Agronomy

39 pages, 2204 KB

Open AccessEditor’s ChoiceReview

Breeding Smarter: Artificial Intelligence and Machine Learning Tools in Modern Breeding—A Review

by Ana Luísa Garcia-Oliveira, Sangam L. Dwivedi, Subhash Chander, Charles Nelimor, Diaa Abd El Moneim and Rodomiro Octavio Ortiz

Agronomy 2026, 16(1), 137; https://doi.org/10.3390/agronomy16010137 - 5 Jan 2026

Viewed by 3180

Abstract

Climate challenges, along with a projected global population increase of 2 billion by 2080, are intensifying pressures on agricultural systems, leading to biodiversity loss, land use constrains, soil fertility declining, and changes in water cycles, while crop yields struggle to meet the rising [...] Read more.

Climate challenges, along with a projected global population increase of 2 billion by 2080, are intensifying pressures on agricultural systems, leading to biodiversity loss, land use constrains, soil fertility declining, and changes in water cycles, while crop yields struggle to meet the rising food demand. These challenges, coupled with evolving legislation and rapid technology advancements, require innovative sustainable agricultural solutions. By reshaping farmers’ daily operations, real-time data acquisition and predictive models can support informed decision-making. In this context, smart farming (SM) applied to plant breeding can improve efficiency by reducing inputs and increasing outputs through the adoption of digital and data-driven technologies. Examples include the investment on common ontologies and metadata standards for phenotypes and environments, standardization of HTP protocols, integration of prediction outputs into breeding databases, and selection workflows, as well in building multi-partner field networks that collect diverse envirotypes. This review outlines how AI and machine learning (ML) can be integrated in modern plant breeding methodologies, including genomic selection (GS) and genetic algorithms (GAs), to accelerate the development of climate-resilient and sustainably performing crop varieties. While many reviews address smart farming or smart breeding independently, herein, these domains are bridged to provide an understandable strategic landscape by enhancing breeding efficiency. Full article

(This article belongs to the Collection AI, Sensors and Robotics for Smart Agriculture)

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20 pages, 3699 KB

Open AccessEditor’s ChoiceArticle

Monitoring Rice Blast Disease Progression Through the Fusion of Time-Series Hyperspectral Imaging and Deep Learning

by Wenjuan Wang, Yufen Zhang, Haoyi Huang, Tao Liu, Minyue Zeng, Youqiang Fu, Hua Shu, Jianyuan Yang and Long Yu

Agronomy 2026, 16(1), 136; https://doi.org/10.3390/agronomy16010136 - 5 Jan 2026

Viewed by 764

Abstract

Rice blast, caused by Magnaporthe oryzae, is a devastating disease that jeopardizes global rice production and food security. Precision agriculture demands timely and accurate monitoring tools to enable targeted intervention. This study introduces a novel deep learning framework that fuses time-series hyperspectral [...] Read more.

Rice blast, caused by Magnaporthe oryzae, is a devastating disease that jeopardizes global rice production and food security. Precision agriculture demands timely and accurate monitoring tools to enable targeted intervention. This study introduces a novel deep learning framework that fuses time-series hyperspectral imaging with an advanced Autoformer model (AutoMSD) to dynamically track rice blast progression. The proposed AutoMSD model integrates multi-scale convolution and adaptive sequence decomposition, effectively decoding complex spatio-temporal patterns associated with disease development. When deployed on a 7-day hyperspectral dataset, AutoMSD achieved 86.67% prediction accuracy using only 3 days of historical data, surpassing conventional approaches. This accuracy at an early infection stage underscores the model’s strong potential for practical field deployment. Our work provides a scalable and robust decision-support tool that paves the way for site-specific disease management, reduced pesticide usage, and enhanced sustainability in rice cultivation systems. Full article

(This article belongs to the Topic Advances in Smart Agriculture with Remote Sensing as the Core and Its Applications in Crops Field)

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17 pages, 1843 KB

Open AccessArticle

Characterization of a Salt-Tolerant Plant Growth-Promoting Bacterial Isolate and Its Effects on Oat Seedlings Under Salt Stress

by Yincui Zhang, Changning Li and Yue Wang

Agronomy 2026, 16(1), 135; https://doi.org/10.3390/agronomy16010135 - 5 Jan 2026

Viewed by 590

Abstract

Oats (Avena sativa L.) are a staple grain and forage crop with substantial market demand. In China, they are the second most-imported forage grass, only after alfalfa (Medicago sativa L.). Enhancing the salt tolerance of oats to facilitate their cultivation in [...] Read more.

Oats (Avena sativa L.) are a staple grain and forage crop with substantial market demand. In China, they are the second most-imported forage grass, only after alfalfa (Medicago sativa L.). Enhancing the salt tolerance of oats to facilitate their cultivation in saline areas can thereby increase forage yield and promote the utilization of saline land, which constitutes an important reserve land resource in China. This study aimed to identify the bacterial strain Bacillus sp. LrM2 (hereafter referred to as strain LrM2) to determine its precise species-level classification and evaluate its effects on oat photosynthesis and growth under salt stress through indoor pot experiments. The results indicated that strain LrM2, capable of urease production and citrate utilization, was identified as Bacillus mojavensis. The strain LrM2 had a positive effect on shoot and root growth of oats under 100 mM NaCl stress conditions. Strain LrM2 inoculation modulated osmotic stress in oats under 100 mM NaCl stress by significantly increasing soluble sugar and decreasing proline content in leaves. It inhibited Na⁺ uptake and promoted K⁺ absorption in the roots, thereby reducing Na⁺ translocation to the leaves and mitigating ionic toxicity. Inoculation with strain LrM2 significantly increased photosynthetic pigment content (chlorophyll a, carotenoids), improved gas exchange parameters (stomatal conductance, transpiration rate, net rate of photosynthesis), enhanced PSII photochemical efficiency (maximum quantum yield, coefficient of photochemical quenching, actual photosynthetic efficiency of PSII, electron transfer rate), and reduced the quantum yield of non-regulated energy dissipation. These improvements, coupled with increased relative water content and instantaneous water use efficiency, thereby collectively enhanced the overall photosynthetic performance. In conclusion, strain LrM2 represents a promising bio-resource for mitigating salt stress and promoting growth in oats, with direct applications for developing novel biofertilizers and sustainable agricultural strategies. Full article

(This article belongs to the Special Issue Utilization of Microorganisms for Sustainable Agricultural Development)

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16 pages, 2200 KB

Open AccessArticle

Preliminary Study on Optimizing Rice Production in Cold Regions: Yield and Nutritional Trade-Offs Between Transplanting and Mechanical Hill-Drop Seeding

by Huaguo Ding, Songjin Zhou, Jiabao Han, Yingying Liu, Ziliang Cao, Lei Lei, Mingliang Bai, Yu Luo, Guang Yang, Lei Chen, Kai Liu, Wu-Rina Sun, Pinglian Sun and Chenshi Sun

Agronomy 2026, 16(1), 134; https://doi.org/10.3390/agronomy16010134 - 5 Jan 2026

Viewed by 553

Abstract

Direct seeding of rice reduces labor intensity and cost, helping alleviate labor shortages in cold-region rice production. To investigate the effects of mechanical precision hill-direct seeding versus mechanical transplanting on yield and nutrient accumulation in cold regions, a set of field split-plot experiments [...] Read more.

Direct seeding of rice reduces labor intensity and cost, helping alleviate labor shortages in cold-region rice production. To investigate the effects of mechanical precision hill-direct seeding versus mechanical transplanting on yield and nutrient accumulation in cold regions, a set of field split-plot experiments were conducted with cultivation method as the main plot and rice variety as the sub-plot. Our comprehensive measurement results indicate that transplanting significantly increased yield by enhancing tiller number, filled grains per panicle, and grain weight per hill, with significant varietal differences observed. No significant difference in 1000-grain weight was found between the two cultivation methods. Except for Zn content, different cultivation methods have no significant effect on other measured nutrients such as N, P, K, Fe, starch, and fat. Transplanting significantly increased effective tiller number (an increase of 2.6 tillers per hill) and filled grains per panicle (an increase of 12.4 grains), with a significant variety–cultivation method interaction. Qijing 2 (QJ2) and Tiandao 261 (TD261) were more suitable for transplanting to achieve high yield potential, whereas Longgeng 3038 (LG3038) and Tianxiangdao 9 (TXD9) obtained relatively high yields under direct seeding. Therefore, appropriate cultivation methods should be selected based on varietal characteristics: transplanting is recommended for high-yield-potential varieties, while simplified direct seeding is advised for varieties tolerant to direct seeding. Overall, this is a comprehensive consideration and rational strategy based on balancing rice yield, revenue, and benefit, as well as ensuring both food security and farmer income of the entire country and society. Full article

(This article belongs to the Special Issue Effects of Efficient Crop Cultivation Techniques on Plant Nutrition and Physiology)

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28 pages, 6915 KB

Open AccessArticle

YOLOv8n-DSP: A High-Precision Model for Oat Ear Detection and Counting in Complex Fields

by Jie Liu, Cong Tian and Yang Wu

Agronomy 2026, 16(1), 133; https://doi.org/10.3390/agronomy16010133 - 5 Jan 2026

Viewed by 368

Abstract

Accurate detection and counting of oat ears are essential for yield estimation but remain challenging in complex field environments due to occlusion, significant scale variation, and fluctuating lighting. The aim of this study is to develop a high-precision detection and counting model to [...] Read more.

Accurate detection and counting of oat ears are essential for yield estimation but remain challenging in complex field environments due to occlusion, significant scale variation, and fluctuating lighting. The aim of this study is to develop a high-precision detection and counting model to address these challenges. The adopted methodology was an improved YOLOv8n model, named YOLOv8n-DSP. To address significant scale variation, a Diverse Branch Block (DBB) was introduced into the backbone to enhance multi-scale feature representation. For improved detection of small, dense oat ears, the neck was augmented with a Spatial and Channel Synergistic Attention (SCSA) mechanism to strengthen discriminative feature extraction. Furthermore, to refine localization among overlapping oat ears, the PIoUv2 loss function was employed for bounding box regression. The main results revealed that the proposed model achieved a mean average precision (mAP) of 94.0% and an F1-score of 87.1% on the oat ear detection task, representing gains of 3.2 and 1.8 percentage points over the baseline YOLOv8n, respectively. For counting, it reached an accuracy of 82.5%, a 9.2-point improvement. In conclusion, the YOLOv8n-DSP model provides an effective and practical approach for in-field oat ear detection and counting, suggesting considerable potential as a reliable tool for future yield prediction systems and advanced intelligent agricultural equipment. Full article

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

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16 pages, 5630 KB

Open AccessEditor’s ChoiceArticle

Alternative to Groundwater Drip Irrigation for Tomatoes in Cold and Arid Regions of North China by Rainwater Harvesting from Greenhouse Film

by Mengmeng Sun, Jizong Zhang, Jiayi Qin, Huibin Li and Lifeng Zhang

Agronomy 2026, 16(1), 132; https://doi.org/10.3390/agronomy16010132 - 5 Jan 2026

Cited by 1 | Viewed by 421

Abstract

Groundwater resources are scarce in the cold and arid regions of north China. Moreover, regional water resource replenishment without external sources remains difficult. This water deficit has become a major factor restricting the sustainable development of regional vegetable production. The effective utilization of [...] Read more.

Groundwater resources are scarce in the cold and arid regions of north China. Moreover, regional water resource replenishment without external sources remains difficult. This water deficit has become a major factor restricting the sustainable development of regional vegetable production. The effective utilization of rainwater harvesting for irrigated agricultural production is necessary to suppress droughts and floods in farming under the semi-arid climate of this area in order to both guarantee a stable supply of vegetables to the market in south and north China and promote the balanced development of regional agriculture–resource–environment integration. In this study, based on continuous simulation and Python modeling, we simulated and analyzed the water supply and production effects of irrigation with harvests and stored rainwater on tomatoes under different water supply scenarios from 1992 to 2023. We then designed and tested a water-saving and high-yield project for rainwater-irrigated greenhouses in 2024 and 2025 under natural rainfall conditions in northwestern Hebei Province based on the reference irrigation scheme. The water supply satisfaction rate, water demand satisfaction rate, and volume of water inventory of tomato fields under different water supply scenarios increased with the rainwater tank size, and the corresponding drought yield reduction rate of tomato decreased. Under the actual rainfall scenarios in 2024 and 2025, a 480 m² greenhouse with a 14.4 m³ rainwater tank for producing tomatoes irrigated with rainwater drip from the greenhouse film collected 127.7 and 120.5 m³ of rainwater, respectively. The volume of the rainwater tank was exceeded 8.3 and 8.0 times, and up to 93.8% and 95.0% of the irrigated groundwater was replaced; additionally, the average yield of the small-fruited tomato ‘Beisi’ was 50,076.6 kg·hm⁻² and 48,110.2 kg·hm⁻², reaching 96.1% and 92.3% of the expected yield. Conclusion: The irrigation strategy based on the innovative “greenhouse film–rainwater harvesting–groundwater replenishment” model developed in this study has successfully achieved a high substitution rate of groundwater for greenhouse tomato production in the cold and arid regions of north China while ensuring stable yields by mitigating drought and waterlogging risks. This model not only provides a replicable technical framework for sustainable agricultural water resource management in semi-arid areas but also offers critical theoretical and practical support for addressing water scarcity and ensuring food security under global climate change. Full article

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

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14 pages, 648 KB

Open AccessArticle

Nitrogen Uptake and Use Efficiency Affected by Spatial Configuration in Maize/Peanut Intercropping in Rain-Fed Semi-Arid Region

by Wuyan Xiang, Yue Zhang, Liangshan Feng, Lizhen Zhang, Wei Bai, Wenbo Song, Chen Feng and Zhanxiang Sun

Agronomy 2026, 16(1), 131; https://doi.org/10.3390/agronomy16010131 - 5 Jan 2026

Viewed by 605

Abstract

Efficient nitrogen (N) management is critical for improving productivity and sustainability in intercropping systems, especially in semi-arid regions. Maize and peanut, the two dominant local crops, were selected to represent a typical cereal/legume intercropping system with contrasting nitrogen acquisition strategies. To investigate how [...] Read more.

Efficient nitrogen (N) management is critical for improving productivity and sustainability in intercropping systems, especially in semi-arid regions. Maize and peanut, the two dominant local crops, were selected to represent a typical cereal/legume intercropping system with contrasting nitrogen acquisition strategies. To investigate how spatial configuration regulates nitrogen uptake and nitrogen use efficiency in maize/peanut intercropping systems, a 3-year field (2022–2024) experiment was conducted on sandy soils in semi-arid northwest Liaoning, China. Six cropping systems were evaluated, including sole maize, sole peanut, and four intercropping configurations differing in strip width and crop proportion, including M2P2 (two rows of maize intercrop with two rows of peanut, M indicates maize and P indicates peanut), M2P4, M4P4, and M8P8. The total land equivalent ratio (LER) varied from 0.65 to 1.09, indicating that yield advantages were highly dependent on spatial configuration. Maize consistently exhibited stronger competitiveness than peanut, resulting in suppressed peanut growth in narrow-strip systems. Increasing strip width and peanut proportion alleviated interspecific competition and improved fertilizer nitrogen equivalent ratio (FNER) and nitrogen equivalent ratio (NER) in intercrops. Although intercropping did not consistently enhance total nitrogen uptake, nitrogen use efficiency was significantly improved. Narrow-strip systems (M2P2 and M2P4) increased nitrogen use efficiency, whereas wide-strip systems (M4P4 and M8P8) achieved yield benefits mainly through enhanced nitrogen uptake. Overall, the results highlight that spatial configuration plays a key role in regulating nitrogen uptake and interspecific competition in maize/peanut intercropping under semi-arid sandy conditions. Optimizing strip width and crop proportion is therefore critical for stabilizing yield and improving resource use efficiency in maize/peanut intercropping systems in dryland agriculture. Full article

(This article belongs to the Special Issue Effects of Efficient Crop Cultivation Techniques on Plant Nutrition and Physiology)

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20 pages, 3598 KB

Open AccessArticle

Biological Control of Endophytic Bacillus subtilis and Stenotrophomonas rhizophila Against Pyrenophora teres f. teres in Barley

by Asmaa El-Nagar, Yasser S. A. Mazrou, Ghady E. Omar, Amr Abdelfatah, Abdelnaser A. Elzaawely, Abeer H. Makhlouf and Samar M. Esmail

Agronomy 2026, 16(1), 130; https://doi.org/10.3390/agronomy16010130 - 5 Jan 2026

Viewed by 639

Abstract

Net form net blotch disease, caused by Pyrenophora teres f. teres (Ptt), is one of the most destructive barley diseases, resulting in severe yield and grain quality losses worldwide. The increasing prevalence of fungicide-resistant Ptt strains, driven by the pathogen’s high [...] Read more.

Net form net blotch disease, caused by Pyrenophora teres f. teres (Ptt), is one of the most destructive barley diseases, resulting in severe yield and grain quality losses worldwide. The increasing prevalence of fungicide-resistant Ptt strains, driven by the pathogen’s high genetic variability, highlights the urgent need for sustainable and eco-friendly disease management strategies. The present study provides novel insights into the use of native seed-borne endophytic bacteria naturally associated with barley as biological control agents against Ptt. Two endophytic bacterial strains isolated from healthy barley seeds were identified based on 16S rRNA gene sequencing as Bacillus subtilis PX491551 and Stenotrophomonas rhizophila PX494419. Their biocontrol potential against Ptt was evaluated through in vitro, greenhouse, and field experiments. In the dual-culture assay, B. subtilis and S. rhizophila inhibited the mycelial growth of Pyrenophora teres f. teres by 64.34% and 50.14%, respectively. Under greenhouse conditions, B. subtilis and S. rhizophila significantly reduced disease severity at the seedling stage, with scores of 2.00 and 4.00, respectively, compared to 9.33 in the untreated control. Beyond disease suppression, both endophytic bacteria markedly enhanced the host’s defense system. S. rhizophila induced the highest accumulation of total soluble phenolics, while B. subtilis significantly increased flavonoid content and boosted higher activities of superoxide dismutase and phenylalanine ammonia-lyase. In contrast, S. rhizophila showed the strongest induction of ascorbate peroxidase activity. Notably, field application of both bacteria consistently reduced net blotch severity over two consecutive growing seasons (2023–2024 and 2024–2025) and considerably improved chlorophyll content, 1000-grain weight, and grain yield. Overall, this study demonstrates that native seed-derived endophytic bacteria not only suppress barley net blotch but also enhance host antioxidant and defense responses, highlighting their potential as effective and sustainable biological control agents for barley disease management. Full article

(This article belongs to the Special Issue Environmentally Friendly Ways to Control Plant Disease)

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15 pages, 4614 KB

Open AccessEditor’s ChoiceArticle

Construction of a CFD Simulation and Prediction Model for Pesticide Droplet Drift in Agricultural UAV Spraying

by Qingqing Zhou, Songchao Zhang, Meng Huang, Chen Cai, Haidong Zhang, Yuxuan Jiao and Xinyu Xue

Agronomy 2026, 16(1), 129; https://doi.org/10.3390/agronomy16010129 - 5 Jan 2026

Viewed by 745

Abstract

This study employed a combined approach of computational fluid dynamics (CFD), numerical simulations, and wind tunnel tests to investigate droplet drift characteristics and develop prediction models in order to address the issues of low pesticide utilization rates and high drift risk, associated with [...] Read more.

This study employed a combined approach of computational fluid dynamics (CFD), numerical simulations, and wind tunnel tests to investigate droplet drift characteristics and develop prediction models in order to address the issues of low pesticide utilization rates and high drift risk, associated with droplet drift during agricultural unmanned aerial vehicle (UAV) spraying, as well as the unreliable results of field experiments. Firstly, a numerical model of the rotor wind field was established using the multiple reference frame (MRF) method, while the realizable k-ε turbulence model was employed to analyze the flow field. The model’s reliability was verified through wind field tests. Next, the Euler–Lagrange method was used to couple the wind field with droplet movement. The drift characteristics of two flat-fan nozzles (FP90-02 and F80-02) were then compared and analyzed. The results showed that the relative error between the simulated and wind tunnel test values was within 20%. Centrifugal nozzle experiments were carried out using single-factor and orthogonal designs to analyze the effects of flight height, rotor wind speed, flight speed, and droplet size on drift. The priority order of influence was found to be “rotor wind speed > flight height > flight speed”, while droplet size (D_V50 = 100–300 µm) was found to have no significant effect. Based on the simulation data, a multiple linear regression drift prediction model was constructed with a goodness of fit R² value of 0.9704. Under the verification condition, the relative error between the predicted and simulated values was approximately 10%. These results can provide a theoretical basis and practical guidance for assessing drift risk and optimizing operational parameters for agricultural UAVs. Full article

(This article belongs to the Special Issue Novel Studies in High-Performance and Smart Plant Protection Products Application—3rd Edition)

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16 pages, 1639 KB

Open AccessArticle

Distant Hybridization of Kazakh Wheat Varieties with Wild Aegilops Species: Cytogenetic Compatibility, Fertilization Dynamics, and Breeding Implications

by Kenenbay Kozhakhmetov, Sholpan Bastaubayeva, Nazira Slyamova, Altynai Zhakataeva, Kasymkhan Koylanov and Zhandos Zholdasbayuly

Agronomy 2026, 16(1), 128; https://doi.org/10.3390/agronomy16010128 - 5 Jan 2026

Viewed by 555

Abstract

Distant hybridization between bread wheat (Triticum aestivum L.) and wild Aegilops species is a valuable approach to take to broaden genetic diversity, but it is frequently impeded by reproductive barriers. This study evaluated crossability, pollen tube dynamics, meiotic behavior, somatic chromosome numbers, [...] Read more.

Distant hybridization between bread wheat (Triticum aestivum L.) and wild Aegilops species is a valuable approach to take to broaden genetic diversity, but it is frequently impeded by reproductive barriers. This study evaluated crossability, pollen tube dynamics, meiotic behavior, somatic chromosome numbers, and pollen fertility in twelve Kazakh wheat cultivars crossed with Ae. triaristata Willd., Ae. cylindrica Host, Ae. triuncialis L., and Ae. squarrosa L. under field-based controlled pollination. Hybridization success varied significantly among combinations, with Ae. triaristata showing the highest compatibility (26.0% in Bezostaya 1 × Ae. triaristata), while Ae. squarrosa produced the lowest seed set. In compatible crosses, pollen tubes reached the ovary within 20–30 min, whereas delayed elongation (>60 min) was associated with fertilization failure. Meiotic analysis revealed incomplete homologous pairing (3–7 bivalents per PMC) and high abnormality rates (>90%). Somatic chromosome counts (2n) of selected F₁ hybrids confirmed extensive aneuploidy and partial chromosome elimination. Pollen fertility was generally below 20%. These results identify Ae. triaristata as a promising donor species for pre-breeding in Kazakhstan and underscores the importance of integrating classical cytology with molecular approaches to overcome hybridization barriers. Full article

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

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18 pages, 2386 KB

Open AccessEditor’s ChoiceArticle

Chloroplast Genome-Based Insights into Variety Identification in Toona sinensis

by Shuqiao Zhang, Panyue Du, Hongqiang Lin, Mingcheng Wang and Rui Li

Agronomy 2026, 16(1), 127; https://doi.org/10.3390/agronomy16010127 - 4 Jan 2026

Viewed by 579

Abstract

Modern sequencing technologies have transformed the identification of medicinal plant species and varieties, overcoming the limitations of traditional approaches. To address the challenge of discriminating Toona sinensis varieties, we sequenced and compared 15 complete chloroplast genomes from five varieties in northern China. Although [...] Read more.

Modern sequencing technologies have transformed the identification of medicinal plant species and varieties, overcoming the limitations of traditional approaches. To address the challenge of discriminating Toona sinensis varieties, we sequenced and compared 15 complete chloroplast genomes from five varieties in northern China. Although these genomes exhibited a highly conserved structure, we identified eight variety-specific simple sequence repeats (SSRs), two unique tandem repeats, and several hypervariable regions with elevated nucleotide diversity. Phylogenetic analysis demonstrated that whole chloroplast genomes provided the highest resolution for variety identification, outperforming conventional barcodes. Furthermore, we developed 13 specific primer pairs targeting variable regions, and PCR validation confirmed their reliable amplification across varieties. In addition, sequence-level validation by Sanger sequencing of representative SSR and tandem repeat markers revealed stable, variety-specific repeat copy number differences. These results demonstrate that the identified chloroplast markers can effectively discriminate closely related T. sinensis varieties. This study confirms that despite overall conservation, the T. sinensis plastome contains sufficient variation for reliable identification, providing a robust framework for future germplasm conservation and molecular breeding. Full article

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

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20 pages, 1694 KB

Open AccessEditor’s ChoiceArticle

The Impact of Smoothing Techniques on Vegetation Phenology Extraction: A Case Study of Inner Mongolia Grasslands

by Mengna Liu, Baocheng Wei and Xu Jia

Agronomy 2026, 16(1), 126; https://doi.org/10.3390/agronomy16010126 - 4 Jan 2026

Viewed by 716

Abstract

The selection of data smoothing methods is one of the key steps in extracting land surface phenology parameters from time-series remote sensing data. However, existing studies often use default parameters for denoising the time-series data, neglecting the sensitivity of phenology extraction to different [...] Read more.

The selection of data smoothing methods is one of the key steps in extracting land surface phenology parameters from time-series remote sensing data. However, existing studies often use default parameters for denoising the time-series data, neglecting the sensitivity of phenology extraction to different combinations of smoothing parameters. Therefore, this study systematically evaluated three parametric smoothing methods—Savitzky–Golay (SG), Whittaker Smoother (WS), and Harmonic Analysis of Time-Series (HANTS)—and two non-parametric methods—Asymmetric Gaussian (AG) and Double-Logistic (DL)—on the accuracy of Start of Season (SOS) and End of Season (EOS) extraction at eight ground phenology observation sites in Inner Mongolia, based on time-series MOD13Q1- Normalized Difference Vegetation Index data and using the derivative method as the background for phenology parameter extraction at the site scale. The results showed that (1) DL and HANTS yielded similar accuracy for phenology extraction in desert steppe, while parametric smoothing methods outperformed non-parametric methods in phenology simulation in typical and meadow steppe regions. (2) We proposed the optimal phenology parameter combination for different steppe types in Inner Mongolia. For desert steppe, DL or HANTS was recommended. For SOS extraction in typical steppe ecosystems, the WS parameter combination was used. For EOS and phenology in meadow steppe, the HANTS parameter combination yielded better simulation results. (3) In desert and meadow steppes, the window radius in SG contributed more to phenology accuracy than polynomial order. The opposite was true for typical steppe. In WS, the contribution of the differential order to SOS and EOS extraction in desert and typical steppes was higher than that of the smoothing factor. The opposite was observed in meadow steppe. In HANTS, the fitting tolerance error was the key factor controlling phenology extraction accuracy. (4) Based on the optimal phenology extraction scheme, the smallest extraction error occurred in meadow steppe at the site scale. This was followed by typical steppe. Desert steppe showed relatively larger errors. This study overcomes the reliance on default parameters in previous studies and proposes a practical framework for phenology extraction for different grassland ecosystems. The findings provide new empirical evidence for method selection and parameter setting in remote sensing phenology monitoring. Full article

(This article belongs to the Section Grassland and Pasture Science)

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16 pages, 1458 KB

Open AccessReview

Cenchrus setaceus as an Invasive Weed: Invasiveness, Distribution, and Management (A Review)

by Sima Sohrabi, Antonia M. Rojano-Delgado, Javid Gherekhloo, Candelario Palma-Bautista and Rafael De Prado

Agronomy 2026, 16(1), 125; https://doi.org/10.3390/agronomy16010125 - 4 Jan 2026

Viewed by 852

Abstract

Invasive alien plants (IAPs) disrupt biodiversity, ecosystem functions, rural livelihoods, and human health/well-being. Hence, the negative impact of Cenchrus setaceus (syn. Pennisetum setaceum) as an invasive weed poses many concerns in terms of environmental and socio-economic impact. The abundance in previous research [...] Read more.

Invasive alien plants (IAPs) disrupt biodiversity, ecosystem functions, rural livelihoods, and human health/well-being. Hence, the negative impact of Cenchrus setaceus (syn. Pennisetum setaceum) as an invasive weed poses many concerns in terms of environmental and socio-economic impact. The abundance in previous research on invasion ecology, weed biology, and the management of C. setaceus establishes the chance to carry out an in-depth evaluation of this invasive alien species for a cohesive understanding, closely linked to policy development. This systematic review aims to provide a comprehensive evaluation of previous research, identify knowledge gaps, and incorporate recent practical research findings on C. setaceus to elucidate management options. Standard methods were used to collect the literary evidence on multiple thematic aspects linked with its traits and management. Results revealed the substantial negative impacts of C. setaceus on ecosystems, ascribed to multiple physiological, biochemical, and ecological features. Further, a multitude of plant traits such as rapid seed distribution and efficient reproductive strategies imposed serious challenges in the control of C. setaceus. Deployment of integrated control methods for at least three years in depleting seed bank conjunction by planting native grass may help in its confinement. In conclusion, policy measures like strict biosecurity/legal regulations, explicit elucidation of weed biology, early detection and response, ecological modeling, and long-term monitoring with community participation can expand the horizon of C. setaceus control and help achieve its sustainable management. Full article

(This article belongs to the Topic Plant Invasion: 2nd Edition)

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28 pages, 11495 KB

Open AccessArticle

A Pipeline for Mushroom Mass Estimation Based on Phenotypic Parameters: A Multiple Oudemansiella raphanipies Model

by Hua Yin, Danying Lei, Anping Xiong, Lu Yuan, Minghui Chen, Yilu Xu, Yinglong Wang, Hui Xiao and Quan Wei

Agronomy 2026, 16(1), 124; https://doi.org/10.3390/agronomy16010124 - 4 Jan 2026

Viewed by 382

Abstract

Estimating the mass of Oudemansiella raphanipies quickly and accurately is indispensable in optimizing post-harvest packaging processes. Traditional methods typically involve manual grading followed by weighing with a balance, which is inefficient and labor-intensive. To address the challenges encountered in actual production scenarios, in [...] Read more.

Estimating the mass of Oudemansiella raphanipies quickly and accurately is indispensable in optimizing post-harvest packaging processes. Traditional methods typically involve manual grading followed by weighing with a balance, which is inefficient and labor-intensive. To address the challenges encountered in actual production scenarios, in this work, we developed a novel pipeline for estimating the mass of multiple Oudemansiella raphanipies. To achieve this goal, an enhanced deep learning (DL) algorithm for instance segmentation and a machine learning (ML) model for mass prediction were introduced. On one hand, to segment multiple samples in the same image, a novel instance segmentation network named FinePoint-ORSeg was applied to obtain the finer edges of samples, by integrating an edge attention module to improve the fineness of the edges. On the other hand, for individual samples, a novel cap–stem segmentation approach was applied and 18 phenotypic parameters were obtained. Furthermore, principal component analysis (PCA) was utilized to reduce the redundancy among features. Combining the two aspects mentioned above, the mass was computed by an exponential GPR model with seven principal components. In terms of segmentation performance, our model outperforms the original Mask R-CNN; the

A P

,

{A P}_{50}

,

{A P}_{75}

, and

{A P}_{s}

are improved by 2%, 0.7%, 1.9%, and 0.3%, respectively. Additionally, our model outperforms other networks such as YOLACT, SOLOV2, and Mask R-CNN with Swin. As for mass estimation, the results show that the average coefficient of variation (CV) of a single sample mass in different attitudes is 6.81%. Moreover, the average mean absolute percentage error (MAPE) for multiple samples is 8.53%. Overall, the experimental results indicate that the proposed method is time-saving, non-destructive, and accurate. This can provide a reference for research on post-harvest packaging technology for Oudemansiella raphanipies. Full article

(This article belongs to the Special Issue Novel Studies in High-Throughput Plant Phenomics)

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37 pages, 1846 KB

Open AccessEditor’s ChoiceReview

Visualization Techniques for Spray Monitoring in Unmanned Aerial Spraying Systems: A Review

by Jungang Ma, Hua Zhuo, Peng Wang, Pengchao Chen, Xiang Li, Mei Tao and Zongyin Cui

Agronomy 2026, 16(1), 123; https://doi.org/10.3390/agronomy16010123 - 4 Jan 2026

Cited by 1 | Viewed by 883

Abstract

Unmanned Aerial Spraying Systems (UASS) has rapidly advanced precision crop protection. However, the spray performance of UASSs is influenced by nozzle atomization, rotor-induced airflow, and external environmental conditions. These factors cause strong spatiotemporal coupling and high uncertainty. As a result, visualization-based monitoring techniques [...] Read more.

Unmanned Aerial Spraying Systems (UASS) has rapidly advanced precision crop protection. However, the spray performance of UASSs is influenced by nozzle atomization, rotor-induced airflow, and external environmental conditions. These factors cause strong spatiotemporal coupling and high uncertainty. As a result, visualization-based monitoring techniques are now essential for understanding these dynamics and supporting spray modeling and drift-mitigation design. This review highlights developments in spray visualization technologies along the “droplet–airflow–target” chain mechanism in UASS spraying. We first outline the physical fundamentals of droplet formation, liquid-sheet breakup, droplet size distribution, and transport mechanisms in rotor-induced flow. Dominant processes are identified across near-field, mid-field, and far-field scales. Next, we summarize major visualization methods. These include optical imaging (PDPA/PDIA, HSI, DIH), laser-based scattering and ranging (LD, LiDAR), and flow-field visualization (PIV). We compare their spatial resolution, measurement range, 3D reconstruction capabilities, and possible sources of error. We then review wind-tunnel trials, field experiments, and point-cloud reconstruction studies. These studies show how downwash flow and tip vortices affect plume structure, canopy disturbance, and deposition patterns. Finally, we discuss emerging intelligent analysis for large-scale monitoring—such as image-based droplet recognition, multimodal data fusion, and data-driven modeling. We outline future directions, including unified feature systems, vortex-coupled models, and embedded closed-loop spray control. This review is a comprehensive reference for advancing UASS analysis, drift assessment, spray optimization, and smart support systems. Full article

(This article belongs to the Special Issue New Trends in Agricultural UAV Application—2nd Edition)

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16 pages, 1981 KB

Open AccessEditor’s ChoiceArticle

Microbial Metagenomics Evidence Reveals Forest Soil Amendment Contributes to Increased Sugarcane Yields in Long-Term Cropping Systems

by Rudan Li, Ruli Zhang, Zhongfu Zhang, Guolei Tang, Peifang Zhao and Jun Deng

Agronomy 2026, 16(1), 122; https://doi.org/10.3390/agronomy16010122 - 4 Jan 2026

Viewed by 700

Abstract

Long-term continuous cropping is a prevalent agricultural practice aimed at maximizing land use efficiency and crop yields, yet it often leads to severe soil degradation, nutrient imbalance, and microbial community disruption. Effective soil remediation strategies are urgently needed to restore soil health and [...] Read more.

Long-term continuous cropping is a prevalent agricultural practice aimed at maximizing land use efficiency and crop yields, yet it often leads to severe soil degradation, nutrient imbalance, and microbial community disruption. Effective soil remediation strategies are urgently needed to restore soil health and ensure sustainable agricultural production. In this study, we investigated the impact of forest soil amendment on microbial community structure, diversity, and functional potential in long-term continuous cropping soils. Using metagenomic sequencing, we analyzed soils from natural forest (BK), forest soil-amended soils (BCP), and fields under continuous cropping for 15 years (CP15) and 30 years (CP30). Forest soil amendment significantly mitigated microbial diversity loss and structural degradation caused by prolonged monoculture. Alpha diversity analysis revealed that BCP restored microbial diversity to levels comparable to BK, while beta diversity and NMDS analyses showed that microbial community composition in BCP closely resembled that of forest soil. Taxonomic profiling indicated that forest soil amendment enriched beneficial taxa such as Actinobacterota and Acidobacteriota, reversing shifts observed in CP15 and CP30. Functionally, COG and KEGG annotations revealed that BCP soils exhibited higher abundances of genes involved in carbohydrate metabolism, energy production, and nutrient cycling. Notably, the amendment reduced antibiotic resistance genes and virulence factors, potentially improving the microbial risk profile of soil communities. These findings demonstrate that forest soil amendment effectively restores microbial community structure and functionality in degraded soils, providing a nature-based solution for sustainable agriculture. Full article

(This article belongs to the Special Issue Advancements in Fertilization Strategies and Soil Health for Rice and Wheat Cultivation)

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16 pages, 3836 KB

Open AccessEditor’s ChoiceArticle

Genome-Wide Association Study Identifies Candidate Genes Regulating Berry Color in Grape (Vitis vinifera L.)

by Zhongyi Yang, Yangshengkai Xu, Tao Xu, Chao Yu, Congling Fang, Lingling Hu, Liufei Huang, Qianqian Zheng, Yuxuan Zhou, Shuyi Zhou and Yueyan Wu

Agronomy 2026, 16(1), 121; https://doi.org/10.3390/agronomy16010121 - 4 Jan 2026

Viewed by 821

Abstract

Berry color is a critical determinant of grape quality and market value. While the genetic basis of skin color has been extensively studied, the regulatory network controlling flesh coloration remains largely uncharacterized. To systematically dissect the independent genetic architectures underlying these traits, we [...] Read more.

Berry color is a critical determinant of grape quality and market value. While the genetic basis of skin color has been extensively studied, the regulatory network controlling flesh coloration remains largely uncharacterized. To systematically dissect the independent genetic architectures underlying these traits, we performed a genome-wide association study (GWAS) on 130 grape accessions, integrated with spatiotemporal expression profiling, subcellular localization, and functional validation. Our analysis revealed distinct genetic loci for skin and flesh color, confirming their independent regulation. For skin color, GWAS robustly validated VvMYBA2 as a major locus, explaining up to 51.5% of the phenotypic variance. More importantly, for flesh color, we identified and prioritized VvF3′M (Flavonoid 3′-monooxygenase) as a key candidate gene. Heterologous overexpression of VvF3′M in tobacco resulted in a profound 13.5-fold increase in anthocyanin content, suggesting its potential role as a rate-limiting enzyme in flesh pigmentation. Intriguingly, VvF3′M-overexpressing plants also exhibited a significant increase in flower number, suggesting a novel role beyond pigment biosynthesis. This study provides a comprehensive genetic and functional framework for understanding berry coloration, identifies VvF3′M as a prime target for breeding red-fleshed grapes, and reveals unexpected crosstalk between color metabolism and reproductive development. Full article

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

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21 pages, 2937 KB

Open AccessArticle

Green Manure Enables Reduced Water and Nitrogen Inputs with Sustained Yield in Maize

by Feng Wang, Yanzi Yu, Xiaoneng Pang, Yali Sun, Zhilong Fan, Wen Yin, Falong Hu, Wei He, Yunyou Nan and Aizhong Yu

Agronomy 2026, 16(1), 120; https://doi.org/10.3390/agronomy16010120 - 2 Jan 2026

Viewed by 518

Abstract

Legume green manure incorporation offers a potential pathway for sustainable cropping in arid irrigated areas. This study aimed to determine whether water and nitrogen inputs could be concurrently reduced without compromising maize productivity under this practice. A two-year field experiment (2024–2025) was conducted [...] Read more.

Legume green manure incorporation offers a potential pathway for sustainable cropping in arid irrigated areas. This study aimed to determine whether water and nitrogen inputs could be concurrently reduced without compromising maize productivity under this practice. A two-year field experiment (2024–2025) was conducted using a split-plot design with three irrigation levels (I1: 4045, I2: 3240, I3: 2430 m³·ha⁻¹) and three nitrogen rates (N1: 360, N2: 288, N3: 216 kg·ha⁻¹). Compared with conventional management (I1N1), 20% co-reduction in water and nitrogen (I2N2) maintained stable leaf area index (LAI), net photosynthetic rate (P_n), transpiration rate (T_r), DM, and GY, while significantly increasing water use efficiency (WUE) by 7.6% and nitrogen use efficiency for grain yield (NUtEg) by 11.7%. Excessive water reduction (I3) or nitrogen reduction (N3) significantly inhibited growth and reduced yield (p < 0.05). Soil water content under I2N2 did not differ significantly from I1N1 in the 0–110 cm profile, and soil total nitrogen remained higher at silking.) Structural equation model (SEM) revealed SWC and STN indirectly affected P_n and T_r via regulating LAI and SPAD (path coefficients: 0.48–0.62), which drove DM accumulation and determined GY (R² = 0.81). These short-term results suggest that moderate water-nitrogen reduction with green manure can sustain yield while improving resource efficiency, offering a promising practice for arid irrigated maize systems, though longer-term validation is needed. Full article

(This article belongs to the Section Farming Sustainability)

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14 pages, 1691 KB

Open AccessEditor’s ChoiceArticle

Intercropping with Different Companion Plants Affects the Growth and Soil Properties of Chrysanthemum morifolium

by Meng Lei, Zaibiao Zhu and Changlin Wang

Agronomy 2026, 16(1), 119; https://doi.org/10.3390/agronomy16010119 - 2 Jan 2026

Viewed by 670

Abstract

To address the soil degradation and growth inhibition caused by long-term monoculture of the medicinal plant Chrysanthemum morifolium Ramat. (Hangju), we conducted a controlled experiment comparing a monoculture (control) with seven different intercropping combinations. The intercropping treatments consisted of the main crop paired [...] Read more.

To address the soil degradation and growth inhibition caused by long-term monoculture of the medicinal plant Chrysanthemum morifolium Ramat. (Hangju), we conducted a controlled experiment comparing a monoculture (control) with seven different intercropping combinations. The intercropping treatments consisted of the main crop paired with pepper, schizonepeta, edible amaranth, dandelion, maize, soya, and purple perilla. Comprehensive assessments were conducted, encompassing plant growth parameters and rhizospheric soil properties. The soil properties included physicochemical characteristics, enzyme activities, and phenolic acid content (4-hydroxybenzoic acid, vanillic acid, and ferulic acid). The results indicated that intercropping significantly altered the rhizosphere environment of Hangju (p < 0.05). Purple perilla and maize emerged as particularly effective companion plants. Intercropping with purple perilla enhanced the aboveground biomass accumulation of Hangju and increased the activities of rhizosphere catalase, sucrase, β-glucosidase, and neutral phosphatase, although it also elevated the contents of three autotoxic phenolic acids. In contrast, intercropping with maize improved Hangju biomass and enhanced the activities of sucrase, urease, neutral phosphatase, and protease, while concurrently reducing the concentrations of all three phenolic acids. Overall, maize demonstrated optimal performance in comprehensively improving soil health by modulating enzyme activities, whereas purple perilla showed a distinct advantage in directly promoting plant growth. Full article

(This article belongs to the Section Innovative Cropping Systems)

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13 pages, 318 KB

Open AccessEditor’s ChoiceArticle

Effect of Dose and Date of Application of Vermicompost and Its Combination with N-Fertilizer on Maize Grain Yield

by Peter Kováčik, Vladimír Šimanský, Mária Kmeťová, Štefan Týr and Iwona Ledwożyw-Smoleń

Agronomy 2026, 16(1), 118; https://doi.org/10.3390/agronomy16010118 - 2 Jan 2026

Viewed by 859

Abstract

The European Union produces about 58 million tons of grain maize annually, and although Slovakia contributes only a small share, grain maize is an important crop occupying 10.6% of the country’s arable land. A two-year pot experiment was conducted to evaluate the effects [...] Read more.

The European Union produces about 58 million tons of grain maize annually, and although Slovakia contributes only a small share, grain maize is an important crop occupying 10.6% of the country’s arable land. A two-year pot experiment was conducted to evaluate the effects of vermicompost (Vc) dose and application timing, applied alone or in combination with mineral nitrogen fertilizer, on maize grain yield and selected grain-quality parameters. The spring pre-sowing Vc application at 170 kg ha⁻¹ total N proved appropriate. Increasing the Vc dose from 170 to 340 kg ha⁻¹ total N did not significantly influence grain yield, thousand kernel weight (TKW), or the contents of crude protein and starch. When soil was fertilized with Vc in autumn, the spring application of mineral N at 60 kg ha⁻¹ resulted in higher grain yield compared with the spring application of Vc at 170 kg ha⁻¹ total N. Application of Vc alone, regardless of dose or timing, did not affect starch content or TKW. The combined use of mineral and organic nitrogen sources appears to be the most effective strategy for maize nitrogen nutrition. Applying Vc in autumn or spring at 170 kg ha⁻¹ total N, followed by 60 kg ha⁻¹ mineral N in spring, created favorable conditions for achieving high grain yield and quality. Full article

(This article belongs to the Special Issue Innovations in Composting and Vermicomposting)

18 pages, 7161 KB

Open AccessEditor’s ChoiceArticle

Assessment of the Impact of the Irrigation Regime and the Application of Fermented Organic Fertilizers on Soil Salinity Dynamics and Alfalfa Growth in Coastal Saline–Alkaline Land

by Qian Yang, Shanshan Shen, Qiu Jin and Jingnan Chen

Agronomy 2026, 16(1), 117; https://doi.org/10.3390/agronomy16010117 - 1 Jan 2026

Viewed by 682

Abstract

Alfalfa cultivation is an effective way to achieve soil improvement while utilizing saline soils. Irrigation and drainage, as physical measures to leach salts, can effectively reduce the soil salt content, while application of organic fertilizer fermented with an effective microorganism (EM) may further [...] Read more.

Alfalfa cultivation is an effective way to achieve soil improvement while utilizing saline soils. Irrigation and drainage, as physical measures to leach salts, can effectively reduce the soil salt content, while application of organic fertilizer fermented with an effective microorganism (EM) may further enhance the improvement effect of saline–alkaline soil by improving soil fertility and microbial community structure. However, there is still a lack of systematic assessment on the effects of applying these three measures on the saline soil–plant system. In this study, we used alfalfa as the plant material and set three water depths of 8 mm (IR1), 16 mm (IR2), and 24 mm (IR3) under the condition of irrigating every 10 days with remote-controlled timed and quantitative irrigation, which is the most acceptable to farmers in the era of smart agriculture. EM organic fertilizer dosage was designed as 0 kg/ha (CK), 1500 kg/ha (OF1), 3000 kg/ha (OF2), 4500 kg/ha (OF3), and 6000 kg/ha (OF4). The multiple-crop alfalfa yield, quality (crude protein (CP), neutral detergent fiber (NDF), and acid detergent fiber (ADF)), and soil electrical conductivity (EC) were observed. The results showed that after the application of EM organic fertilizer, the soil’s EC value of fertilized treatments was higher than that of CK, but this difference became smaller with the prolongation of alfalfa’s growing period, implying that EM organic fertilizer could absorb more soil salts by promoting alfalfa’s growth; the water depth was obviously negatively correlated with the soil’s EC value, demonstrating that the increase in the water depth had a stronger ability to reduce the soil salts. By the end of the experiment, the soil’s EC values were reduced by 21.4–43.7% for the treatments. The alfalfa yield was significantly increased by EM organic fertilizer application, and the three alfalfa yields were increased by 63.3–69.1%, 65.4–83.6%, and 52.6–56.2%, respectively, when fertilizer application was elevated from CK to OF4. The highest alfalfa yields were all found at IR2OF4, reaching 1164.7, 2637.3 and 2519.7 t/ha, corresponding to the first, second, and third alfalfa crops, respectively. The analysis of alfalfa quality indexes revealed that higher CP values were found in the IR2 treatments, and increasing fertilizer application from OF1–OF4 resulted in an increase in CP values by 2.4–9.1%, 1.5–7.4%, and 0.8–6.7% for the three alfalfa crops. Relatively low NDF and ADF values were observed for alfalfa under IR2 conditions; however, the application of EM organic fertilizer reduced the NDF and ADF values within a certain range. According to the results of the entropy weight evaluation model, IR3OF4, IR3OF2, and IR3OF3 were the top three treatments with the best overall benefits, respectively, with relative closeness values of 0.71, 0.70, and 0.68, in that order, which suggests that the appropriate water depth is 24 mm, while the appropriate EM organic fertilizer dosage is in the range of 3000–6000 kg/ha. There was a pattern observed in our study, in which the treatments with better overall benefits were better distributed at high water depths, which emphasizes the critical role of the irrigation volume in ameliorating saline soils. The conclusions of the study are intended to provide a practical basis for the comprehensive utilization and sustainable development of saline soils. Full article

(This article belongs to the Special Issue Impact of Irrigation or Drainage on Soil Environment and Crop Growth)

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20 pages, 1883 KB

Open AccessEditor’s ChoiceArticle

Agrivoltaics in the Tropics: Soybean Yield Stability and Microclimate Buffering Across Wet and Dry Seasons

by Sung Yoon, MinKyoung Kim, SeungYeun Han and Jai-Young Lee

Agronomy 2026, 16(1), 116; https://doi.org/10.3390/agronomy16010116 - 1 Jan 2026

Viewed by 1008

Abstract

Agrivoltaics (APV) offers a promising dual land-use solution for food and energy production, yet empirical data regarding its impact on leguminous crops in tropical monsoon climates remain limited. This study evaluated the microclimate, growth, and yield of soybean (Glycine max) under an APV [...] Read more.

Agrivoltaics (APV) offers a promising dual land-use solution for food and energy production, yet empirical data regarding its impact on leguminous crops in tropical monsoon climates remain limited. This study evaluated the microclimate, growth, and yield of soybean (Glycine max) under an APV system compared to an open-field control during the wet and dry seasons in Bogor, Indonesia. The APV structure reduced incident solar radiation by approximately 35%, significantly lowering soil temperatures and maintaining higher soil moisture across both seasons. In the wet season, the APV treatment significantly increased grain yield (3528.8 vs. 1708.3 kg ha⁻¹, +106%) relative to the open field by mitigating excessive heat and radiative loads, which enhanced pod retention. In the dry season, APV maintained a yield advantage (2025.6 vs. 1724.4 kg ha⁻¹, +17%), driven by improved water conservation and a higher harvest index. Notably, shading did not delay phenological development or hinder vegetative growth in either season. These findings demonstrate that APV systems can contribute to sustainably higher yields and stability in tropical environments by buffering against season-specific environmental stresses, suggesting a viable pathway for sustainable agricultural intensification in equatorial regions. Full article

(This article belongs to the Section Farming Sustainability)

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21 pages, 10923 KB

Open AccessEditor’s ChoiceArticle

Genome-Wide Analysis of the GH3 Gene Family in Nicotiana benthamiana and Its Role in Plant Defense Against Tomato Yellow Leaf Curl Virus

by Xueting Zhong, Xiuyan Fang, Yuan Sun, Ye Zeng, Zaihang Yu, Jiapeng Li and Zhanqi Wang

Agronomy 2026, 16(1), 115; https://doi.org/10.3390/agronomy16010115 - 1 Jan 2026

Viewed by 700

Abstract

The Gretchen Hagen 3 (GH3) gene family, a key component of the early auxin-responsive gene family, plays a pivotal role in regulating plant growth, development, and stress responses. However, to date, a comprehensive genome-wide analysis of the GH3 gene family and [...] Read more.

The Gretchen Hagen 3 (GH3) gene family, a key component of the early auxin-responsive gene family, plays a pivotal role in regulating plant growth, development, and stress responses. However, to date, a comprehensive genome-wide analysis of the GH3 gene family and its potential role in plant defense against viruses, such as tomato yellow leaf curl virus (TYLCV), has not been conducted in Nicotiana benthamiana. Here, the GH3 gene family was thoroughly examined in N. benthamiana using a comprehensive genome-wide bioinformatic approach. A total of 25 potential GH3 genes were discovered in N. benthamiana. Phylogenetic analysis classified these NbGH3s into three different clades. Chromosomal distribution and synteny analyses revealed that NbGH3s are unevenly distributed across 14 chromosomes, with 20 segmental and one tandem duplication pairs. Promoter analysis suggested their involvement in phytohormone signaling and stress responses. Quantitative PCR showed that several NbGH3s are transcriptionally responsive to TYLCV infection, with five of them significantly upregulated in infected leaves. Furthermore, virus-induced gene silencing revealed that the suppression of NbGH3-3 and NbGH3-9 markedly increased host susceptibility to TYLCV, underscoring their critical roles in plant antiviral defense mechanisms. This research establishes a framework for understanding the functions of NbGH3s in plant growth and their response to TYLCV infection. Full article

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

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14 pages, 2856 KB

Open AccessArticle

Promotion of Sweet Potato Growth and Yield by Decreasing Soil CO₂ Concentrations with Forced Aeration

by Yoshiaki Kitaya

Agronomy 2026, 16(1), 114; https://doi.org/10.3390/agronomy16010114 - 1 Jan 2026

Viewed by 357

Abstract

Effects of forced aeration on sweet potato growth and yield by decreasing CO₂ concentrations in the rooting zone were investigated. The following four experiments were conducted with forced aeration in the rooting zone of sweet potato: (1) with air containing different CO [...] Read more.

Effects of forced aeration on sweet potato growth and yield by decreasing CO₂ concentrations in the rooting zone were investigated. The following four experiments were conducted with forced aeration in the rooting zone of sweet potato: (1) with air containing different CO₂ concentrations to clarify the effects of CO₂ in the rooting zone on the net photosynthetic rate and leaf conductance, (2) with atmospheric air into cultivating soil ridges through porous pipes as a feasibility study, (3) with varying forced-aeration rates, and (4) with varying time intervals of forced aeration to find a more efficient aeration method. The results are summarized as follows: (1) During the six-week growing period, the mean values of net photosynthetic rates and leaf conductance for 1% CO₂ and 2% CO₂ were 0.8 and 0.7 times, respectively, those in the Control with 0.04% CO₂. (2) When the aeration rate was 1.5 L min⁻¹ per 1 m of ridge length, the CO₂ concentration reduced to 0.1–0.2% in the rooting zone, whereas the control ridge with non-forced aeration was 0.5–1.4% CO₂. The fresh and dry weight yields of sweet potato tubers were 1.18 and 1.19 times those of the control, respectively. (3) The CO₂ concentrations decreased as the aeration rate increased. The dry weights of tuberous roots in forced-aeration ridges at aeration rates of 1.25 and 2.5 L min⁻¹ were 1.19 and 1.26 times those in the control, respectively. Sweet potato growth was promoted when forced aeration reduced CO₂ in the rooting zone. (4) The yield increased by 24% even when forced aeration was performed for just 15 min per day after irrigation. In conclusion, reducing rooting zone CO₂ concentrations through forced aeration, even for 15 minutes daily, improves sweet potato yield by approximately 20%. Full article

(This article belongs to the Special Issue Physiological and Anatomical Responses of Crops to Environmental Factors)

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21 pages, 2849 KB

Open AccessEditor’s ChoiceReview

Arbuscular Mycorrhizal Fungi Mitigate Crop Multi-Stresses Under Mediterranean Climate: A Systematic Review

by Claudia Formenti, Giovanni Mauromicale, Gaetano Pandino and Sara Lombardo

Agronomy 2026, 16(1), 113; https://doi.org/10.3390/agronomy16010113 - 1 Jan 2026

Viewed by 973

Abstract

Agricultural systems in Mediterranean-type climates are increasingly threatened by drought, salinity, extreme temperatures, heavy metal contamination, and pathogen pressure, all of which undermine crop productivity and agroecosystem stability. In this context, arbuscular mycorrhizal fungi (AMF), natural symbionts of most terrestrial plants, emerge as [...] Read more.

Agricultural systems in Mediterranean-type climates are increasingly threatened by drought, salinity, extreme temperatures, heavy metal contamination, and pathogen pressure, all of which undermine crop productivity and agroecosystem stability. In this context, arbuscular mycorrhizal fungi (AMF), natural symbionts of most terrestrial plants, emerge as key biological agents capable of enhancing crop resilience. Following PRISMA guidelines, this systematic review synthesizes current knowledge on the role of AMF in mitigating abiotic and biotic stresses, highlighting their potential as a central component of sustainable Mediterranean agriculture. The available evidence demonstrates that AMF symbiosis significantly increases plant tolerance to multiple stressors across major crop families, including Poaceae, Fabaceae, Solanaceae, and Asteraceae. Under abiotic constraints, AMF improve water and nutrient uptake via extensive hyphal networks, modulate ion homeostasis under salinity, enhance tolerance to thermal extremes, and reduce heavy metal toxicity by immobilizing contaminants. Regarding biotic stresses, AMF induce systemic resistance to pathogens, stimulate secondary metabolite production that deters herbivores, and suppress parasitic nematode populations. Moreover, co-inoculation with other biostimulants, such as plant growth-promoting rhizobacteria, shows synergistic benefits, further improving crop productivity and resource-use efficiency. Overall, AMF represent an effective and multifunctional nature-based tool for improving the sustainability of Mediterranean agroecosystems. However, further research is required to evaluate AMF performance under simultaneous multiple stress factors, thereby reflecting real-world conditions and enabling a more integrated understanding of their agronomic potential. Full article

(This article belongs to the Special Issue Adaptations and Responses of Cropping Systems to Climate Change)

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22 pages, 1059 KB

Open AccessArticle

Moderate Drought Stress Enhances Grain Quality in Upland Rice by Optimizing Nitrogen Metabolism and Endosperm Structure

by Xiao Tong, Tianyang Zhou, Yating Zhang, Junfei Gu and Yajie Zhang

Agronomy 2026, 16(1), 112; https://doi.org/10.3390/agronomy16010112 - 1 Jan 2026

Viewed by 467

Abstract

Water scarcity is a major constraint to upland rice production, and optimizing drought management to balance yield and quality is critical for sustainable agriculture. This study investigated the effects of three soil water potential (SWP) levels—0 kPa (control), −20 kPa (moderate drought), and [...] Read more.

Water scarcity is a major constraint to upland rice production, and optimizing drought management to balance yield and quality is critical for sustainable agriculture. This study investigated the effects of three soil water potential (SWP) levels—0 kPa (control), −20 kPa (moderate drought), and −40 kPa (severe drought)—on grain quality, nitrogen metabolism, and endosperm structure in two upland rice varieties (Brazilian upland rice and Zhonghan 3). Compared with the control, moderate drought significantly improved grain quality: whole milled rice recovery increased by 5.3–7.8%, chalky grain rate decreased by 16.1–29.6%, amylose content declined by 8.65–12.19%, and glutelin content rose by 9.3–12.9%. Under moderate drought, nitrogen metabolism appeared to be upregulated, as indicated by increased activities of glutamine synthetase (GS, +18.6%) and glutamate dehydrogenase (GDH, +14.2%) and higher glutamate content (+21.4%) in Zhonghan 3, with similar but slightly attenuated responses in Brazilian upland rice. Moderate drought was associated with elevated glutelin accumulation and a more compact endosperm microstructure, suggesting a potential link between nitrogen metabolism and grain development. In contrast, severe drought impaired both grain quality and yield. Correlation analysis (n = 12) revealed that the GS/GDH ratio and glutelin content were significantly correlated with improved grain quality—positively with milled rice recovery (r = 0.58 * to 0.82 **, p < 0.05 or 0.01) and negatively with chalkiness, amylose content, and setback viscosity (r = −0.58 * to −0.93 **, p < 0.05 or 0.01). These findings indicate that maintaining SWP at −20 kPa represents a feasible strategy to enhance upland rice grain quality, offering a theoretical basis for water-saving, quality-oriented production systems. Full article

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

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20 pages, 904 KB

Open AccessEditor’s ChoiceReview

Cylindrocladium Black Rot of Peanut and Red Crown Rot of Soybean Caused by Calonectria ilicicola: A Review

by Ying Xue, Xiaohe Geng, Xingxing Liang, Guanghai Lu, Guy Smagghe, Lingling Wei, Changjun Chen, Yunpeng Gai and Bing Liu

Agronomy 2026, 16(1), 111; https://doi.org/10.3390/agronomy16010111 - 1 Jan 2026

Viewed by 945

Abstract

Calonectria ilicicola (anamorph: Cylindrocladium parasiticum) is a globally important soil-borne fungal pathogen, causing Cylindrocladium black rot (CBR) in peanuts (Arachis hypogaea) and red crown rot (RCR) in soybeans (Glycine max), two legume crops central to global food security. [...] Read more.

Calonectria ilicicola (anamorph: Cylindrocladium parasiticum) is a globally important soil-borne fungal pathogen, causing Cylindrocladium black rot (CBR) in peanuts (Arachis hypogaea) and red crown rot (RCR) in soybeans (Glycine max), two legume crops central to global food security. Under favorable conditions, these diseases can cause yield losses of 15–50%, with severe epidemics causing substantial economic damage. A defining feature of C. ilicicola is its production of melanized microsclerotia that persist in soil for up to seven years, complicating long-term disease management across major production regions worldwide. The recent spread of RCR into the U.S. Midwest highlights the adaptive potential of the pathogen and underscores the urgency of updated, integrated control strategies. This review synthesizes current knowledge on disease symptoms, pathogen biology, the life cycle, isolation techniques, and molecular diagnostics, with particular emphasis on recent genomic and multiomics advances. These approaches have identified key virulence-associated genes and core pathogenicity factors, providing new insights into host–pathogen interactions and enabling more targeted resistance breeding through marker-assisted selection and the use of wild germplasm. We critically evaluate integrated disease management strategies, including host resistance, chemical and biological control, cultural practices, and physical interventions, highlighting their complementarities and limitations. By integrating classical pathology with emerging molecular and ecological innovations, this review provides a comprehensive background for developing more effective and sustainable management approaches for CBR and RCR. Full article

(This article belongs to the Special Issue Research Progress on Pathogenicity of Fungi in Crops—2nd Edition)

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15 pages, 3917 KB

Open AccessArticle

Cultivation Management Reshapes Soil Profile Configuration and Organic Carbon Sequestration: Evidence from a 45-Year Field Study

by Si-Yu Cui, Zhong-Xiu Sun, Si-Yi Duan, Wei-Wen Qiu and Ying-Ying Jiang

Agronomy 2026, 16(1), 110; https://doi.org/10.3390/agronomy16010110 - 1 Jan 2026

Viewed by 452

Abstract

Long-term human cultivation activities are the key factors of the vertical distribution and storage dynamics of soil organic carbon (SOC) in cropland. Based on a 45-year long-term field experiment, this study systematically compared SOC dynamics and carbon storage characteristics in soil profiles (0–200 [...] Read more.

Long-term human cultivation activities are the key factors of the vertical distribution and storage dynamics of soil organic carbon (SOC) in cropland. Based on a 45-year long-term field experiment, this study systematically compared SOC dynamics and carbon storage characteristics in soil profiles (0–200 cm) between cultivated land and adjacent natural forest. The findings reveal the hierarchical regulatory effects of tillage management on the soil carbon pool. The results show that: (1) Under both land use types, SOC content decreased exponentially with depth, but values in cultivated soils were 0.35–1.54% lower than in forest soils at each layer. SOC content in surface soil (0–78 cm) was significantly higher than in the subsoil (78–158 cm) and substratum layers (158–200 cm) (p < 0.01). At equivalent depths, SOC in cultivated land was significantly lower than in forest land (p < 0.01). Over 45 years, the SOC accumulation rate in the surface soil of cropland (0.07 g·kg⁻¹·yr⁻¹) was only half that of forest land (0.14 g·kg⁻¹·yr⁻¹). (2) The controls of soil physicochemical properties on SOC differed with land use: in forest soils, SOC correlated positively with clay content (r = 0.63, p < 0.01), whereas in cultivated soils, SOC was primarily regulated by total nitrogen (r = 0.94, p < 0.01) and sand content (r = 0.60, p < 0.01) and negatively correlated with bulk density (r = −0.55, p < 0.01) and pH value (r = −0.45, p < 0.05). (3) Long-term tillage significantly reshaped soil profile structure, thickening the plough layer from 20 cm to 78 cm. Surface carbon storage reached 20.76 t·ha⁻², an increase of 11.13 t·ha⁻² compared with forest soil (p < 0.01). However, storage decreased by 4.99 t·ha⁻² and 7.60 t·ha⁻² in the subsoil and substratum layers, respectively (p < 0.01). The SOC storage increment rate was 50.95 t·ha⁻²·yr⁻¹ higher than that of forest soil in the surface layer but 46.81 t·ha⁻²·yr⁻¹ and 11.12 t·ha⁻²·yr⁻¹ lower in deeper layers. These results confirm that cultivation alters soil structure and material cycling, enhancing carbon enrichment in surface soils while accelerating depletion of deeper carbon pools. This provides new insights into the vertical differentiation mechanisms of SOC under long-term agricultural management. Full article

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

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20 pages, 1079 KB

Open AccessArticle

Response of Maize Varieties with Different Nitrogen Efficiencies to Nitrogen Fertilizer

by Yulong Yang, Tao Wen, Huifeng Wang, Junfeng Ma, Xinlong Shi, Shufeng Yan, Xinyuan Mu, Chunmiao Li, Haoying Zheng, Dian Liu and Xia Zhao

Agronomy 2026, 16(1), 109; https://doi.org/10.3390/agronomy16010109 - 1 Jan 2026

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Abstract

While pursuing high yields, China’s maize industry is facing a series of complex challenges that not only affect production efficiency but also relate to the sustainable development of the industry. Maize varieties with different nitrogen use efficiencies (NUEs) significantly influence yield. Therefore, investigating [...] Read more.

While pursuing high yields, China’s maize industry is facing a series of complex challenges that not only affect production efficiency but also relate to the sustainable development of the industry. Maize varieties with different nitrogen use efficiencies (NUEs) significantly influence yield. Therefore, investigating the response mechanisms of maize varieties with varying NUEs to nitrogen fertilization can provide theoretical foundations and technical support for achieving high and stable yields, as well as for the breeding of new varieties. Based on previous research findings, this experiment selected three maize varieties with different NUE levels. A field trial was conducted with eight nitrogen fertilization gradient levels to analyze their responses to varying nitrogen inputs, thereby further evaluating the performance of maize varieties with different nitrogen use efficiencies. The results indicated that increasing nitrogen application significantly enhanced maize yield; however, with continued nitrogen application, the yield exhibited a trend of initial increase followed by a decrease or stabilization. The highest yields for Jingpin 450 (JP450), Xianyu 335 (XY335), and Qiule 368 (QL368) were achieved under the N250, N300, and N250 treatments, respectively, reaching 8.9 t·ha⁻¹, 9.2 t·ha⁻¹, and 10.1 t·ha⁻¹. Across all nitrogen treatments, QL368 > XY335 > JP450. Maize varieties with high nitrogen efficiency maintained higher post-anthesis nitrogen accumulation throughout the growth period, thereby promoting the translocation of post-anthesis nitrogen to the grains, increasing grain nitrogen content at maturity, and ultimately improving yield. The dual-high-efficiency maize variety QL 368 (QiuLe 368) achieved high yields under both low- and high-nitrogen conditions, primarily due to its high pre-anthesis nitrogen translocation rate and substantial post-anthesis nitrogen accumulation. This enhanced nitrogen translocation to the grains, improved nitrogen use efficiency, further strengthened the plant’s dry matter production capacity, and ultimately led to high yield and efficiency in maize production. Full article

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

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19 pages, 4511 KB

Open AccessArticle

Selection of High-Yield Varieties (Lines) and Analysis on Molecular Regulation Mechanism About Yield Formation of Seeds in Alfalfa

by Zhili Ren and Huiling Ma

Agronomy 2026, 16(1), 108; https://doi.org/10.3390/agronomy16010108 - 1 Jan 2026

Viewed by 536

Abstract

The goal of this study was to elucidate the genetic and molecular regulatory mechanisms underlying agronomic traits in elite alfalfa (Medicago sativa L.). Through the analysis of 44 varieties and lines, we measured 19 yield-related traits and performed transcriptome sequencing to investigate [...] Read more.

The goal of this study was to elucidate the genetic and molecular regulatory mechanisms underlying agronomic traits in elite alfalfa (Medicago sativa L.). Through the analysis of 44 varieties and lines, we measured 19 yield-related traits and performed transcriptome sequencing to investigate the factors driving yield variation. The results indicated extensive variation in agronomic traits among the tested accessions, with the coefficients of variation (CVs) ranging from 7.85% to 42.66%, suggesting substantial potential for genetic improvement. Correlation analysis revealed that seed yield was significantly and positively correlated with the number of reproductive branches and inflorescences at maturity, whereas early vegetative growth was negatively correlated with 100-seed weight. The 44 accessions were categorized into three clusters: Cluster II (the largest group) exhibited balanced traits; Cluster I showed vigorous early growth but low pod yield; and Cluster III was characterized by the highest pod and branch numbers. Principal Component Analysis (PCA) explained 65.88% of the total variation (first six components), identifying GNS31 and GNS43 as the superior and inferior genotypes, respectively. Furthermore, transcriptome profiling detected the highest number of differentially expressed genes (10,089 DEGs) in pod tissues, with 66% being upregulated. Functional enrichment analyses (GO and KEGG) highlighted that varietal differences were primarily enriched in secondary metabolism, lipid metabolism, and plant hormone signal transduction pathways. Notably, within the auxin pathway, the SAUR and GH3 families displayed significant tissue-specific expression in pods. Full article

(This article belongs to the Section Grassland and Pasture Science)

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Agronomy, Volume 16, Issue 1 (January-1 2026) – 137 articles

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