TNAA, and TNTA in the stem, sheath, leaf, spike axis, kernel husk (SAKH), and culm. The results showed that FBT significantly reduced soil moisture loss, with the 100 cm depth reducing soil leakage by 59.6% (p < 0.001). At the flowering stage, nitrogen derived from fertilizer (NDF) and soil nitrogen (NDS) were significantly higher at the 80 cm depth (p < 0.001). At maturity, the total nitrogen absorption amount (TNAA) and translocation amount (TNTA) in the main stem and across nutrient organs were significantly higher under the 80 cm DFBT (p < 0.001), leading to improved nitrogen use efficiency. The correlation between TNTA and GN was strongest at 80 cm (p < 0.001). Grain yield (GY) and GN were optimized at intermediate depths, particularly at 80 cm, suggesting this depth provides an optimal balance between water retention and drainage efficiency. These findings underscore the importance of optimizing DFBT depth, particularly at 80 cm, to achieve enhanced water retention, efficient nitrogen utilization, and improved crop productivity in arid agricultural systems. This research provides critical insights into sustainable agricultural practices under water-limited conditions, offering practical guidance for improving food security in arid regions. Full article

(This article belongs to the Special Issue Advances in Tillage Methods to Improve the Yield and Quality of Crops)

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16 pages, 7156 KB

Open AccessEditor’s ChoiceArticle

Effects of Serendipita indica on the Morphological and Physiological Characteristics of Agrostis stolonifera L. Under Drought Stress

by Chuhong Lin, Wenxu Hu, Xin Qin, Yongjun Fei and Die Hu

Agronomy 2025, 15(1), 234; https://doi.org/10.3390/agronomy15010234 - 18 Jan 2025

Cited by 3 | Viewed by 1093

Abstract

This study investigates the effect of Serendipita indica inoculation on the growth, structural characteristics of leaf epidermis, photosynthetic parameters, and antioxidant and osmoregulation capacities of Agrostis stolonifera L. under different drought stresses (normal moisture management: at 70–75% of the field capacity, low drought: [...] Read more.

This study investigates the effect of Serendipita indica inoculation on the growth, structural characteristics of leaf epidermis, photosynthetic parameters, and antioxidant and osmoregulation capacities of Agrostis stolonifera L. under different drought stresses (normal moisture management: at 70–75% of the field capacity, low drought: at 55–60% field capacity, moderate drought: at 40–45% of the field capacity, and severe drought: at 25–30% of the field capacity). The results showed that inoculation with S. indica significantly enhanced the growth potential of A. stolonifera compared to uninoculated controls, and then under drought stress conditions, inoculation with S. indica significantly alleviated the inhibition of the growth and development of A. stolonifera, especially under mild and moderate drought stresses. These improvements were evident in both aboveground and underground parts, leaf relative water content, total root length, and root surface area after 25 days of drought treatments. Inoculated plants also exhibited higher levels of photosynthetic pigments, net photosynthetic rate (Pn), stomatal conductance (Gs), and transpiration rate (Tr) under drought conditions. Additionally, S. indica inoculation significantly increased the activities of catalase (CAT), peroxidase (POD), and ascorbate peroxidase (APX), as well as the soluble sugar, soluble protein, and proline levels under drought-stressed and non-stressed conditions. In addition, the increases in the malondialdehyde (MDA) content and relative conductivity (RC) of leaves were significantly lower in the inoculated group compared to the control group. In conclusion, the symbiosis with S. indica promotes the growth of A. stolonifera under drought stress, likely by enhancing photosynthesis, osmoregulatory substances, and antioxidant enzyme activities. Full article

(This article belongs to the Section Plant-Crop Biology and Biochemistry)

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18 pages, 5456 KB

Open AccessEditor’s ChoiceArticle

Smart Agricultural Pest Detection Using I-YOLOv10-SC: An Improved Object Detection Framework

by Wenxia Yuan, Lingfang Lan, Jiayi Xu, Tingting Sun, Xinghua Wang, Qiaomei Wang, Jingnan Hu and Baijuan Wang

Agronomy 2025, 15(1), 221; https://doi.org/10.3390/agronomy15010221 - 17 Jan 2025

Cited by 3 | Viewed by 1739

Abstract

Aiming at the problems of insufficient detection accuracy and high false detection rates of traditional pest detection models in the face of small targets and incomplete targets, this study proposes an improved target detection network, I-YOLOv10-SC. The network leverages Space-to-Depth Convolution to enhance [...] Read more.

Aiming at the problems of insufficient detection accuracy and high false detection rates of traditional pest detection models in the face of small targets and incomplete targets, this study proposes an improved target detection network, I-YOLOv10-SC. The network leverages Space-to-Depth Convolution to enhance its capability in detecting small insect targets. The Convolutional Block Attention Module is employed to improve feature representation and attention focus. Additionally, Shape Weights and Scale Adjustment Factors are introduced to optimize the loss function. The experimental results show that compared with the original YOLOv10, the model generated by the improved algorithm improves the accuracy by 5.88 percentage points, the recall rate by 6.67 percentage points, the balance score by 6.27 percentage points, the mAP value by 4.26 percentage points, the bounding box loss by 18.75%, the classification loss by 27.27%, and the feature point loss by 8%. The model oscillation has also been significantly improved. The enhanced I-YOLOv10-SC network effectively addresses the challenges of detecting small and incomplete insect targets in tea plantations, offering high precision and recall rates, thus providing a solid technical foundation for intelligent pest monitoring and precise prevention in smart tea gardens. Full article

(This article belongs to the Special Issue Modern Control of Biotic Stress in Crops: Intelligent Detection and Precision Pesticide Application)

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20 pages, 6410 KB

Open AccessEditor’s ChoiceArticle

An Improved iTransformer with RevIN and SSA for Greenhouse Soil Temperature Prediction

by Fahai Wang, Yiqun Wang, Wenbai Chen and Chunjiang Zhao

Agronomy 2025, 15(1), 223; https://doi.org/10.3390/agronomy15010223 - 17 Jan 2025

Cited by 3 | Viewed by 1488

Abstract

In contemporary agricultural practices, greenhouses serve as a critical component of infrastructure, where soil temperature plays a vital role in enhancing pest management and regulating crop growth. However, achieving precise greenhouse environmental control continues to pose a significant challenge. In this context, the [...] Read more.

In contemporary agricultural practices, greenhouses serve as a critical component of infrastructure, where soil temperature plays a vital role in enhancing pest management and regulating crop growth. However, achieving precise greenhouse environmental control continues to pose a significant challenge. In this context, the present study proposes ReSSA-iTransformer, an advanced predictive model engineered to accurately forecast soil temperatures within greenhouses across diverse temporal scales, encompassing both long-term and short-term horizons. This model capitalizes on the iTransformer time-series forecasting framework and integrates Singular Spectrum Analysis (SSA) to decompose environmental variables, thereby augmenting the extraction of pivotal features, such as soil temperature. Furthermore, to mitigate the prevalent distribution shift issues inherent in time-series data, Reversible Instance Normalization (RevIN) is incorporated within the model architecture. ReSSA-iTransformer is adept at executing multi-step forecasts for both extended and immediate future intervals, thereby offering comprehensive predictive capabilities. Empirical evaluations substantiate that ReSSA-iTransformer surpasses conventional models, including LSTM, Informer, and Autoformer, across all assessed metrics. Specifically, it attained R² coefficients of 98.51%, 97.03%, 97.26%, and 94.83%, alongside MAE values of 0.271, 0.501, 0.648, and 1.633 for predictions at 3 h, 6 h, 24 h, and 48 h intervals, respectively. These results highlight the model’s superior accuracy and robustness. Ultimately, ReSSA-iTransformer not only provides dependable soil temperature forecasts but also delivers actionable insights, thereby facilitating enhanced greenhouse management practices. Full article

(This article belongs to the Section Precision and Digital Agriculture)

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18 pages, 6676 KB

Open AccessEditor’s ChoiceArticle

Genetic Mapping for Seed Aging Tolerance Under Multiple Environments in Sweet Corn

by Yanchao Du, Jianting Lin, Haoxuan Jiang, Huating Zhao, Xuebiao Zhang, Ruigang Wang and Faqiang Feng

Agronomy 2025, 15(1), 225; https://doi.org/10.3390/agronomy15010225 - 17 Jan 2025

Cited by 1 | Viewed by 1213

Abstract

Seed vigor significantly impacts seed production and storage. Enhancing seed vigor is a pivotal goal in sweet corn breeding, as improved seed sowing quality is crucial for agricultural development, aiding in better resilience against storage adversities and facilitating long-term germplasm preservation. In this [...] Read more.

Seed vigor significantly impacts seed production and storage. Enhancing seed vigor is a pivotal goal in sweet corn breeding, as improved seed sowing quality is crucial for agricultural development, aiding in better resilience against storage adversities and facilitating long-term germplasm preservation. In this study, a recombinant inbred line (RIL) population, including 158 families, was derived from the aging-tolerant line K62 and the aging-sensitive line K107. Utilizing SNP arrays, genotypes were identified, and a genetic linkage map was constructed. Composite interval mapping was employed to detect quantitative trait loci (QTLs) associated with five seed vigor traits, namely the seedling fresh weight (SFW), germination potential (GP), germination rate (GR), germination index (GI), and vigor index (VI), at three days after artificial aging treatment. Upon analysis, a total of 42 QTLs affecting seed vigor indices were identified over two years. Of these, six were linked to SFW, while the GP, GR, GI, and VI each comprised nine QTLs. Nine QTL clusters were identified, with significant contributions (>10%) from Loci02.1, Loci05.2, Loci06.1, and Loci10.1, ranging from 9.50% to 24.20%, 8.89% to 11.54%, 9.16% to 15.55%, and 7.54% to 17.77%, respectively. Candidate genes were explored within QTL cluster regions based on the aging-induced transcriptomic sequencing data of K62 and K107. Through Gene Ontology enrichment, gene annotation, and expression profiling clustering analyses, 12 positive candidate genes linked to seed aging tolerance were identified. This study provides a foundational understanding of the genetic mechanisms of seed aging tolerance and the innovation of an elite germplasm for seed aging tolerance in sweet corn. Full article

(This article belongs to the Section Crop Breeding and Genetics)

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21 pages, 11846 KB

Open AccessEditor’s ChoiceArticle

Winter Wheat Yield Prediction Using Satellite Remote Sensing Data and Deep Learning Models

by Hongkun Fu, Jian Lu, Jian Li, Wenlong Zou, Xuhui Tang, Xiangyu Ning and Yue Sun

Agronomy 2025, 15(1), 205; https://doi.org/10.3390/agronomy15010205 - 16 Jan 2025

Cited by 5 | Viewed by 2405

Abstract

Accurate crop yield prediction is crucial for formulating agricultural policies, guiding agricultural management, and optimizing resource allocation. This study proposes a method for predicting yields in China’s major winter wheat-producing regions using MOD13A1 data and a deep learning model which incorporates an Improved [...] Read more.

Accurate crop yield prediction is crucial for formulating agricultural policies, guiding agricultural management, and optimizing resource allocation. This study proposes a method for predicting yields in China’s major winter wheat-producing regions using MOD13A1 data and a deep learning model which incorporates an Improved Gray Wolf Optimization (IGWO) algorithm. By adjusting the key parameters of the Convolutional Neural Network (CNN) with IGWO, the prediction accuracy is significantly enhanced. Additionally, the study explores the potential of the Green Normalized Difference Vegetation Index (GNDVI) in yield prediction. The research utilizes data collected from March to May between 2001 and 2010, encompassing vegetation indices, environmental variables, and yield statistics. The results indicate that the IGWO-CNN model outperforms traditional machine learning approaches and standalone CNN models in terms of prediction accuracy, achieving the highest performance with an R² of 0.7587, an RMSE of 593.6 kg/ha, an MAE of 486.5577 kg/ha, and an MAPE of 11.39%. The study finds that April is the optimal period for early yield prediction of winter wheat. This research validates the effectiveness of combining deep learning with remote sensing data in crop yield prediction, providing technical support for precision agriculture and contributing to global food security and sustainable agricultural development. Full article

(This article belongs to the Section Precision and Digital Agriculture)

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14 pages, 295 KB

Open AccessEditor’s ChoiceReview

Novel Breeding Techniques and Strategies for Enhancing Greenhouse Vegetable Product Quality

by Julia Weiss and Nazim S. Gruda

Agronomy 2025, 15(1), 207; https://doi.org/10.3390/agronomy15010207 - 16 Jan 2025

Cited by 7 | Viewed by 2682

Abstract

With its controlled environment, protected cultivation is advantageous and effective for breeding programs. This distinct setting also guarantees that fresh vegetables meet high quality standards. The controlled environment allows for precise monitoring and tuning of breeding efforts, a critical factor in continuously improving [...] Read more.

With its controlled environment, protected cultivation is advantageous and effective for breeding programs. This distinct setting also guarantees that fresh vegetables meet high quality standards. The controlled environment allows for precise monitoring and tuning of breeding efforts, a critical factor in continuously improving the quality of fresh vegetable production. Classical breeding strategies include hybridization, pedigree selection, backcrossing, recombination, and marker-assisted breeding. However, advanced techniques like phenomics and genome editing are revolutionizing the field. These methods accelerate phenotyping and aid in identifying traits and genetic variants linked to quality characteristics. Modern biotechnological tools, specifically genetic engineering and gene editing methods like CRISPR/Cas, have enhanced a wide array of traits in numerous vegetable species. These technological advancements have the potential to effectively address challenges associated with stress resistance, product quality, and shelf-life, thereby presenting promising prospects for the advancement of agriculture. The protracted process of developing new vegetable cultivars with reduced physiological issues through contemporary techniques is an enduring endeavor. Full article

(This article belongs to the Special Issue Conventional vs. Modern Techniques in Horticultural Crop Breeding)

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19 pages, 3051 KB

Open AccessEditor’s ChoiceArticle

Non-Thermal Plasma-Activated Water Enhances Nursery Production of Vegetables: A Species-Specific Study

by Silvia Locatelli, Stefano Triolone, Marina De Bonis, Giampaolo Zanin and Carlo Nicoletto

Agronomy 2025, 15(1), 209; https://doi.org/10.3390/agronomy15010209 - 16 Jan 2025

Cited by 6 | Viewed by 1879

Abstract

Non-thermal plasma technology (NTP) has found widespread applications across several fields, including agriculture. Researchers have explored the use of NTP to improve plant growth and increase agricultural product quality using plasma-activated water (PAW). This technology has shown potential benefits in boosting seed germination, [...] Read more.

Non-thermal plasma technology (NTP) has found widespread applications across several fields, including agriculture. Researchers have explored the use of NTP to improve plant growth and increase agricultural product quality using plasma-activated water (PAW). This technology has shown potential benefits in boosting seed germination, promoting plant growth, as an effective defense against plant pathogens, and increasing systemic plant resistance. An experiment was set up over three different cultivation cycles to investigate the benefits of PAW administration on nursery production. Plasma-activated water was generated using two NTP intensities (PAW-HI = 600 mV; PAW-LI = 450 mV; CTR = tap water control) and manually applied to plants under greenhouse conditions. The species considered in the current study were tomato (Solanum lycopersicum L.), Swiss chard (Beta vulgaris L.), cabbage (Brassica oleracea L.), basil (Ocimum basilicum L.), and lettuce (Lactuca sativa L. var. Longifolia). The following morphological traits were measured at the end of each cycle and for each species: plant height (PH, cm), collar diameter (CD, mm), biomass (g), nutritional status (SPAD index), dry matter (DM, %), and chemical composition. The sturdiness index (SI) was determined by the PH-to-CD ratio. Results indicated a species-specific response to both PAW treatments compared to CTR. The plant height significantly increased in tomato (+11.9%) and cabbage (+5%) under PAW-HI treatment. In contrast, PAW-HI treatment negatively affected the PH in lettuce and basil (−18% and −9%, respectively). Swiss chard showed no significant response to either PAW-LI or PAW-HI treatments. Regarding DM, no significant differences were observed between the PAW treatments and CTR. However, an increase in total N content was detected in plant tissues across all species, except for basil, where no change was observed. The results suggest that PAW treatment has the potential to enhance vegetable nursery production, with species-specific responses observed in crops. Full article

(This article belongs to the Special Issue High-Voltage Plasma Applications in Agriculture)

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14 pages, 6231 KB

Open AccessEditor’s ChoiceArticle

Establishment of a Breeding Approach Combined with Gamma Ray Irradiation and Tissue Regeneration for Highbush Blueberry

by Xuan Yu, Haidi Yuan, Yihong Jin, Chuizheng Xia, Jiani Zhu, Jiali Che, Jiao Yang, Xiaofei Wang, Bingsong Zheng, Shufang Yang, Cristian Silvestri, Fuqiang Cui and Jianfang Zuo

Agronomy 2025, 15(1), 217; https://doi.org/10.3390/agronomy15010217 - 16 Jan 2025

Cited by 3 | Viewed by 1105

Abstract

Blueberries are a relatively recently domesticated species, primarily bred through hybridization. Mutation breeding, which uses chemical or physical treatment to increase plant mutation, has not yet been applied to blueberries. This study introduces a mutation breeding strategy for the highbush blueberry cultivar Vaccinium [...] Read more.

Blueberries are a relatively recently domesticated species, primarily bred through hybridization. Mutation breeding, which uses chemical or physical treatment to increase plant mutation, has not yet been applied to blueberries. This study introduces a mutation breeding strategy for the highbush blueberry cultivar Vaccinium corymbosum. We established a high-efficiency regeneration protocol, which was applied to leaves and stems exposed to gamma irradiation using ⁶⁰Co-γ rays at doses of 10, 20, 40, 80, and 120 gray (Gy), to increase the efficiency of mutated cells to develop into adventitious shoots. We determined that the median lethal dose (LD₅₀) was approximately 56 Gy for leaf explants and 80 Gy for stem explants. Phenotypic variations, including changes in leaf color and growth characteristics, which may be due to altered plant response to environmental factors, were successfully observed in the first-generation (M1) plants. The height of M1 plants quantitatively decreased with increasing irradiation doses. To evaluate the mutants induced by each irradiation dose, whole-genome resequencing was conducted on individuals from each dose group, revealing significant genomic alterations at the 80 Gy dose. This approach provides a valuable reference for future blueberry breeding programs aimed at enhancing genetic diversity and improving cultivar performance. Full article

(This article belongs to the Special Issue Advancing Fruit Tree Breeding: Exploring Cutting-Edge Techniques in Genome Editing, Genetic Transformation, and In Vitro Culture)

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19 pages, 2320 KB

Open AccessEditor’s ChoiceArticle

Organic Fertilization Leads to N Limitation Rather than P Limitation in Both Vegetable Soils

by Qingshan Li, Mengqian Xu, Lingying Xu, Xingwang Wu, Yuqin Zhang, Jia Xin, Yazhen Shen and Jichao Gao

Agronomy 2025, 15(1), 190; https://doi.org/10.3390/agronomy15010190 - 15 Jan 2025

Cited by 2 | Viewed by 1216

Abstract

Organic amendments are widely used to enhance soil fertility and nutrient cycling in greenhouse cultivation, but their effectiveness can vary depending on their origin and composition. This study investigated the impact of four organic materials (rice husk, coconut coir, biochar, and sheep manure) [...] Read more.

Organic amendments are widely used to enhance soil fertility and nutrient cycling in greenhouse cultivation, but their effectiveness can vary depending on their origin and composition. This study investigated the impact of four organic materials (rice husk, coconut coir, biochar, and sheep manure) on nutrient cycling and enzyme activities in two of greenhouse tomato soils. The distribution of soil nutrients and enzyme activities was analyzed under controlled conditions during a pot experiment. The addition of organic amendments, regardless of their source, significantly altered the microbial resource allocation, reducing the carbon limitation while increasing the nitrogen demand. The effect on soil nutrient pools was largely determined by the chemical composition of the amendments. In clayey soils, biochar and rice husk additions most effectively promoted enzyme activities related to carbon, nitrogen, and phosphorus acquisition. Under sandy soil conditions, sheep manure increased carbon and phosphorus acquisition enzymes, while biochar most effectively enhanced nitrogen acquisition enzymes. Biochar emerged as a particularly effective amendment, enhancing organic carbon sequestration across different soil types. The chemical composition of the amendments, specifically, the content of carboxyl C, aromatic C, and O-alkyl C, played a crucial role in influencing soil nutrient limitations. In clayey soils, the mean C:N:P ratios for CK, T1, T2, T3, and T4 treatments were 1:1.375:0.625, 1:1.244:0.662, 1:0.839:0.610, 1:1.161:0.689, and 1:1.038:0.549, respectively. In sandy soils, the ratios were 1:1.117:0.698, 1:1.18:0.75, 1:1.096:0.731, 1:1.217:0.689, and 1:1.06:0.669, respectively. These findings suggest that the addition of organic amendments can improve nutrient retention and enzyme activities, but their effects on soil nutrient pools are influenced by both the composition of the amendments and the soil texture. This research enhances our understanding of organic amendments and soil nutrient transformations, and aids in optimizing the application of organic materials for improved soil management in greenhouse cultivation. Full article

(This article belongs to the Special Issue Soil Evolution, Management, and Sustainable Utilization)

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20 pages, 7523 KB

Open AccessEditor’s ChoiceArticle

SMC-YOLO: A High-Precision Maize Insect Pest-Detection Method

by Qinghao Wang, Yongkang Liu, Qi Zheng, Rui Tao and Yong Liu

Agronomy 2025, 15(1), 195; https://doi.org/10.3390/agronomy15010195 - 15 Jan 2025

Cited by 6 | Viewed by 2217

Abstract

Maize is an excellent crop with high yields and versatility, and the extent and frequency of pest outbreaks will have a serious impact on maize yields. Therefore, helping growers accurately identify pest species is important for improving corn yields. Thus, in this study, [...] Read more.

Maize is an excellent crop with high yields and versatility, and the extent and frequency of pest outbreaks will have a serious impact on maize yields. Therefore, helping growers accurately identify pest species is important for improving corn yields. Thus, in this study, we propose to use a pest detector called SMC-YOLO, which is proposed using You Only Look Once (YOLO) v8 as a reference model. First, the Spatial Pyramid Convolutional Pooling Module (SPCPM) is utilized in lieu of the Spatial Pyramid Pooling-Fast (SPPF) to enrich the diversity of feature information. Subsequently, a Multi-Dimensional Feature-Enhancement Module (MDFEM) is incorporated into the neck network. This module serves the purpose of augmenting the feature information associated with pests. Finally, a cross-scale feature-level non-local module (CSFLNLM) is incorporated in front of the detector head, which improves the global perception of the detector head. The results showed that SMC-YOLO achieved excellent results in several metrics, with its F1 Score (F1), mean Average Precision (mAP) @0.50, mAP@0.50:0.95 and mAP@0.75 reaching 83.18%, 86.7%, 60.6% and 70%, respectively, outperforming YOLOv11. This study provides a more reliable method of pest identification for the development of smart agriculture. Full article

(This article belongs to the Section Pest and Disease Management)

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15 pages, 3723 KB

Open AccessEditor’s ChoiceReview

The Renaissance of Polyamines: New Roles in Crop Yield and Quality Properties in Freshly Fruit

by Jenifer Puente-Moreno, Fernando Garrido-Auñón, María E. García-Pastor, Daniel Valero and María Serrano

Agronomy 2025, 15(1), 201; https://doi.org/10.3390/agronomy15010201 - 15 Jan 2025

Cited by 1 | Viewed by 1771

Abstract

Polyamines (PAs) are low-molecular-weight compounds that contain amino groups. PAs are present in a variety of organisms, including plants, animals and microorganisms. In plants, the main PAs are putrescine (PUT), spermidine (SPD) and spermine (SPM). They play crucial physiological roles in plant development, [...] Read more.

Polyamines (PAs) are low-molecular-weight compounds that contain amino groups. PAs are present in a variety of organisms, including plants, animals and microorganisms. In plants, the main PAs are putrescine (PUT), spermidine (SPD) and spermine (SPM). They play crucial physiological roles in plant development, including flowering, fruit set, growth, ripening and metabolic processes. In addition, PAs are components of the diet and have a role in health and disease. Furthermore, PAs have been demonstrated to help overcome the negative effects of adverse environmental factors of both biotic and abiotic stresses. Thus, the main objective of this review was to examine the recent literature regarding the mentioned effects of PAs apart from the impact of preharvest PAs treatments, applied at different stages of fruit development, on fresh fruit crop yield and fruit quality properties at harvest, and in their maintenance during storage, with a special emphasis on the fruit content in bioactive compounds with antioxidant activity. Moreover, this review addressed the impact of PAs on other physiological processes affecting crop yield such as flowering and fruit set. Full article

(This article belongs to the Special Issue Adaptation of Crops to the Environment under Climate Change: Physiological and Agronomic Strategies—3rd Edition)

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26 pages, 2182 KB

Open AccessEditor’s ChoiceArticle

The Role of Organic Farming in Reducing Greenhouse Gas Emissions from Agriculture in the European Union

by Claudiu George Bocean

Agronomy 2025, 15(1), 198; https://doi.org/10.3390/agronomy15010198 - 15 Jan 2025

Cited by 5 | Viewed by 3200

Abstract

Agriculture remains a key source of greenhouse gas (GHG) emissions within the European Union, posing substantial obstacles to achieving climate objectives and fostering sustainable development. On this background, organic farming stands out as a viable alternative, offering significant potential for reducing emissions. This [...] Read more.

Agriculture remains a key source of greenhouse gas (GHG) emissions within the European Union, posing substantial obstacles to achieving climate objectives and fostering sustainable development. On this background, organic farming stands out as a viable alternative, offering significant potential for reducing emissions. This study explores the impact of expanding organic farming on GHG emissions in the EU agricultural sector. The empirical research examines the connection between organic farming practices and GHG emission levels using structural equation modeling, complemented by Holt and ARIMA forecasting models, to project future trends based on expected growth in organic farmland. The findings highlight a robust negative influence (p < 0.001), demonstrating that organic farming practices are associated with tangible reductions in emissions. Forecasting analyses further reinforce this, predicting considerable declines in GHG emissions (by almost 14 percent below the level of 2008) as organic farming continues to expand for over 23% of agricultural land by 2035, according to the projections in this research. These insights underscore the critical role of organic farming in advancing the EU’s climate ambitions. The study concludes that broader adoption of organic practices offers a practical and impactful pathway for building a more sustainable agricultural system while mitigating environmental harm across member states. Full article

(This article belongs to the Special Issue Approaches to Promote Wider Emergence of Sustainable Agricultural Production—2nd Edition)

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25 pages, 5457 KB

Open AccessEditor’s ChoiceArticle

Research on Small-Target Detection of Flax Pests and Diseases in Natural Environment by Integrating Similarity-Aware Activation Module and Bidirectional Feature Pyramid Network Module Features

by Manxi Zhong, Yue Li and Yuhong Gao

Agronomy 2025, 15(1), 187; https://doi.org/10.3390/agronomy15010187 - 14 Jan 2025

Cited by 3 | Viewed by 1013

Abstract

In the detection of the pests and diseases of flax, early wilt disease is elusive, yellow leaf disease symptoms are easily confusing, and pest detection is hampered by issues such as diversity in species, difficulty in detection, and technological bottlenecks, posing significant challenges [...] Read more.

In the detection of the pests and diseases of flax, early wilt disease is elusive, yellow leaf disease symptoms are easily confusing, and pest detection is hampered by issues such as diversity in species, difficulty in detection, and technological bottlenecks, posing significant challenges to detection efforts. To address these issues, this paper proposes a flax pest and disease detection method based on an improved YOLOv8n model. To enhance the detection accuracy and generalization capability of the model, this paper first employs the Albumentations library for data augmentation, which strengthens the model’s adaptability to complex environments by enriching the diversity of training samples. Secondly, in terms of model architecture, a Bidirectional Feature Pyramid Network (BiFPN) module is introduced to replace the original feature extraction network. Through bidirectional multi-scale feature fusion, the model’s ability to distinguish pests and diseases with similar features and large scale differences is effectively improved. Meanwhile, the integration of the SimAM attention mechanism enables the model to learn information from three-dimensional channels, enhancing its perception of pest and disease features. Additionally, this paper adopts the EIOU loss function to further optimize the model’s bounding box regression, reducing the distortion of bounding boxes caused by high sample variability. The experimental results demonstrate that the improved model achieves a significant detection performance on the flax pest and disease dataset, with notable improvements in the detection accuracy and mean average precision compared to the original YOLOv8n model. Finally, this paper proposes a YOLOv8n model with a four-headed detection design, which significantly enhances the detection capability for small targets such as pests and diseases with a size of 4 × 4 pixels or larger by introducing new detection heads and optimizing feature extraction. This method not only improves the detection accuracy for flax pests and diseases but also maintains a high computational efficiency, providing effective technical support for the rapid and precise detection of flax pests and diseases and possessing an important practical application value. Full article

(This article belongs to the Section Pest and Disease Management)

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19 pages, 5165 KB

Open AccessEditor’s ChoiceArticle

Non-Destructive Detection of Silage pH Based on Colorimetric Sensor Array Using Extended Color Components and Novel Sensitive Dye Screening Method

by Kai Zhao, Haiqing Tian, Jue Zhang, Yang Yu, Lina Guo, Jianying Sun and Haijun Li

Agronomy 2025, 15(1), 184; https://doi.org/10.3390/agronomy15010184 - 14 Jan 2025

Cited by 2 | Viewed by 985

Abstract

Non-destructive detection of maize silage quality is essential. The aim is to propose a fast and non-destructive silage pH detection method based on a colorimetric sensor array (CSA). Extended color components, a novel sensitive dye screening method, and a feature screening method were [...] Read more.

Non-destructive detection of maize silage quality is essential. The aim is to propose a fast and non-destructive silage pH detection method based on a colorimetric sensor array (CSA). Extended color components, a novel sensitive dye screening method, and a feature screening method were integrated and applied to enhance pH detection. Fifty color components were constructed from five color spaces and used to extract information about the response of CSA to silage. Forward and backward stepwise selection and support vector regression (SVR) were combined to create a sensitive dye screening method, which was used to determine the optimal sensitive dye. The variable combination population analysis–iteratively retains informative variables algorithm was iterated to optimize effective features. Consequently, six hundred variables were extracted from the twelve dyes, which were able to comprehensively and finely characterize the CSA response. Four sensitive dyes were screened out from the twelve dyes, which were sensitive to silage volatile compounds and accurately reflected the odor changes. Twenty-eight effective features were preferred, based on which the SVR model had

R_{p}^{2}

, RMSEP and RPD scores of 0.9533, 0.4186, and 4.4186, respectively; the pH prediction performance was substantially improved. This study provides technical support for the scientific evaluation of silage quality. Full article

(This article belongs to the Section Precision and Digital Agriculture)

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19 pages, 12769 KB

Open AccessEditor’s ChoiceArticle

YOLOv8n-CA: Improved YOLOv8n Model for Tomato Fruit Recognition at Different Stages of Ripeness

by Xin Gao, Jieyuan Ding, Ruihong Zhang and Xiaobo Xi

Agronomy 2025, 15(1), 188; https://doi.org/10.3390/agronomy15010188 - 14 Jan 2025

Cited by 6 | Viewed by 1366

Abstract

This study addresses the challenges of tomato maturity recognition in natural environments, such as occlusion caused by branches and leaves, and the difficulty in detecting stacked fruits. To overcome these issues, we propose a novel YOLOv8n-CA method for tomato maturity recognition, which defines [...] Read more.

This study addresses the challenges of tomato maturity recognition in natural environments, such as occlusion caused by branches and leaves, and the difficulty in detecting stacked fruits. To overcome these issues, we propose a novel YOLOv8n-CA method for tomato maturity recognition, which defines four maturity stages: unripe, turning color, turning ripe, and fully ripe. The model is based on the YOLOv8n architecture, incorporating the coordinate attention (CA) mechanism into the backbone network to enhance the model’s ability to capture and express features of the tomato fruits. Additionally, the C2f-FN structure was utilized in both the backbone and neck networks to strengthen the model’s capacity to extract maturity-related features. The CARAFE up-sampling operator was integrated to expand the receptive field for improved feature fusion. Finally, the SIoU loss function was used to solve the problem of insufficient CIoU of the original loss function. Experimental results showed that the YOLOv8n-CA model had a parameter count of only 2.45 × 10⁶, computational complexity of 6.9 GFLOPs, and a weight file size of just 4.90 MB. The model achieved a mean average precision (mAP) of 97.3%. Compared to the YOLOv8n model, it reduced the model size slightly while improving accuracy by 1.3 percentage points. When compared to seven other models—Faster R-CNN, YOLOv3s, YOLOv5s, YOLOv5m, YOLOv7, YOLOv8n, YOLOv10s, and YOLOv11n—the YOLOv8n-CA model was the smallest in size and demonstrated superior detection performance. Full article

(This article belongs to the Section Precision and Digital Agriculture)

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17 pages, 2007 KB

Open AccessEditor’s ChoiceReview

Enhancing Maize Production Through Timely Nutrient Supply: The Role of Foliar Fertiliser Application

by Brian Ssemugenze, Akasairi Ocwa, Ronald Kuunya, Costa Gumisiriya, Csaba Bojtor, János Nagy, Adrienn Széles and Árpád Illés

Agronomy 2025, 15(1), 176; https://doi.org/10.3390/agronomy15010176 - 13 Jan 2025

Cited by 5 | Viewed by 3917

Abstract

Maize, regarded as a staple economic crop, attracts special global attention with the aim to enhance its production. Foliar fertilisation offers a complementary method to traditional soil fertilisation amongst resource-limited agricultural systems, providing a more efficient solution to nutrient deficiencies, especially in suboptimal [...] Read more.

Maize, regarded as a staple economic crop, attracts special global attention with the aim to enhance its production. Foliar fertilisation offers a complementary method to traditional soil fertilisation amongst resource-limited agricultural systems, providing a more efficient solution to nutrient deficiencies, especially in suboptimal soil conditions. This study aimed to analyse foliar fertiliser formulation research directions and their application in maize production. A literature search was conducted in the Web of Science (WoS) database. Bibliometric analyses were performed using the VOSviewer software (version 1.6.17). The changes in the publication trends of documents were tested using the Mann–Kendall test. The production effects of foliar fertilisation were independently synthesised. The results showed a strong positive increase in publication trends regarding maize foliar fertilisation (R² = 0.7842). The predominant nutrients that affected maize production were nitrogen, phosphorous, potassium, zinc, iron, and manganese. The timely foliar application of nutrients corrected deficiencies and/or sustained nutrient supply under several abiotic stresses. Foliar application at critical growth stages like flowering and grain filling boosted carbohydrate and protein content, lipid levels, kernel size, mineral content, and the weight of the maize grain. This review identified important research gaps, namely genotype-specific responses, interactions with other agronomic practices, and long-term environmental effects. Full article

(This article belongs to the Special Issue Foliar Fertilization: Novel Approaches and Field Practices)

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21 pages, 298 KB

Open AccessEditor’s ChoiceArticle

Can the Adoption of Green Pest Control Technologies Reduce Pesticide Use? Evidence from China

by Haochen Jiang and Yubin Wang

Agronomy 2025, 15(1), 178; https://doi.org/10.3390/agronomy15010178 - 13 Jan 2025

Cited by 4 | Viewed by 1473

Abstract

The widespread use of pesticides has long been a cornerstone of modern agriculture, but their overuse has led to several challenges, including increased production costs, food safety risks, and environmental damage. Green pest control technologies (GPCTs) have emerged as a promising alternative to [...] Read more.

The widespread use of pesticides has long been a cornerstone of modern agriculture, but their overuse has led to several challenges, including increased production costs, food safety risks, and environmental damage. Green pest control technologies (GPCTs) have emerged as a promising alternative to traditional chemical methods, although their widespread adoption is still in progress, and their environmental and economic impacts require further examination. This study aims to evaluate the adoption of GPCT in apple orchards by employing a rigorous framework to measure pesticide intensity per unit, assess the impact of GPCT on pesticide reduction, and analyze the associated environmental effects in large-scale apple farming systems in China. Based on survey data collected from apple farmers across key production regions in China, we apply an Endogenous Treatment Effect Regression (ETR) model to evaluate the effects of these technologies on pesticide usage and concentration. This model allows for more accurate estimates of the treatment effects by addressing selection bias and accounting for both observable and unobservable factors. Our results show that the adoption of GPCT leads to a significant reduction in pesticide use intensity. Notably, the reductions are more pronounced among specific groups of farmers, particularly those who are less risk-averse and those with larger or more fragmented landholdings. These findings underscore the dual ecological and economic benefits of GPCT, providing strong support for policy initiatives that promote sustainable agricultural practices and encourage land consolidation. Full article

(This article belongs to the Topic High-Efficiency Utilization of Water-Fertilizer Resources and Green Production of Crops)

15 pages, 2795 KB

Open AccessEditor’s ChoiceArticle

Compensation Mechanisms for Early Maturity and High Yield in Tartary Buckwheat (Fagopyrum tataricum): A Study on ‘Source–Sink’ Relationship and Phosphorus Utilization

by Xuling Chen, Li Yang, Chunxia Zhao, Shunjiang Zhao, Ziye Meng, Xiaona Zhang, Qijiao Chen, Kesu Wei, Dabing Xiang, Yan Wan, Yu Fan, Yan Wang and Chenggang Liang

Agronomy 2025, 15(1), 173; https://doi.org/10.3390/agronomy15010173 - 12 Jan 2025

Cited by 2 | Viewed by 1183

Abstract

The regulatory mechanisms underlying the ‘source–sink’ relationship in Tartary buckwheat remain largely unexplored. This study selected an early-maturing, high-yield variety, ‘Zhukuzao1’ (ZKZ1), to delve into the ‘source–sink’ relationship and the regulatory mechanisms of phosphorus utilization. Compared with Jinqiao2 (JQ2), ZKZ1 matured approximately 10 [...] Read more.

The regulatory mechanisms underlying the ‘source–sink’ relationship in Tartary buckwheat remain largely unexplored. This study selected an early-maturing, high-yield variety, ‘Zhukuzao1’ (ZKZ1), to delve into the ‘source–sink’ relationship and the regulatory mechanisms of phosphorus utilization. Compared with Jinqiao2 (JQ2), ZKZ1 matured approximately 10 days earlier, with significantly reduced chlorophyll content, net photosynthetic rate, and down-regulated PSI-III and GBSSI, indicating a reduced ‘source’. However, ZKZ1 maintained soluble sugar levels in upper leaves and increased sugar transport to seeds, promoting plant growth and yield formation. Under varying phosphorus conditions, ZKZ1 exhibited significantly higher total phosphorus content in lower (3.9~4.5-fold) and upper (1.4~1.6-fold) leaves of seedlings, along with increased phosphorus transport to upper leaves and seeds, and up-regulated PHO1 (2.4~3.0-fold), SPX3 (1.8~2.8-fold), PAP2 (2.8~7.7-fold), and 5PTase2 (1.4~3.5-fold) in leaves, indicating improved phosphorus absorption, transport, and remobilization. At maturity, ZKZ1 achieved yields comparable to JQ2, with superior quality traits, including significantly increased contents of protein (glutenin, prolamin, and globulin) and flavonoids under normal phosphorus conditions. Notably, the efficient phosphorus-regulated sugar metabolism in ZKZ1 maintains yield via enhanced ‘flow’ despite photosynthesis decrease. This study highlights the potential of optimizing the ‘source–sink’ relationship and phosphorus utilization in early-maturing, high-yield Tartary buckwheat breeding. Full article

(This article belongs to the Special Issue Advanced Lighting Strategies for Controlling Crop Development and Quality)

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16 pages, 6834 KB

Open AccessEditor’s ChoiceArticle

Development of Genome-Wide Unique Indel Markers for a Heat-Sensitive Genotype in Wheat (Triticum aestivum L.)

by Huijie Zhai, Kunpeng Xu, Meng Wang, Zhenchuang Wang, Ziyang Cai, Ao Li, Anxin He, Xiaoming Xie, Lingling Chai, Mingjiu Liu, Xingqi Ou and Zhongfu Ni

Agronomy 2025, 15(1), 169; https://doi.org/10.3390/agronomy15010169 - 11 Jan 2025

Cited by 1 | Viewed by 1532

Abstract

A chromosome segment substituted line (CSSL) represents an ideal resource for studying quantitative traits like thermotolerance. To develop wheat inter-varietal CSSLs with E6015-3S (a heat-sensitive genotype) being the recipient parent, genome-wide unique DNA markers are urgently needed for marker-assisted selection. In this study, [...] Read more.

A chromosome segment substituted line (CSSL) represents an ideal resource for studying quantitative traits like thermotolerance. To develop wheat inter-varietal CSSLs with E6015-3S (a heat-sensitive genotype) being the recipient parent, genome-wide unique DNA markers are urgently needed for marker-assisted selection. In this study, 11,016 primer pairs targeting 5036 indel sites were successfully designed for E6015-3S, with an average density of 0.36 indels per Mbp. These primer pairs are believed to be unique and polymorphic in the wheat genome; as gathered from the evidence, (i) 76.18 to 99.34% of the 11,016 primer pairs yielded a single hit during sequence alignment with 18 sequenced genomes, (ii) 83.59 to 90.98% of 1042 synthesized primer pairs amplified a single band in 16 wheat accessions, and (iii) 59.69 to 99.81% of the tested 1042 primer pairs were polymorphic between E6015-3S and 15 individual wheat accessions. These primer pairs are also anticipated with excellent resolvability on agarose or polyacrylamide gels, since most of them have indel sizes from 15 to 46 bp, amplicon sizes from 141 to 250 bp, and polymorphism ratios from 6.0 to 25.0%. Collectively, these primer pairs are ideal DNA markers for inter-varietal CSSL development and more broad applications, like germplasm classification, seed purity testing, genetic linkage mapping, and marker-assisted breeding in wheat, owing to their uniqueness, polymorphism, and easy-to-use characteristics. Full article

(This article belongs to the Collection Crop Breeding for Stress Tolerance)

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17 pages, 5952 KB

Open AccessEditor’s ChoiceArticle

Evaluation of Spray Drift from an Electric Boom Sprayer: Impact of Boom Height and Nozzle Type

by Xiaoyong Pan, Shuo Yang, Yuanyuan Gao, Zhichong Wang, Changyuan Zhai and Wei Qiu

Agronomy 2025, 15(1), 160; https://doi.org/10.3390/agronomy15010160 - 10 Jan 2025

Cited by 4 | Viewed by 1206

Abstract

In the Huang-Huai-Hai region of China, the instability of electric boom sprayers has prompted many farmers to raise the boom height to improve clearance. However, the drift risks associated with these conditions remain poorly assessed. This study investigated two key factors influencing drift: [...] Read more.

In the Huang-Huai-Hai region of China, the instability of electric boom sprayers has prompted many farmers to raise the boom height to improve clearance. However, the drift risks associated with these conditions remain poorly assessed. This study investigated two key factors influencing drift: boom height and nozzle type. The standard LI CHENG VP11003 nozzle was compared to the Teejet XR11003 nozzle, and droplet size and velocity were measured at various boom heights. The results showed that, at the same boom height, the LI CHENG nozzle produced droplets with an average D[V, 0.5] 14.6 µm larger (8.13%), an average velocity 0.53 m/s lower (29.26%), and a relative span (RS) value 0.05 higher (4.52%) compared to the Teejet nozzle. Drift tests were performed under field conditions using a spray drift test bench. The results showed that the total drift amount per unit area (TDA) for the LI CHENG nozzle showed minimal variation at boom heights of 0.4–0.6 m (Stage 1), 0.7–0.9 m (Stage 2), and 1.0–1.2 m (Stage 3). The drift potential of the LI CHENG VP11003 nozzle increased by 136.62% in Stage 2 and 282.69% in Stage 3, relative to Stage 1. Similarly, the Teejet XR11003 nozzle showed increases of 30.52% and 165.51% in Stages 2 and 3, respectively. The results showed that the LICHENG nozzle, which is the standard equipment on the sprayer, can only be used to moderately increase the boom height to improve the sprayer’s clearance within the range of the first stage. When the boom height exceeds this range, the drift risk becomes too high. This study provides meaningful insights into enhancing drift control and developing application strategies for growers. Full article

(This article belongs to the Special Issue Novel Studies in High-Performance and Precision Plant Protection Products Application—2nd Edition)

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18 pages, 1655 KB

Open AccessEditor’s ChoiceArticle

Effects of Sewage Sludge Compost on Carbon, Nitrogen, Phosphorus, and Sulfur Ratios and Soil Enzyme Activities in a Long-Term Experiment

by Csilla Almási, Viktória Orosz, Timea Tóth, Mostafa M. Mansour, Ibolya Demeter, István Henzsel, Zsolt Bogdányi, Tamás András Szegi and Marianna Makádi

Agronomy 2025, 15(1), 143; https://doi.org/10.3390/agronomy15010143 - 9 Jan 2025

Cited by 4 | Viewed by 1622

Abstract

The carbon, nitrogen, phosphorus, and sulfur (CNPS) ratios of soils are known to be relatively stable parameters, characterizing different land uses. We hypothesized that the long-term application of sewage sludge compost (SSC) would not change these ratios but would increase the concentration of [...] Read more.

The carbon, nitrogen, phosphorus, and sulfur (CNPS) ratios of soils are known to be relatively stable parameters, characterizing different land uses. We hypothesized that the long-term application of sewage sludge compost (SSC) would not change these ratios but would increase the concentration of these elements and change the quality of organic matter (OM), as well as soil enzyme activities. Hence, soil chemical and microbiological properties were studied in a 20-year long-term experiment. The plots were grouped into five blocks and treated every third year with SSC at the rates of 0, 9, 18, or 27 t ha⁻¹. Three plants, in a crop rotation, were tested and sown every year as follows: rye, rye with hairy vetch, and maize. The results showed that basic soil parameters (pH, OM content, E4/E6 ratio, NO₃-NO₂-N, AL-P₂O₅, and soil moisture content) were increased, along with the SSC doses in soil for the rye. Similar trends were found in CNPS concentrations, β-glucosidase, and alkaline phosphatase activities, while the acidic phosphatase activity was reduced. The C:N, C:S, and N:S ratios were not affected by the compost application. The main factors of treatment effects were plant-available phosphorus (ammonium lactate (AL)-soluble P₂O₅), total P, and NO₃-NO₂-N, based on principal component analysis. The canonical correspondent analyses revealed that phosphatase activities were affected by C:N, C:P, and N:P ratios and β-glucosidase was correlated with P forms and the E4/E6 ratio, while the soil pH strongly affected all soil enzymes. Based on the alkaline and acidic phosphatase activities, the role of microbes became more important with increasing compost doses in phosphorus mobilization. We conclude that the addition of SSC could improve soil health through increasing the pH, OM, nutrient content, and microbial activity. Also, some elemental ratios have an important role in the regulation of soil enzyme activities. Full article

(This article belongs to the Section Agricultural Biosystem and Biological Engineering)

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28 pages, 2426 KB

Open AccessEditor’s ChoiceArticle

Comparative Evaluation of Salt Tolerance in Four Self-Rooted Hazelnut (Corylus avellana L. and Corylus americana Walter) Cultivars

by Xavier Rius-Garcia, María Videgain-Marco, José Casanova-Gascón, Luis Acuña-Rello and Pablo Martín-Ramos

Agronomy 2025, 15(1), 148; https://doi.org/10.3390/agronomy15010148 - 9 Jan 2025

Cited by 2 | Viewed by 2753

Abstract

Rising soil salinity poses a significant challenge to hazelnut cultivation, particularly in Mediterranean regions, where the increasing use of low-quality irrigation water necessitates the identification of salt-tolerant cultivars for sustainable production. This study investigated the salt tolerance mechanisms in four hazelnut cultivars (Barcelona, [...] Read more.

Rising soil salinity poses a significant challenge to hazelnut cultivation, particularly in Mediterranean regions, where the increasing use of low-quality irrigation water necessitates the identification of salt-tolerant cultivars for sustainable production. This study investigated the salt tolerance mechanisms in four hazelnut cultivars (Barcelona, Tonda di Giffoni, Tonda Gentile Romana, and Yamhill) exposed to varying NaCl concentrations (0, 25, 50, and 75 mM) over five months. This research assessed their morphological, physiological, and biochemical responses through an analysis of their growth parameters, photosynthetic efficiency, visual symptoms, and ion content. The results revealed significant genotypic variation in their salt tolerance mechanisms. Tonda di Giffoni demonstrated superior salt tolerance, maintaining a higher photosynthetic efficiency and better ion balance, particularly in K⁺/Na⁺ and Ca²⁺/Na⁺ ratios. Barcelona showed moderate tolerance at lower salinity levels but declined sharply under higher stress. Yamhill exhibited a strong survival capacity despite its poor photosynthetic performance, while Tonda Gentile Romana proved most sensitive to salinity stress. All the cultivars showed a significant biomass reduction, with their fresh and dry weights decreasing by over 80% at 75 mM NaCl. Leaf chloride concentrations dramatically increased, reaching levels 481% higher than those in the control conditions. This study identifies Tonda di Giffoni as the most suitable cultivar for moderately saline conditions and provides insights into hazelnut salt tolerance mechanisms, contributing valuable information for breeding programs and cultivation strategies in salt-affected regions. Full article

(This article belongs to the Special Issue Crop and Vegetable Physiology Under Environmental Stresses—2nd Edition)

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17 pages, 4569 KB

Open AccessEditor’s ChoiceArticle

Sustainable Fertilization of Organic Sweet Cherry to Improve Physiology, Quality, Yield, and Soil Properties

by Liliana Gaeta, Luigi Tarricone, Alessandro Persiani, Angelo Fiore, Francesco Montemurro, Daniela De Benedetto, Carolina Vitti, Pasquale Campi and Mariangela Diacono

Agronomy 2025, 15(1), 135; https://doi.org/10.3390/agronomy15010135 - 8 Jan 2025

Cited by 2 | Viewed by 2375

Abstract

Sustainable fertilization techniques are essential in Mediterranean farming systems, where the depletion of organic matter, influencing soil water and nutrient availability, is becoming an increasing concern. In this context, organic fertilizers offer an effective strategy to restore soil fertility while reducing environmental impacts. [...] Read more.

Sustainable fertilization techniques are essential in Mediterranean farming systems, where the depletion of organic matter, influencing soil water and nutrient availability, is becoming an increasing concern. In this context, organic fertilizers offer an effective strategy to restore soil fertility while reducing environmental impacts. This research aimed to evaluate the effects of different organic fertilizers on soil quality and tree performance in a sweet cherry (Prunus avium L.) orchard. This study was conducted in two growing seasons (2021–2022) in an organic orchard in Southern Italy, comparing four treatments: (i) compost, (ii) compost combined with compost tea, (iii) mixed manure, and (iv) an unfertilized control. The results indicated that compost tea, applied both to the soil and as a foliar spray, significantly improved tree water status, particularly under water stress conditions, as reflected by more negative stem water potential values. Moreover, this treatment enhanced photosynthetic performance, yield, and fruit quality, achieving the highest ratio of soluble solids content/total acidity. The findings suggest that compost tea, in combination with compost, could be a sustainable and valuable fertilization option for Mediterranean organic tree orchards. However, further studies are necessary to understand the benefits of other fruit orchards as well as the long-term effects on soils. Full article

(This article belongs to the Section Soil and Plant Nutrition)

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14 pages, 2449 KB

Open AccessEditor’s ChoiceArticle

Effects of Grazing Intensity on Microbial Diversity at Different Soil Depths in Desert Steppe Soils

by Yuxin Wang, Xin Ju, Qian Wu and Guodong Han

Agronomy 2025, 15(1), 124; https://doi.org/10.3390/agronomy15010124 - 6 Jan 2025

Cited by 2 | Viewed by 1150

Abstract

This study examines the influence of grazing intensity on soil microbial communities in a desert steppe ecosystem. Soil samples were collected from three depths (0–10 cm, 10–20 cm, and 20–30 cm) under varying grazing intensities: control (CK), light (LG), moderate (MG), and heavy [...] Read more.

This study examines the influence of grazing intensity on soil microbial communities in a desert steppe ecosystem. Soil samples were collected from three depths (0–10 cm, 10–20 cm, and 20–30 cm) under varying grazing intensities: control (CK), light (LG), moderate (MG), and heavy grazing (HG). Key soil physicochemical properties and plant characteristics were analyzed alongside microbial diversity and community composition, which were assessed by identifying amplicon sequence variants and by conducting linear discriminant analysis effect size. The results showed that grazing intensity significantly impacted soil moisture, organic carbon, total nitrogen, and phosphorus levels, with a notable decrease in plant cover and microbial diversity under heavy grazing. CK and LG treatments supported higher microbial diversity, especially in surface layers, while heavy grazing was associated with a shift in community composition toward stress-tolerant taxa like Acidobacteriota and Blastocatella. Non-metric multidimensional scaling analysis revealed differences in microbial community structure between soil depths, with the effects of grazing diminishing with depth. These findings highlight the critical role of sustainable grazing practices in maintaining soil health and microbial diversity, with implications for the long-term resilience of desert steppe ecosystems. Full article

(This article belongs to the Special Issue Utilization and Management of Grassland Ecosystems)

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17 pages, 1474 KB

Open AccessEditor’s ChoiceArticle

Nitrogen, Phosphorus, and Potassium Requirements to Improve Portulaca oleracea L. Growth, Nutrient and Water Use Efficiency in Hydroponics

by Antonios Chrysargyris and Nikolaos Tzortzakis

Agronomy 2025, 15(1), 111; https://doi.org/10.3390/agronomy15010111 - 4 Jan 2025

Cited by 2 | Viewed by 1789

Abstract

Purslane (Portulaca oleracea L.) is an herbaceous species that is traditionally consumed across the world due to its nutraceutical quality, boasting anticancer, anti-inflammatory and antidiabetic properties. These traits render purslane an attractive wild edible species for research and commercial exploitation. The current [...] Read more.

Purslane (Portulaca oleracea L.) is an herbaceous species that is traditionally consumed across the world due to its nutraceutical quality, boasting anticancer, anti-inflammatory and antidiabetic properties. These traits render purslane an attractive wild edible species for research and commercial exploitation. The current study examined the effect of different nitrogen (N) concentrations (100–200 mg L⁻¹; as N100, N200) in combination with different levels (decreased 0.66-fold: dec, recommended 1-fold: rec, or increased 1.5-fold: inc) of phosphorus (P; 47–70–105 mg L⁻¹) and potassium (K; 250–350–525 mg L⁻¹) in the nutrient solution (NS) used in hydroponic nutrient film technique (NFT) cultivation. The N200_PKinc NS resulted in improved crop growth compared to N200_PKrec NS, suggesting a positive correlation between optimal N levels (i.e., 200 mg L⁻¹) and increased P and K levels (105 and 525 mg L⁻¹, respectively). Plants grown in N200_PKinc revealed decreased antioxidant activity (e.g., DPPH, FRAP, and ABTS), phenols and flavonoids, while simultaneously increased total soluble solids levels. The recommended levels of P and K mirrored low levels in lipid peroxidation, mainly due to the increase in catalase enzymatic activity. Higher nutrient use efficiency was observed when both N100_PKinc and N200_PKinc were applied, resulting in higher yield and enhanced plant growth, while N100_PKinc produced plants with increased antioxidant activity. These findings suggest that both (N200_PKinc and N100_PKinc) NS have potential benefits for the hydroponic cultivation of purslane, with the latter NS offering additional advantages in terms of higher produce quality. Full article

(This article belongs to the Special Issue Advanced Hydroponics Technology for Vegetable Production: New Opportunities and Challenges)

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26 pages, 16808 KB

Open AccessEditor’s ChoiceArticle

Design and Experimental Evaluation of a Smart Intra-Row Weed Control System for Open-Field Cabbage

by Shenyu Zheng, Xueguan Zhao, Hao Fu, Haoran Tan, Changyuan Zhai and Liping Chen

Agronomy 2025, 15(1), 112; https://doi.org/10.3390/agronomy15010112 - 4 Jan 2025

Cited by 9 | Viewed by 1668

Abstract

Addressing the challenges of complex structure, limited modularization capability, and insufficient responsiveness in traditional hydraulically driven inter-plant mechanical weeding equipment, this study designed and developed an electric swing-type opening and closing intra-row weeding control system. The system integrates deep learning technology for accurate [...] Read more.

Addressing the challenges of complex structure, limited modularization capability, and insufficient responsiveness in traditional hydraulically driven inter-plant mechanical weeding equipment, this study designed and developed an electric swing-type opening and closing intra-row weeding control system. The system integrates deep learning technology for accurate identification and localization of cabbage, enabling precise control and dynamic obstacle avoidance for the weeding knives. The system’s performance was comprehensively evaluated through laboratory and field experiments. Laboratory experiments demonstrated that, under conditions of low speed and large plant spacing, the system achieved a weeding accuracy of 96.67%, with a minimum crop injury rate of 0.83%. However, as the operational speed increased, the weeding accuracy decreased while the crop injury rate increased. Two-way ANOVA results indicated that operational speed significantly affected both weeding accuracy and crop injury rate, whereas plant spacing had a significant effect on weeding accuracy but no significant effect on crop injury rate. Field experiment results further confirmed that the system maintained high weeding accuracy and crop protection under varying speed conditions. At a low speed of 0.1 m/s, the weeding accuracy was 96.00%, with a crop injury rate of 1.57%. However, as the speed increased to 0.5 m/s, the weeding accuracy dropped to 81.79%, while the crop injury rate rose to 5.49%. These experimental results verified the system’s adaptability and reliability in complex field environments, providing technical support for the adoption of intelligent mechanical weeding systems. Future research will focus on optimizing control algorithms and feedback mechanisms to enhance the system’s dynamic response capability and adaptability, thereby advancing the development of sustainable agriculture and precision field management. Full article

(This article belongs to the Topic Challenges, Development and Frontiers of Smart Agriculture and Forestry—2nd Volume)

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17 pages, 6207 KB

Open AccessEditor’s ChoiceArticle

Genome-Wide Analysis of the PLATZ Gene Family in Oryza Genus: Evolution, Expression During Inflorescence Development and Stress Responses

by Hongwei Chen, Xiufang Ma, Guilan Lv, Zheng Wang, Lili Wang, Bowen Yan, Wenqi Shang, Xianju Wang, Zuobin Ma and Wenjing Zheng

Agronomy 2025, 15(1), 117; https://doi.org/10.3390/agronomy15010117 - 4 Jan 2025

Cited by 1 | Viewed by 1211

Abstract

The PLATZ gene family, known for its pivotal roles in regulating plant growth, development, and stress responses, is of great significance in rice biology and crop improvement efforts. In this study, we undertook a comprehensive identification and analysis of the PLATZ gene family [...] Read more.

The PLATZ gene family, known for its pivotal roles in regulating plant growth, development, and stress responses, is of great significance in rice biology and crop improvement efforts. In this study, we undertook a comprehensive identification and analysis of the PLATZ gene family across 10 Oryza genus species, including both cultivated and wild rice varieties. A total of 144 PLATZ genes were identified, demonstrating their widespread distribution. Phylogenetic analysis revealed six distinct groups among these genes, with high sequence similarity among members indicating a common evolutionary origin and potential functional conservation. Further analysis of conserved motifs, domains, and promoter regions provided insights into the transcriptional regulation and potential functions of PLATZ genes. Notably, expression profiling showed differential expression patterns of specific PLATZ genes, such as OsPLATZ7, OsPLATZ9, and OsPLATZ11, under various abiotic stress conditions and hormone treatments, highlighting their important roles in stress adaptation and hormone signaling. Additionally, the consistently high expression of OsPLATZ9 across multiple tissues suggests its involvement in multiple developmental processes. Overall, this study provides a detailed characterization of the PLATZ gene family in rice, laying the foundation for future functional studies and potential applications in agricultural biotechnology. Full article

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18 pages, 3164 KB

Open AccessEditor’s ChoiceArticle

Temperature Sensitivity Response of Soil Enzyme Activity to Simulated Climate Change at Growth Stages of Winter Wheat

by Yaokun Jiang, Bingbing Lu, Meng Liang, Yang Wu, Yuanze Li, Ziwen Zhao, Guobin Liu and Sha Xue

Agronomy 2025, 15(1), 106; https://doi.org/10.3390/agronomy15010106 - 3 Jan 2025

Cited by 3 | Viewed by 2413

Abstract

In recent years, research on farmland soil stability has gained attention due to climate change. Studying the thermal stability of soil enzymes at key crop growth stages in response to increased CO₂, drought, and warming is critical for evaluating climate change [...] Read more.

In recent years, research on farmland soil stability has gained attention due to climate change. Studying the thermal stability of soil enzymes at key crop growth stages in response to increased CO₂, drought, and warming is critical for evaluating climate change impacts on crop production and soil ecosystem stability. Despite its importance, research on the thermal stability of soil nutrient cycling enzymes remains limited. A pot experiment was conducted using the soil of winter wheat (Triticum aestivum L.), one of China’s main grain crops, as the research object. An artificial climate chamber was used to simulate four growth stages of winter wheat (jointing stage, flowering stage, grain filling stage, and maturity stage). Different levels of CO₂ concentration (400 and 800 μmol mol⁻¹), temperature conditions (current temperature and 4 °C higher), and water conditions (80% and 60% of field water capacity) were set, and their interactions were examined. By analyzing the temperature sensitivity (Q₁₀) of soil enzyme activities related to soil carbon (C), nitrogen (N), and phosphorous (P) cycles in response to different treatments, the results showed that doubling CO₂ concentration decreased soil C cycle enzyme Q₁₀ and increased soil N and P cycle enzyme Q₁₀ significantly. Additionally, soil C cycle enzyme Q₁₀ decreased with increasing temperature, while other enzymes showed inconsistent responses. Mild drought significantly decreased the soil N-cycling enzyme Q₁₀ in the early growth stage of winter wheat and the soil P-cycling enzyme Q₁₀ in each growth stage, but significantly increased the soil N-cycling enzyme Q₁₀ in the mature stage. The interaction between CO₂ concentration doubling and warming exhibited a single-factor superimposed effect in reducing soil C cycle enzyme Q₁₀. Moreover, doubling CO₂ concentration offset the effect of mild drought stress on soil P cycle enzyme Q₁₀. Above-ground biomass, soil total dissolved nitrogen, and nitrate nitrogen were identified as the primary factors influencing soil C, N, and P cycling enzyme Q₁₀. This study is of great significance in exploring the effects of global warming on food production and the mechanism of soil ecosystem functional stability under future climate change. Full article

(This article belongs to the Section Soil and Plant Nutrition)

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