Agronomy

Article

16 pages, 6361 KiB

Open AccessEditor’s ChoiceCommunication

Hybrid CNN-SVM Classifier Approaches to Process Semi-Structured Data in Sugarcane Yield Forecasting Production

by Debnath Bhattacharyya, Eali Stephen Neal Joshua, N. Thirupathi Rao and Tai-hoon Kim

Agronomy 2023, 13(4), 1169; https://doi.org/10.3390/agronomy13041169 - 20 Apr 2023

Cited by 6 | Viewed by 2302

Information communication technology (ICT) breakthroughs have boosted global social and economic progress. Most rural Indians rely on agriculture for income. The growing population requires modern agricultural practices. ICT is crucial for educating farmers on how to be environmentally friendly. It helps them create [...] Read more.

Information communication technology (ICT) breakthroughs have boosted global social and economic progress. Most rural Indians rely on agriculture for income. The growing population requires modern agricultural practices. ICT is crucial for educating farmers on how to be environmentally friendly. It helps them create more food by solving a variety of challenges. India’s sugarcane crop is popular and lucrative. Long-term crops that require water do not need specific soil. They need water; the ground should always have adequate water due to the link between cane growth and evaporation. This research focuses on forecasting soil moisture and classifying sugarcane output; sugarcane has so many applications that it must be categorized. This research examines these claims: The first phase model predicts soil moisture using two-level ensemble classifiers. Secondly, to boost performance, the proposed ensemble model integrates the Gaussian probabilistic method (GPM), the convolutional neural network (CNN), and support vector machines (SVM). The suggested approach aims to correctly anticipate future soil moisture measurements affecting crop growth and cultivation. The proposed model is 89.53% more accurate than conventional neural network classifiers. The recommended models’ outcomes will assist farmers and agricultural authorities in boosting production. Full article

(This article belongs to the Special Issue “Smart Agriculture” Information Technology and Agriculture Cross-Discipline Research and Development)

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15 pages, 476 KiB

Open AccessEditor’s ChoiceArticle

The Impact of Rotational Pasture Management for Farm-Bred Fallow Deer (Dama dama) on Fodder Quality in the Context of Animal Welfare

by Mariusz Kulik, Katarzyna Tajchman, Antoni Lipiec, Maciej Bąkowski, Aleksandra Ukalska-Jaruga, Francisco Ceacero, Monika Pecio and Żaneta Steiner-Bogdaszewska

Agronomy 2023, 13(4), 1155; https://doi.org/10.3390/agronomy13041155 - 19 Apr 2023

Cited by 2 | Viewed by 2042

Abstract

Extensive breeding of farmed cervids, similarly to other livestock, affects the vegetation of grasslands in different seasons. For this reason, the impact of the rotational grazing of fallow deer on the chemical and species composition of the pasture sward was assessed, along with [...] Read more.

Extensive breeding of farmed cervids, similarly to other livestock, affects the vegetation of grasslands in different seasons. For this reason, the impact of the rotational grazing of fallow deer on the chemical and species composition of the pasture sward was assessed, along with the possibility of using these animals for grasslands conservation. The species composition of the pastures was analysed through the botanical-weight method. A quality index and mineral concentration test by inductively coupled plasma mass spectrometry were used to evaluate the feed. The highest proportion of valuable grasses, such as Dactylis glomerata, Poa pratensis and Lolium perenne, was recorded in the summer pens (65.7–66.1%), while the smallest proportion was recorded in the control area (46.1%). The estimated yield potential was relatively large, from 5.74 to 7.02 t ha⁻¹ dry matter. The lowest total protein content occurred in the control area in the spring and autumn. The summer pens, including the sown one, had a better fodder quality, depending on the species composition. All pens were characterised by a high production potential and similar floristic composition, without the participation of undesirable plant species, which confirms the hypothesis that, under extensive grazing conditions, fallow deer can be used for grassland conservation. Full article

(This article belongs to the Special Issue Advance in Grassland Productivity and Sustainability)

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19 pages, 3862 KiB

Open AccessEditor’s ChoiceArticle

Modeling Soil Organic Carbon Dynamics of Arable Land across Scales: A Simplified Assessment of Alternative Management Practices on the Level of Administrative Units

by Felix Witing, Martin Volk and Uwe Franko

Agronomy 2023, 13(4), 1159; https://doi.org/10.3390/agronomy13041159 - 19 Apr 2023

Cited by 3 | Viewed by 1557

Abstract

Regional assessments of soil organic carbon (SOC) trends and the carbon sequestration potential of alternative management practices (AMP) are highly relevant for developing climate change mitigation strategies for the agricultural sector. Such studies could benefit from simplified SOC modeling approaches on the scale [...] Read more.

Regional assessments of soil organic carbon (SOC) trends and the carbon sequestration potential of alternative management practices (AMP) are highly relevant for developing climate change mitigation strategies for the agricultural sector. Such studies could benefit from simplified SOC modeling approaches on the scale of administrative units as this often corresponds to the level of policy-making and data availability. However, there is a risk of systematic errors in such scaling operations. To overcome this problem, we performed a scaling experiment where we simulated the SOC dynamics of the arable soils of the State of Saxony (Germany) across a series of scales using the CANDY Carbon Balance (CCB) model. Specifically, we developed model set-ups on four different administrative levels (NUTS1, NUTS2, NUTS3, and LAU) and evaluated the simulation results of the upscaled models against a 500 m grid-based reference model. Furthermore, we quantified the carbon sequestration potential of selected AMP scenarios (addressing field grass, cover crops, and conservation tillage) across all scales. The upscaled model set-ups adequately simulated the SOC trends of Saxon arable land compared to the grid-based reference simulation (scaling error: 0.8–3.8%), while providing significant benefits for model application, data availability and runtime. The carbon sequestration potential of the AMP scenarios (1.33 Mt C until 2050) was slightly overestimated (+0.07–0.09 Mt C) by the upscaled model set-ups. Regardless of the scale of model set-up, we showed that the use of aggregated statistical input data could lead to a systematic underestimation of SOC trends. LAU and NUTS3 levels were shown to be a suitable compromise for effectively quantifying SOC dynamics and allowed for an acceptable spatial prioritization of AMPs. Such simplified, scale-adapted assessments are valuable for cross-regional comparisons and for communication to and among decision-makers, and might provide a quantitative basis for discussions on the effectiveness of AMPs in various stakeholder processes. Full article

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

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20 pages, 1930 KiB

Open AccessEditor’s ChoiceArticle

Screening Canola Genotypes for Resistance to Ammonium Toxicity

by Omar Ali Shaban Al-Awad, Kit Stasia Prendergast, Alan Robson and Zed Rengel

Agronomy 2023, 13(4), 1150; https://doi.org/10.3390/agronomy13041150 - 18 Apr 2023

Cited by 2 | Viewed by 1408

Abstract

Soil ammonium toxicity can decrease plant growth, and many crop species have low resistance to ammonium, including canola, an economically important crop. Different genotypes may differ in their resistance to ammonium toxicity, and therefore determining if there are genotypes that exhibit variation in [...] Read more.

Soil ammonium toxicity can decrease plant growth, and many crop species have low resistance to ammonium, including canola, an economically important crop. Different genotypes may differ in their resistance to ammonium toxicity, and therefore determining if there are genotypes that exhibit variation in their ability to tolerate soil ammonium is a research priority. Here, we evaluate how soil ammonium impacts canola root and shoot growth and characterise differences among canola genotypes in regard to resistance to ammonium toxicity. In the first experiment, eight ammonium chloride treatments and five calcium nitrate treatments were tested for their impact on the canola genotype Crusher TT, where high application (60 mg N/kg soil) significantly decreased the dry weight of canola shoots and roots and acidified the soil from pH_{CaCl₂ 5.9 to 5.6. In the second experiment, 30 canola genotypes were screened at selected concentrations of NH₄}⁺-N, using nitrate as the control. There was wide variation among genotypes in sensitivity to high NH₄⁺-N application. Genotypes G16, G26, and G29 had greater shoot dry weights and the highest shoot N concentration of all genotypes, and G16, G26, and G28 had root dry weight up to 35% higher at high soil NH₄⁺-N compared with other genotypes. In contrast, genotypes G3, G13, and G30 showed the largest reduction in shoot weight, and genotypes G13, G23, and G30 showed the largest reduction in root weight at high NH₄⁺-N application. Residual NH₄⁺-N/kg soil in soil was higher for sensitive than resistant genotypes, suggesting lower NH₄⁺-N use in the former. These results reveal the potential for selecting canola genotypes that are resistant to high NH₄⁺-N concentrations in soil. Full article

(This article belongs to the Special Issue Development of Tools for Diagnosing and Counteracting Ammonium Toxicity in Model and Crop Plants)

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13 pages, 2926 KiB

Open AccessEditor’s ChoiceArticle

Wheat Response and Weed-Suppressive Ability in the Field Application of a Nanoencapsulated Disulfide (DiS-NH₂) Bioherbicide Mimic

by Aurelio Scavo, Francisco J. R. Mejías, Nuria Chinchilla, José M. G. Molinillo, Stefan Schwaiger, Sara Lombardo, Francisco A. Macías and Giovanni Mauromicale

Agronomy 2023, 13(4), 1132; https://doi.org/10.3390/agronomy13041132 - 16 Apr 2023

Cited by 2 | Viewed by 1722

Abstract

Improving the efficacy of bioherbicides to overcome weed resistance phenomena is one of the main challenges within agriculture. Organic encapsulation is attracting attention as an alternative and eco-friendly tool, mainly in organic farming. In this research, for the first time, across three different [...] Read more.

Improving the efficacy of bioherbicides to overcome weed resistance phenomena is one of the main challenges within agriculture. Organic encapsulation is attracting attention as an alternative and eco-friendly tool, mainly in organic farming. In this research, for the first time, across three different wheat field trials, we tested the weed-suppressive ability (WSA) and crop response of a nanoparticle formulation of DiS-NH₂ (2,2′-disulfanediyldianiline) applied as post-emergence foliar herbicide, both at standard (T1, 0.75 g m⁻²) and double dosages (T2, 1.5 g m⁻²), compared to no weeding (NC) and chemical weed control (PC). Averaged over locations, T2 showed the highest WSA (51.3%), followed by T1 (40.9%) and PC (33.5%). T2 induced also a wheat grain yield and a plant height comparable to PC (3185 kg ha⁻¹ and 67.7 cm vs. 3153 kg ha⁻¹ and 67.7 cm, respectively). Moreover, compared to NC, T2 increased the number of spikes m⁻² (+19%) and the number of kernel spikes⁻¹ (+26%). Similar results were observed for T1, which caused also a significant reduction in non-vitreous kernels (‒40%). These promising results suggest that the nanoencapsulated DiS-NH₂ could be a good candidate as a post-emergence bioherbicide in wheat crop production. Full article

(This article belongs to the Special Issue The Future of Weed Science—Novel Approaches to Weed Management)

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14 pages, 1963 KiB

Open AccessEditor’s ChoiceArticle

Irrigation Zone Delineation and Management with a Field-Scale Variable Rate Irrigation System in Winter Wheat

by Elisa A. Flint, Bryan G. Hopkins, Jeffery D. Svedin, Ruth Kerry, Matthew J. Heaton, Ryan R. Jensen, Colin S. Campbell, Matt A. Yost and Neil C. Hansen

Agronomy 2023, 13(4), 1125; https://doi.org/10.3390/agronomy13041125 - 15 Apr 2023

Cited by 4 | Viewed by 2171

Abstract

Understanding spatial and temporal dynamics of soil water within fields is critical for effective variable rate irrigation (VRI) management. The objectives of this study were to develop VRI zones, manage irrigation rates within VRI zones, and examine temporal differences in soil volumetric water [...] Read more.

Understanding spatial and temporal dynamics of soil water within fields is critical for effective variable rate irrigation (VRI) management. The objectives of this study were to develop VRI zones, manage irrigation rates within VRI zones, and examine temporal differences in soil volumetric water content (VWC) from irrigation events via soil sensors across zones. Five irrigation zones were delineated after two years (2016 and 2017) of yield and evapotranspiration (ET) data collection. Soil sensors were placed within each zone to give real time data of VWC values and assist in irrigation decisions within a 23 ha field of winter wheat (Triticum aestivum ‘UI Magic’) near Grace, Idaho, USA (2019). Cumulative irrigation rates among zones ranged from 236 to 298 mm. Although a statistical comparison could not be made, the irrigation rates were 0.6 to 21% less than an estimated uniform grower standard practice (GSP) irrigation approach. Based on soil sensor data, crop water stress was avoided with VRI management in all but Zone 3. Thus, this simple approach to VRI zone delineation and VWC monitoring has the potential to reduce irrigation, such as this study, on average by 12% and should be evaluated in other site-years to assess its viability. Full article

(This article belongs to the Special Issue The Importance of Soil Spatial Variability in Precision Agriculture)

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23 pages, 33072 KiB

Open AccessEditor’s ChoiceArticle

Deep Learning YOLO-Based Solution for Grape Bunch Detection and Assessment of Biophysical Lesions

by Isabel Pinheiro, Germano Moreira, Daniel Queirós da Silva, Sandro Magalhães, António Valente, Paulo Moura Oliveira, Mário Cunha and Filipe Santos

Agronomy 2023, 13(4), 1120; https://doi.org/10.3390/agronomy13041120 - 14 Apr 2023

Cited by 14 | Viewed by 3536

Abstract

The world wine sector is a multi-billion dollar industry with a wide range of economic activities. Therefore, it becomes crucial to monitor the grapevine because it allows a more accurate estimation of the yield and ensures a high-quality end product. The most common [...] Read more.

The world wine sector is a multi-billion dollar industry with a wide range of economic activities. Therefore, it becomes crucial to monitor the grapevine because it allows a more accurate estimation of the yield and ensures a high-quality end product. The most common way of monitoring the grapevine is through the leaves (preventive way) since the leaves first manifest biophysical lesions. However, this does not exclude the possibility of biophysical lesions manifesting in the grape berries. Thus, this work presents three pre-trained YOLO models (YOLOv5x6, YOLOv7-E6E, and YOLOR-CSP-X) to detect and classify grape bunches as healthy or damaged by the number of berries with biophysical lesions. Two datasets were created and made publicly available with original images and manual annotations to identify the complexity between detection (bunches) and classification (healthy or damaged) tasks. The datasets use the same 10,010 images with different classes. The Grapevine Bunch Detection Dataset uses the Bunch class, and The Grapevine Bunch Condition Detection Dataset uses the OptimalBunch and DamagedBunch classes. Regarding the three models trained for grape bunches detection, they obtained promising results, highlighting YOLOv7 with 77% of mAP and 94% of the F1-score. In the case of the task of detection and identification of the state of grape bunches, the three models obtained similar results, with YOLOv5 achieving the best ones with an mAP of 72% and an F1-score of 92%. Full article

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

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17 pages, 7449 KiB

Open AccessEditor’s ChoiceArticle

Potential Impacts of Clove Essential Oil Nanoemulsion as Bio Fungicides against Neoscytalidium Blight Disease of Carum carvi L.

by Amr H. Hashem, Amer M. Abdelaziz, Mahmoud M. H. Hassanin, Abdulaziz A. Al-Askar, Hamada AbdElgawad and Mohamed S. Attia

Agronomy 2023, 13(4), 1114; https://doi.org/10.3390/agronomy13041114 - 14 Apr 2023

Cited by 17 | Viewed by 2616

Abstract

Fungal plant diseases are considered one of the most destructive diseases for plants. In this current study, Neoscytalidium dimidiatum as a fungal plant pathogen was isolated from an infected Carum carvi L. plant (C. carvi) for the first time and controlled [...] Read more.

Fungal plant diseases are considered one of the most destructive diseases for plants. In this current study, Neoscytalidium dimidiatum as a fungal plant pathogen was isolated from an infected Carum carvi L. plant (C. carvi) for the first time and controlled it using clove essential oil nanoemulsion (CEONE). This fungal plant pathogen was identified morphologically and genetically, then deposited in the gene bank under accession number OQ338188. CEONE was prepared and characterized using DLS, Zeta potential, and TEM analysis. The characterization results illustrated that the size of CEONE was lower than 100 nm, which was confirmed by TEM, which appeared spherical in shape. Results revealed that CEONE has promising antifungal activity towards N. dimidiatum, where inhibition percentages of CEONE at concentrations of 5000, 3000, and 1000 ppm were 82.2%, 53.3%, and 25.5%, respectively. At the pot level, N. dimidiatum was highly virulent on C. carvi, and CEONE and CEO were highly effective against N. dimidiatum blight disease, with 71.42% and 57.14% protection, respectively. Moreover, results revealed that there was a vast improvement in root length, plant height, and leaves. Additionally, the application of CEONE and CEO induced plant resistance by modifying proline, phenol, hydrogen peroxide, malondialdehyde, and antioxidant enzymes. In conclusion, N. dimidiatum was highly virulent on C. carvi but can be effectively reduced by CEONE through the eco-friendly method. Full article

(This article belongs to the Special Issue Advances in Plant–Fungal Pathogen Interactions)

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11 pages, 2312 KiB

Open AccessEditor’s ChoiceArticle

Use of a Pair of Pulse-Charged Grounded Metal Nets as an Electrostatic Soil Cover for Eradicating Weed Seedlings

by Yoshinori Matsuda, Yoshihiro Takikawa, Kunihiko Shimizu, Shin-ichi Kusakari and Hideyoshi Toyoda

Agronomy 2023, 13(4), 1115; https://doi.org/10.3390/agronomy13041115 - 14 Apr 2023

Cited by 2 | Viewed by 1179

Abstract

An electrostatic technique was developed to generate a simple physical method to eradicate weeds in crop fields. The proposed apparatus consisted of double-expanded metal nets connected to a pulse-charging type negative voltage generator and a grounded line. The two metal nets were arranged [...] Read more.

An electrostatic technique was developed to generate a simple physical method to eradicate weeds in crop fields. The proposed apparatus consisted of double-expanded metal nets connected to a pulse-charging type negative voltage generator and a grounded line. The two metal nets were arranged in parallel at an interval (6 mm) that caused no arc (spark) discharge between the negatively charged metal net (NC-MN) and the grounded metal net (G-MN). The paired nets were used as a soil cover to zap weed seedlings emerging from the ground. As plant seedlings are biological conductors, the seedling was subjected to an arc discharge from the upper metal net (NC-MN) when it emerged from the soil and passed through the lower net (G-MN). The discharge was strong enough to destroy the seedling with a single exposure. The arc treatment was highly effective for eradicating successively emerging mono- and dicotyledonous weed seedlings, regardless of the number of coexisting weeds or the area of the netted field. Thus, the present study provides a simple and reliable weed eradication method that could be integrated into a sustainable crop production system. Full article

(This article belongs to the Special Issue New Insights into Pathogen, Insect Pest, and Weed Control in Field and Greenhouse Cropping Systems)

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16 pages, 457 KiB

Open AccessEditor’s ChoiceArticle

Determining Pollinizer Success Rates among Several Apple (Malus domestica L.) Cultivars Using Microsatellite Markers

by Fuad Gasi, Naris Pojskić, Belma Kalamujić Stroil, Oddmund Frøynes, Milica Fotirić Akšić and Mekjell Meland

Agronomy 2023, 13(4), 1106; https://doi.org/10.3390/agronomy13041106 - 12 Apr 2023

Cited by 2 | Viewed by 1649

Abstract

In order to determine the pollinizer success rates between twelve apple cultivars in 2021 and 2022, 671 apple embryos were collected from 19 different orchards in Ullensvang (southwestern Norway) and Svelvik (southeastern Norway). Genomic DNA was extracted from the collected embryos and, afterward, [...] Read more.

In order to determine the pollinizer success rates between twelve apple cultivars in 2021 and 2022, 671 apple embryos were collected from 19 different orchards in Ullensvang (southwestern Norway) and Svelvik (southeastern Norway). Genomic DNA was extracted from the collected embryos and, afterward, a genetic characterization with 15 polymorphic microsatellite markers was conducted. An identical set of markers was also used on all twelve mother cultivars, as well as on six crabapple pollinizers, which were found in the investigated orchards. The obtained molecular data enabled paternity analyses to be performed with the objective of assigning a male parent to each embryo. The paternity analyses identified pollen donors for all, except for 3% of the embryos. In most cases, it was possible to identify the most successful pollinizers for each cultivar, with ‘Aroma’ and ‘Discovery’ being the most efficient pollen donors overall. Tree abundance seems to be a major factor in pollinizer success, while semi-cross-compatible characteristics represent a hindrance. Only 7% of the analyzed embryos were determined to have been fertilized by pollinizers outside the orchard, confirming the significance of pollinizer proximity for efficient pollination. Full article

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

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16 pages, 1268 KiB

Open AccessEditor’s ChoiceArticle

Suitability of Volcanic Ash, Rice Husk Ash, Green Compost and Biochar as Amendments for a Mediterranean Alkaline Soil

by José María De la Rosa, Sara María Pérez-Dalí, Paloma Campos, Águeda Sánchez-Martín, José Antonio González-Pérez and Ana Zelia Miller

Agronomy 2023, 13(4), 1097; https://doi.org/10.3390/agronomy13041097 - 11 Apr 2023

Cited by 3 | Viewed by 3081

Abstract

Today’s agriculture has the challenge of ensuring food supply for a growing population while human activity has already deteriorated about 40% of the world’s soils, reducing productive capacity and increasing reliance on mineral fertilizers. In this context, valorizing and recycling mineral and agricultural [...] Read more.

Today’s agriculture has the challenge of ensuring food supply for a growing population while human activity has already deteriorated about 40% of the world’s soils, reducing productive capacity and increasing reliance on mineral fertilizers. In this context, valorizing and recycling mineral and agricultural waste for use as substrates or soil supplements enhance a sustainable economy, as well as the development of activities focused on finishing the soil nutrients’ cycle. Looking for an effective solution to the massive waste generation and to enhance the agronomic qualities of soils, this study investigates the agronomic impact of contrasting inorganic and organic materials such as green compost (GC), wood biochar (WB), rice husk ash (RA), and volcanic ash (VA) as amendments to an alkaline Luvisol under controlled conditions. In this sense, barley seeds were planted and grown in a greenhouse under controlled conditions for 60 days on a soil amended with the aforementioned materials. The amendments demonstrated appropriate attributes for improving soil agronomic properties, enhancing the soil’s nutritional content with no effect on barley germination. The WB showed high aromaticity and abundance of refractory organic C. Both ash-rich amendments showed high P and K contents, which are important elements for plant development. The GC has high water retention capacity and an adequate C and N balance. Although the application of the amendments had no effect on barley yields, the plants from the ash-amended pots showed an increase of Photosystem II efficiency, indicative of a better physiological status. In terms of toxicological safety, the abundance of trace elements in soils and plants was investigated. All soils met the maximum allowable limits for these persistent pollutants. Nevertheless, longer-term tests on plants are required to determine the risk of Pb accumulation, particularly in soils amended with GC and compost-ash mixtures. The simultaneous combination of organic and inorganic amendments showed adequate agronomic attributes. WB analysis revealed its great recalcitrance and carbon sequestration potential. Full article

(This article belongs to the Special Issue The Effect of Appropriate Agriculture Management on Soil and Sustainable Crop Productivity)

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31 pages, 10310 KiB

Open AccessEditor’s ChoiceArticle

Toward Sustainable Farming: Implementing Artificial Intelligence to Predict Optimum Water and Energy Requirements for Sensor-Based Micro Irrigation Systems Powered by Solar PV

by Maged Mohammed, Hala Hamdoun and Alaa Sagheer

Agronomy 2023, 13(4), 1081; https://doi.org/10.3390/agronomy13041081 - 8 Apr 2023

Cited by 12 | Viewed by 7026

Abstract

Future trends in climate change, water scarcity, and energy costs will motivate agriculturists to develop innovative agricultural systems. In order to achieve sustainable farming in arid regions, there is an urgent need to use artificial intelligence (AI) to predict and estimate the optimum [...] Read more.

Future trends in climate change, water scarcity, and energy costs will motivate agriculturists to develop innovative agricultural systems. In order to achieve sustainable farming in arid regions, there is an urgent need to use artificial intelligence (AI) to predict and estimate the optimum water and energy requirements for the irrigation of date palms. Therefore, this study aimed to predict the optimum water and energy requirements for date palm irrigation depending on the optimum water use efficiency (WUE) and yield in arid conditions. To achieve this aim, four solar-powered micro irrigation systems were developed and evaluated under six irrigation levels for date palm irrigation. Soil moisture sensor-based controllers were used to automate irrigation scheduling for the micro irrigation systems. The water pumping in these systems was powered using a solar photovoltaic (PV) system. In addition, four machine-learning (ML) algorithms, including linear regression (LR), support vector regression (SVR), long short-term memory (LSTM) neural network, and extreme gradient boosting (XGBoost), were developed and validated for prediction purposes. These models were developed in Python programing language using the Keras library. The results indicated that the optimum WUS was achieved when the maximum setpoints of irrigation control were adjusted at the field capacity and by adjusting the minimum setpoints at 40, 50, 70, and 80% of the available water (AW). The optimum yield was achieved by adjusting the minimum setpoints at 60, 70, 80, and 90% of AW for subsurface irrigation, subsurface drip irrigation, drip irrigation, and bubbler irrigation, respectively. Therefore, the dataset was prepared at these levels for four years to train and test the models, and a fifth year was used to validate the performance of the best model. The evaluation of the models showed that the LSTM followed by XGBoost models were more accurate than the SVR and LR models for predicting the optimum irrigation water and energy requirements. The validation result showed that the LSTM was able to predict the water and energy requirements for all irrigation systems with R² ranging from 0.90 to 0.92 based on limited meteorological variables and date palm age. The findings of the current study demonstrated that the developed LSTM model can be a powerful tool in irrigation water and energy management as a fast and easy-to-use approach. Full article

(This article belongs to the Special Issue Agricultural Automation and Innovative Agricultural Systems)

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16 pages, 908 KiB

Open AccessEditor’s ChoiceArticle

Use of Medicinal and Aromatic Plant Residues for Partial Peat Substitution in Growing Media for Sonchus oleraceus Production

by Antonios Chrysargyris, Christos Goumenos and Nikolaos Tzortzakis

Agronomy 2023, 13(4), 1074; https://doi.org/10.3390/agronomy13041074 - 7 Apr 2023

Cited by 7 | Viewed by 1563

Abstract

A substantial quantity of solid waste that is high in phenolics and biocomponents is produced during the industrial manufacturing of essential oils (EOs); this presents an important management challenge for the EO sector. This currently produces a significant amount of residue, causing issues [...] Read more.

A substantial quantity of solid waste that is high in phenolics and biocomponents is produced during the industrial manufacturing of essential oils (EOs); this presents an important management challenge for the EO sector. This currently produces a significant amount of residue, causing issues of disposal and management and the impact that the residues have on both the environment and human health. The present study evaluated the potential use of Origanum dubium Boiss. residues (ODR) and Sideritis cypria Post. residues (SCR) derived via distillation at different levels (0–5–10–20–40% v/v) for use in partial peat substitution in the production of Sonchus oleraceus L. (sowthistle) plants. Both ODR and SCR accelerated the pH, electrical conductivity, organic matter content, and mineral content of the growing media, but also negatively affected several of the physical characteristics of the media, such as the total porosity and aeration. This resulted in decreased plant growth, which was more noticeable at the high residue ratios. Plants responded to this by decreasing the leaf stomatal conductance, decreasing the chlorophyll content at 40% ODR and 20% SCR mixtures, and activating several non-enzymatic (phenols, flavonoids, and antioxidant capacity) and enzymatic (superoxide dismutase) mechanisms to challenge the observed stress conditions, as indicated by lipid peroxidation and the hydrogen peroxide increase. Plants grown in residue media exhibited changes in mineral accumulation, even though both ODR and SCR were rich in minerals. It may be concluded that ODR and SCR, when employed at low levels of 10% and 20%, respectively, have the potential for use in the preparation of growing media as they may increase plant material antioxidants, but further improvement of the growing media’s properties is needed to ensure adequate yield. Full article

(This article belongs to the Special Issue Integrated Management of Crop Residues and Their Bioactive Properties in Agri-Food Production)

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14 pages, 3860 KiB

Open AccessEditor’s ChoiceArticle

FvMYB44, a Strawberry R2R3-MYB Transcription Factor, Improved Salt and Cold Stress Tolerance in Transgenic Arabidopsis

by Wenhui Li, Yangfan Wei, Lihua Zhang, Yu Wang, Penghui Song, Xingguo Li and Deguo Han

Agronomy 2023, 13(4), 1051; https://doi.org/10.3390/agronomy13041051 - 4 Apr 2023

Cited by 4 | Viewed by 1934

Abstract

MYB (v-MYB avian myeloblastosis viral oncogene homolog) transcription factor (TF) family has numerous members with complex and diverse functions, which perform an integral role in regulating the plant’s response to adversity. This study used cloning to obtain a novel MYB TF gene from [...] Read more.

MYB (v-MYB avian myeloblastosis viral oncogene homolog) transcription factor (TF) family has numerous members with complex and diverse functions, which perform an integral role in regulating the plant’s response to adversity. This study used cloning to obtain a novel MYB TF gene from the diploid strawberry Fragaria vesca, which was given the designation FvMYB44. Subcellular localization results showed that the protein of FvMYB44 was a nuclear localization protein. The resistance of Arabidopsis thaliana to salt and low temperature stresses was greatly enhanced by the overexpression of FvMYB44. When subjected to salt and temperature stress, transgenic plants showed higher proline and chlorophyll concentrations and higher superoxide dismutase (SOD), peroxidase (POD), and catalase (CAT) activities than wild-type (WT) and unloaded line (UL) of A. thaliana. In contrast, WT and UL lines had higher malondialdehyde (MDA) content and reactive oxygen species ROS (O₂⁻ and H₂O₂) content. These findings suggest that FvMYB44 may perform a role in controlling the response of A. thaliana to cold and salt stress. Full article

(This article belongs to the Special Issue Decrypting the Mechanism of Protein Transcription in Plant Stress Resistance)

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19 pages, 3378 KiB

Open AccessEditor’s ChoiceArticle

Fruit Quality and Primary and Secondary Metabolites Content in Eight Varieties of Blood Oranges

by María Ángeles Forner-Giner, Manuel Ballesta-de los Santos, Pablo Melgarejo, Juan José Martínez-Nicolás, Amparo Melián-Navarro, Antonio Ruíz-Canales, Alberto Continella and Pilar Legua

Agronomy 2023, 13(4), 1037; https://doi.org/10.3390/agronomy13041037 - 31 Mar 2023

Cited by 4 | Viewed by 2441

Abstract

In Europe, the cultivation of blood oranges for fresh consumption is increasing due to their excellent organoleptic and nutraceutical properties, which give this fruit the status of functional food. Blood orange has a higher content of bioactive compounds, which confer additional benefits for [...] Read more.

In Europe, the cultivation of blood oranges for fresh consumption is increasing due to their excellent organoleptic and nutraceutical properties, which give this fruit the status of functional food. Blood orange has a higher content of bioactive compounds, which confer additional benefits for human health. The main morphological and qualitative parameters were studied together with the content of primary metabolites by ¹H NMR and secondary metabolites by HPLC-ESI-DAD-MSⁿ from eight varieties of blood orange grafted on Citrus macrophylla. Tarocco Dalmuso was the variety with the highest values of weight (350.6 g), caliber (86.4 mm and 88.6 mm) and juice content (214.2 g). Tarocco Gallo obtained the most interesting qualitative parameters (13.95 °Brix; 22.75 MI). The most intense red juice was in Sanguinelli (a^* = 9.45) and, in crust, it was in Tarocco Scirè (a^* = 40.13). The most abundant primary metabolites were proline, aspartate and asparagine, citric acid and sucrose. The results showed that the juice of the Moro had the highest levels of total flavones and flavanones (90.07 and 592.88 mg L⁻¹, respectively), and Sanguinelli in total anthocyanins (101.06 mg L⁻¹). To conclude, Tarocco Dalmuso obtained the best values of agronomic parameters, and Moro and Sanguinelli in the content of phenolic compounds. Full article

(This article belongs to the Special Issue Advances in Fruit Pre-harvest and Postharvest Quality, Physiology and Technology)

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17 pages, 4540 KiB

Open AccessEditor’s ChoiceArticle

RDE-YOLOv7: An Improved Model Based on YOLOv7 for Better Performance in Detecting Dragon Fruits

by Jialiang Zhou, Yueyue Zhang and Jinpeng Wang

Agronomy 2023, 13(4), 1042; https://doi.org/10.3390/agronomy13041042 - 31 Mar 2023

Cited by 21 | Viewed by 4032

Abstract

There is a great demand for dragon fruit in China and Southeast Asia. Manual picking of dragon fruit requires a lot of labor. It is imperative to study the dragon fruit-picking robot. The visual guidance system is an important part of a picking [...] Read more.

There is a great demand for dragon fruit in China and Southeast Asia. Manual picking of dragon fruit requires a lot of labor. It is imperative to study the dragon fruit-picking robot. The visual guidance system is an important part of a picking robot. To realize the automatic picking of dragon fruit, this paper proposes a detection method of dragon fruit based on RDE-YOLOv7 to identify and locate dragon fruit more accurately. RepGhost and decoupled head are introduced into YOLOv7 to better extract features and better predict results. In addition, multiple ECA blocks are introduced into various locations of the network to extract effective information from a large amount of information. The experimental results show that the RDE-YOLOv7 improves the precision, recall, and mean average precision by 5.0%, 2.1%, and 1.6%. The RDE-YOLOv7 also has high accuracy for fruit detection under different lighting conditions and different blur degrees. Using the RDE-YOLOv7, we build a dragon fruit picking system and conduct positioning and picking experiments. The spatial positioning error of the system is only 2.51 mm, 2.43 mm, and 1.84 mm. The picking experiments indicate that the RDE-YOLOv7 can accurately detect dragon fruits, theoretically supporting the development of dragon fruit-picking robots. Full article

(This article belongs to the Special Issue Machine Vision Systems in Digital Agriculture)

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14 pages, 1029 KiB

Open AccessEditor’s ChoiceArticle

Effects of Two Biochar Types on Mitigating Drought and Salt Stress in Tomato Seedlings

by Wenqian Zhang, Jiahua Wei, Lili Guo, Heng Fang, Xiaojuan Liu, Kehao Liang, Wenquan Niu, Fulai Liu and Kadambot H. M. Siddique

Agronomy 2023, 13(4), 1039; https://doi.org/10.3390/agronomy13041039 - 31 Mar 2023

Cited by 22 | Viewed by 3894

Abstract

Biochar’s underlying biochemical and physiological mechanisms in reducing irrigation and salinity stress are elusive. This paper investigates the effects of two types of biochar (wood biochar and poultry biochar) on the growth and physiology of tomato seedlings exposed to the combined effects of [...] Read more.

Biochar’s underlying biochemical and physiological mechanisms in reducing irrigation and salinity stress are elusive. This paper investigates the effects of two types of biochar (wood biochar and poultry biochar) on the growth and physiology of tomato seedlings exposed to the combined effects of drought and salinity stress. Two types of biochar, wood biochar (WB) and poultry biochar (PB), were added to the soil separately, with three salinity gradients of 0, 100, and 200 mmol/L and two water supply conditions of full irrigation (FI) and deficit irrigation (DI). Results showed that biochar addition effectively improved the root water potential and osmotic potential of tomato plant under drought and salinity stress. Biochar application also mitigated leaf relative water content by 9.86% and 24.37% under drought and salinity stress, respectively. Furthermore, biochar application decreased abscisic acid concentrations in xylem sap under drought and salinity stress. Biochar altered the soil structure and increased field water holding capacity, indirectly increasing the soil water supply. While water use efficiency did not increase significantly after biochar application, a synergistic increase in seedling growth and water consumption occurred. In conclusion, biochar addition shows promise for promoting seedling growth to help mitigate the adverse impacts of drought and salinity stress on plant growth and physiology. Full article

(This article belongs to the Special Issue Soil Improvement and the Efficient Utilization of Water and Fertilizer in Greenhouse Crops)

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18 pages, 16314 KiB

Open AccessEditor’s ChoiceArticle

Phytoremediation of Cadmium-, Lead-, and Nickel-Polluted Soils by Industrial Hemp

by Giorgio Testa, Sebastiano Andrea Corinzia, Salvatore Luciano Cosentino and Barbara Rachele Ciaramella

Agronomy 2023, 13(4), 995; https://doi.org/10.3390/agronomy13040995 - 28 Mar 2023

Cited by 7 | Viewed by 2738

Abstract

The restoration of polluted soils is crucial for ecosystem recovery services. Evidently, phytoremediation is a biological and sustainable technique that includes the use of plants to remediate heavy-metal-contaminated land; the plants should be tolerant to the contamination and capable of uptake or immobilization [...] Read more.

The restoration of polluted soils is crucial for ecosystem recovery services. Evidently, phytoremediation is a biological and sustainable technique that includes the use of plants to remediate heavy-metal-contaminated land; the plants should be tolerant to the contamination and capable of uptake or immobilization of the heavy metals in the soil. Moreover, defining an economically efficient approach to the remediation of a contaminated area, with the possibility of further utilization of phytoremediation biomass, renders energy crops a great option for this technique. Energy crops, in fact, are known for their ability to grow with low agricultural input, and later, the biomass product can be used to produce biofuels, bioenergy, and bioproducts in a sustainable and renewable way, creating economic potential, especially when these crops are cultivated in marginal lands. The aim of this work is to test two monoecious industrial hemp varieties in different levels of Cd, Pb, and Ni in soil. Both varieties were tolerant to levels of Cd and Pb contamination that were higher than the limit for commercial and industrial use, while Ni showed a significant effect at all the tested concentrations. The variety Futura 75 performed better than Kc Dora in terms of productivity and tolerance. Full article

(This article belongs to the Special Issue Social-Ecologically More Sustainable Agricultural Production)

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20 pages, 14697 KiB

Open AccessEditor’s ChoiceArticle

Banana Pseudostem Visual Detection Method Based on Improved YOLOV7 Detection Algorithm

by Liyuan Cai, Jingming Liang, Xing Xu, Jieli Duan and Zhou Yang

Agronomy 2023, 13(4), 999; https://doi.org/10.3390/agronomy13040999 - 28 Mar 2023

Cited by 9 | Viewed by 2822

Abstract

Detecting banana pseudostems is an indispensable part of the intelligent management of banana cultivation, which can be used in settings such as counting banana pseudostems and smart fertilization. In complex environments, dense and occlusion banana pseudostems pose a significant challenge for detection. This [...] Read more.

Detecting banana pseudostems is an indispensable part of the intelligent management of banana cultivation, which can be used in settings such as counting banana pseudostems and smart fertilization. In complex environments, dense and occlusion banana pseudostems pose a significant challenge for detection. This paper proposes an improved YOLOV7 deep learning object detection algorithm, YOLOV7-FM, for detecting banana pseudostems with different growth conditions. In the loss optimization part of the YOLOV7 model, Focal loss is introduced, to optimize the problematic training for banana pseudostems that are dense and sheltered, so as to improve the recognition rate of challenging samples. In the data augmentation part of the YOLOV7 model, the Mixup data augmentation is used, to improve the model’s generalization ability for banana pseudostems with similar features to complex environments. This paper compares the AP (average precision) and inference speed of the YOLOV7-FM algorithm with YOLOX, YOLOV5, YOLOV3, and Faster R-CNN algorithms. The results show that the AP and inference speed of the YOLOV7-FM algorithm is higher than those models that are compared, with an average inference time of 8.0 ms per image containing banana pseudostems and AP of 81.45%. This improved YOLOV7-FM model can achieve fast and accurate detection of banana pseudostems. Full article

(This article belongs to the Special Issue Applications of Deep Learning in Smart Agriculture—Volume II)

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20 pages, 2043 KiB

Open AccessEditor’s ChoiceArticle

Very Early Biomarkers Screening for Water Deficit Tolerance in Commercial Eucalyptus Clones

by Thais R. Corrêa, Edgard Augusto de T. Picoli, Washington Luiz Pereira, Samyra A. Condé, Rafael T. Resende, Marcos Deon V. de Resende, Weverton Gomes da Costa, Cosme Damião Cruz and Edival Angelo V. Zauza

Agronomy 2023, 13(3), 937; https://doi.org/10.3390/agronomy13030937 - 22 Mar 2023

Cited by 7 | Viewed by 1897

Abstract

The identification of genotypes more tolerant to water deficit is a challenge to breeding programs. In this research, our objectives were to identify and validate traits for tolerance to water deficit in eucalypts. The estimation of genotypic parameters and early selection are proposed [...] Read more.

The identification of genotypes more tolerant to water deficit is a challenge to breeding programs. In this research, our objectives were to identify and validate traits for tolerance to water deficit in eucalypts. The estimation of genotypic parameters and early selection are proposed based on mixed models, selection indexes and validation schemes. Seedlings with 110 days were grown in a greenhouse for 12 weeks, and two water deficit treatments were conducted (polyethylene glycol and water limitation). A total of 26 biomarkers were evaluated, and 15 of them were significant, exhibited adequate heritability, and used for screening: final plant height, increment in height, increment in diameter, area of mature and fully expanded leaf, nutrient contents of N, K, Ca, Mg, S, Cu, Zn, Mn and B, photosynthesis (A) and stomatal conductance (gs). Both treatments were adequate to discriminate water deficit-tolerant clones. The ranking of tolerant clones according to their phenotype in the field demonstrates the potential for early selection and is consistent with the maintenance of water-deficit-tolerance mechanisms until adulthood. There is evidence that the choice of biomarker depends on the species involved and different strategies contributing to the tolerance trait. Full article

(This article belongs to the Special Issue Photosynthetic Adaptability of Crops under Environmental Change)

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17 pages, 3058 KiB

Open AccessEditor’s ChoiceArticle

Response of Soybean Yield and Certain Growth Parameters to Simulated Reproductive Structure Removal

by Sarah Kezar, Anna Ballagh, Vanaja Kankarla, Sumit Sharma, Raedan Sharry and Josh Lofton

Agronomy 2023, 13(3), 927; https://doi.org/10.3390/agronomy13030927 - 21 Mar 2023

Cited by 7 | Viewed by 2433

Abstract

Soybeans often encounter several in-season stressors that can alter retention of reproductive structures. To understand soybean response to structural losses through altered growth parameters—and, ultimately, yield—a field trial was established in Bixby, Oklahoma, in 2019 and 2020 and Perkins, Oklahoma, in 2019. Removal [...] Read more.

Soybeans often encounter several in-season stressors that can alter retention of reproductive structures. To understand soybean response to structural losses through altered growth parameters—and, ultimately, yield—a field trial was established in Bixby, Oklahoma, in 2019 and 2020 and Perkins, Oklahoma, in 2019. Removal of reproductive structures occurred at full flower (R2), the beginning of pod development (R3), and the beginning of seed development (R5) and at three locations on the plant (top third (T), middle third (M), whole (W)). The impact of flower removal on yield at the R2 and R3 stages did not significantly differ from that in non-treated soybean. Pod removal as late as R5 from the upper fruiting positions (T) had a lesser impact on overall yield, with R5:T showing a reduction in seed number of 860 seeds plant⁻¹, whereas R5:M was 1921 seeds plant⁻¹ below the non-treated soybean. The middle portion of the mainstem was the location where the loss demonstrated was paramount at R5, as this region is a large sink and major contributor to yield. Late-season, stress-negating yield recovery, depending on the severity, may indicate that management practices should anticipate physiological limitations for stress, as well as the potential for relative yield recovery and yield improvement. Full article

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16 pages, 1486 KiB

Open AccessEditor’s ChoiceArticle

Agronomic, Economic and Environmental Comparative of Different Aeration Systems for On-Farm Composting

by Víctor Valverde-Orozco, Irene Gavilanes-Terán, Julio Idrovo-Novillo, Lourdes Carrera-Beltrán, Cristian Basantes-Cascante, Maria Angeles Bustamante and Concepción Paredes

Agronomy 2023, 13(3), 929; https://doi.org/10.3390/agronomy13030929 - 21 Mar 2023

Cited by 3 | Viewed by 2176

Abstract

On-farm composting of agro-livestock wastes can be considered the most appropriate method for their recycling. Pile turning (PW) is one of the most widely used aeration systems for composting. However, this system has long composting periods and is inefficient at supplying oxygen and [...] Read more.

On-farm composting of agro-livestock wastes can be considered the most appropriate method for their recycling. Pile turning (PW) is one of the most widely used aeration systems for composting. However, this system has long composting periods and is inefficient at supplying oxygen and controlling the temperature. To minimize these drawbacks, the combination of turnings with forced aeration (PR) is an option; in this work, this combination was compared to PW as an aeration system for the co-composting of vegetable waste with different manures. In this comparative study, the evolution of the process, the compost quality and the economic and environmental impacts of the process were evaluated. The PR system was more appropriate for obtaining sanitized composts (the temperature was ≥55 °C for at least three consecutive days) with an adequate degree of maturity. Furthermore, this system reduced the organic matter and nutrient losses, yielding composts with higher agronomic value and a higher total combined value of the nutrients than those obtained using the PW system. However, the energy consumption and associated CO₂ emissions were lower for the PW system, since this aeration system was based only on turnings without the use of forced aeration, as in the case of the PR system. Agricultural valorization of composts will offset this energy consumption and its impact, since it will contribute to reducing the use of synthetic fertilizers. However, more studies are required on the PR composting system and other agro-livestock wastes for the creation of centralized on-farm composting sites, where all steps of the composting chain are optimized. Full article

(This article belongs to the Special Issue Composting as a Key Driver for Sustainable Agricultural Scenarios—Volume II)

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14 pages, 2498 KiB

Open AccessEditor’s ChoiceArticle

Properties of Biochar Obtained from Tropical Crop Wastes Under Different Pyrolysis Temperatures and Its Application on Acidic Soil

by Shuhui Song, Ping Cong, Chao Wang, Puwang Li, Siru Liu, Zuyu He, Chuang Zhou, Yunhao Liu and Ziming Yang

Agronomy 2023, 13(3), 921; https://doi.org/10.3390/agronomy13030921 - 20 Mar 2023

Cited by 12 | Viewed by 2023

Abstract

When biochars are produced, feedstock is a crucial factor that determines their physicochemical properties. However, the characteristics of tropical crop waste-derived biochar have not been described and limit its availability. In this study, pineapple leaf (PAL), banana stem (BAS), sugarcane bagasse (SCB) and [...] Read more.

When biochars are produced, feedstock is a crucial factor that determines their physicochemical properties. However, the characteristics of tropical crop waste-derived biochar have not been described and limit its availability. In this study, pineapple leaf (PAL), banana stem (BAS), sugarcane bagasse (SCB) and horticultural substrate (HCS), were used to prepare biochar at 300, 500 and 700 °C. Properties of biochars and their applications were analysed. The results indicated that hydrophobicity, nonpolarity and aromaticity of SCB biochar (SCBB) were higher than other biochars due to the loss of H (hydrogen), O (oxygen), and N (nitrogen). The pH of PAL biochar (PALB) and BAS biochar (BASB) ranged from 9.69 to 10.30 higher than that of SCBB and HCS biochar (HCSB) with 7.17–9.77. In PALB and BASB, sylvite was the dominant crystal structure. With temperature rising, C–H stretching, C=C stretching and H–O in alcohol groups decreased, and Si–O stretching in HCSB and SCBB strengthened. Biochars obtained at 500 °C, especially SCBB and HCSB, significantly promoted the growth of maize. The PALB and BASB greatly increased the soil pH/EC to 6.90–7.35 and 0.67–0.95 ms/cm, while those of SCBB and HCSB were 5.97–6.74 and 0.23–0.45 ms/cm. The application of the biochars to the soil increased soil pH, reducing the acidic soil stress in maize growth, especially PAL and BAS biochars prepared at 300 °C. Biochar prepared at lower temperature will greatly reduce energy consumption and increase the utilization efficiency of tropical agricultural waste resources. Full article

(This article belongs to the Special Issue Soil Properties, Microorganisms and Plants in Soils after Amelioration)

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17 pages, 5429 KiB

Open AccessEditor’s ChoiceArticle

Accurate Detection Algorithm of Citrus Psyllid Using the YOLOv5s-BC Model

by Shilei Lyu, Zunbai Ke, Zhen Li, Jiaxing Xie, Xu Zhou and Yuanyuan Liu

Agronomy 2023, 13(3), 896; https://doi.org/10.3390/agronomy13030896 - 17 Mar 2023

Cited by 6 | Viewed by 1481

Abstract

Citrus psyllid is the main vector of Huanglongbing, and as such, it is responsible for huge economic losses across the citrus industry. The small size of this pest, difficulties in data acquisition, and the lack of target detection algorithms suitable for complex occlusion [...] Read more.

Citrus psyllid is the main vector of Huanglongbing, and as such, it is responsible for huge economic losses across the citrus industry. The small size of this pest, difficulties in data acquisition, and the lack of target detection algorithms suitable for complex occlusion environments inhibit detection of the pest. The present paper describes the construction of a standard sample database of citrus psyllid in multi-focal lengths and out-of-focus states in the natural environment. By integrating the attention mechanism and optimizing the key module of BottleneckCSP, YOLOv5s-BC, we have created an accurate detection algorithm for small targets. Based on YOLOv5s, our algorithm incorporates an SE-Net channel attention module into the Backbone network and improves the detection of small targets by guiding the algorithm to the channel characteristics of small-target information. At the same time, the BottleneckCSP module in the neck network is improved, and extraction of multiple features of recognition targets is improved by the addition of a normalization layer and SiLU activation function. Experimental results based on a standard sample database show the recognition accuracy (intersection over union (IoU) = 0.5) of the YOLOv5s-BC algorithm for citrus psyllid to be 93.43%, 2.41% higher than that of traditional YOLOv5s. The accuracy and recall rates are also increased by 1.31% and 4.22%, respectively. These results confirm that the YOLOv5s-BC algorithm has good generalization ability in the natural context of citrus orchards, and it offers a new approach for the control of citrus psyllid. Full article

(This article belongs to the Special Issue Precision Operation Technology and Intelligent Equipment in Farmland)

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16 pages, 2862 KiB

Open AccessEditor’s ChoiceArticle

Yield and Quality of Processing Tomato as Improved by Biostimulants Based on Trichoderma sp. and Ascophyllum nodosum and Biodegradable Mulching Films

by Ida Di Mola, Lucia Ottaiano, Eugenio Cozzolino, Roberta Marra, Stefania Vitale, Angela Pironti, Nunzio Fiorentino and Mauro Mori

Agronomy 2023, 13(3), 901; https://doi.org/10.3390/agronomy13030901 - 17 Mar 2023

Cited by 9 | Viewed by 2421

Abstract

Tomato is a great source of bioactive compounds, is important for human health, and is cultivated worldwide. However, the high inputs required for its cultivation must be sustainably managed in order to limit yield losses, thus obtaining high-quality and environmentally friendly production. In [...] Read more.

Tomato is a great source of bioactive compounds, is important for human health, and is cultivated worldwide. However, the high inputs required for its cultivation must be sustainably managed in order to limit yield losses, thus obtaining high-quality and environmentally friendly production. In this perspective, we compared four biostimulant treatments, i.e., Ascophyllum nodosum extract—Bio; microbial biostimulant containing the micro-organism Trichoderma afroharzianum—Mic; a combination of both—M-B; not treated—Control) and three mulch treatments (biodegradable film Ecovio—ECO; biodegradable film MaterBi^®—NOV; bare soil—BS) and evaluated their effects on yield and quality traits in processing tomato. Both biodegradable films elicited a 27.0% yield increase compared to plants grown on bare soil, and biostimulants determined a 23.7% increase over the Control, with the best performance recorded for M-B (+24.8%). Biodegradable MaterBi^® film (NOV) was associated with higher total soluble solids (TSS) and firmness values (average of 4.9 °Brix and 1.30 kg cm⁻², respectively), even if a significant effect of biostimulants was observed only for the second element. Carotenoid content was higher in non-treated plants grown on bare soil as well as hydrophilic antioxidant activity (AA), but in this case, no differences between biostimulant treatments were recorded. The lipophilic AA in NOV-treated plants was about six and four times higher than observed in BS and ECO treatments, respectively; NOV also caused a 38.7% increase in ascorbic acid content over the Control but was not different from ECO. All biostimulant treatments elicited a 30% increase in phenol content compared to Control plants. Our findings highlight that microbial biostimulants based on A. nodosum extract and T. afroharzianum (both applied singularly and combined) can be considered a sustainable tool for increasing yield and improve some quality traits of processing tomato; in addition, we also confirmed the capability of biodegradable mulches, in particular, MaterBi^®, to enhance the agronomic performance of tomato. Full article

(This article belongs to the Special Issue Comparison of Sustainable Approaches in Conservation and Protected Agriculture: Asia, Latin America and Europe)

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29 pages, 4854 KiB

Open AccessEditor’s ChoiceArticle

Sustainability Research in the Wine Industry: A Bibliometric Approach

by Johnny Vicente Montalvo-Falcón, Eduardo Sánchez-García, Bartolomé Marco-Lajara and Javier Martínez-Falcó

Agronomy 2023, 13(3), 871; https://doi.org/10.3390/agronomy13030871 - 16 Mar 2023

Cited by 21 | Viewed by 7284

Abstract

Currently, the wine industry has gained great relevance worldwide. At the same time, the sustainability of the business activity has positioned itself as one of the main challenges to be achieved in the coming years. Due to the great impact that agricultural processes [...] Read more.

Currently, the wine industry has gained great relevance worldwide. At the same time, the sustainability of the business activity has positioned itself as one of the main challenges to be achieved in the coming years. Due to the great impact that agricultural processes can have on the environment, vine and wine production is particularly susceptible to the application of new technologies and processes that improve its sustainability in the medium and long term, while allowing the improvement of product quality. The main objective of this paper is to analyze the academic literature in the field of wine industry sustainability, to determine the main contributions carried out, as well as the most prominent authors, universities, and countries in this field of study. The methodology used is bibliometric analysis, specifically the Bibliometrix^® R package, in its version 4.1.1. The results reveal that research in the field of sustainability in the wine industry has increased considerably in the last three years by several leading researchers, mainly from universities located in wine-producing regions. It is concluded that research shows a trend towards collaboration among stakeholders, especially in terms of innovation, which is postulated as the main tool to improve the sustainability of the sector in the coming years. Full article

(This article belongs to the Special Issue Environment Management and Compositional Quality of Fruit and Wine)

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14 pages, 3516 KiB

Open AccessEditor’s ChoiceArticle

Three Bayesian Tracer Models: Which Is Better for Determining Sources of Root Water Uptake Based on Stable Isotopes under Various Soil Water Conditions?

by Junming Liu, Zhuanyun Si, Shuang Li, Sunusi Amin Abubakar, Yingying Zhang, Lifeng Wu, Yang Gao and Aiwang Duan

Agronomy 2023, 13(3), 843; https://doi.org/10.3390/agronomy13030843 - 14 Mar 2023

Cited by 6 | Viewed by 1800

Abstract

Stable hydrogen and oxygen isotopes provide a powerful technique for quantifying the proportion of root water uptake (RWU) from different potential water sources. Although many models coupled with stable isotopes have been developed to estimate plant water source apportionment, inter-comparisons of different methods [...] Read more.

Stable hydrogen and oxygen isotopes provide a powerful technique for quantifying the proportion of root water uptake (RWU) from different potential water sources. Although many models coupled with stable isotopes have been developed to estimate plant water source apportionment, inter-comparisons of different methods are still limited, especially their performance under different soil water content (SWC) conditions. In this study, three Bayesian tracer mixing models, which included MixSIAR, MixSIR and SIAR, were tested to evaluate their performances in determining the RWU of winter wheat under various SWC conditions (normal, dry and wet) in the North China Plain (NCP). The proportions of RWU in different soil layers showed significant differences (p < 0.05) among the three Bayesian models, for example, the proportion of 0–20 cm soil layer calculated by MixSIR, MixSIAR and SIAR was 69.7%, 50.1% and 48.3% for the third sampling under the dry condition (p < 0.05), respectively. Furthermore, the average proportion of the 0–20 cm layer under the dry condition was lower than that under normal and wet conditions, being 45.7%, 58.3% and 59.5%, respectively. No significant difference (p > 0.05) was found in the main RWU depth (i.e., 0–20 cm) among the three models, except for individual sampling periods. The performance of three models in determining plant water source allocation varied with SWC conditions: the performance indicators such as coefficient of determination (R²) and Nash-Sutcliffe efficiency coefficient (NS) in MixSIAR were higher than that in MixSIR and SIAR, showing that MixSIAR performed well under normal and wet conditions. The rank of performance under the dry condition was MixSIR, MixSIAR, and then SIAR. Overall, MixSIAR performed relatively better than other models in predicting RWU under the three different soil moisture conditions. Full article

(This article belongs to the Special Issue Isotopic & Nuclear Techniques in Studying (Agro)environmental Processes)

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18 pages, 6506 KiB

Open AccessEditor’s ChoiceArticle

Research on Winter Jujube Object Detection Based on Optimized Yolov5s

by Junzhe Feng, Chenhao Yu, Xiaoyi Shi, Zhouzhou Zheng, Liangliang Yang and Yaohua Hu

Agronomy 2023, 13(3), 810; https://doi.org/10.3390/agronomy13030810 - 10 Mar 2023

Cited by 13 | Viewed by 2213

Abstract

Winter jujube is a popular fresh fruit in China for its high vitamin C nutritional value and delicious taste. In terms of winter jujube object detection, in machine learning research, small size jujube fruits could not be detected with a high accuracy. Moreover, [...] Read more.

Winter jujube is a popular fresh fruit in China for its high vitamin C nutritional value and delicious taste. In terms of winter jujube object detection, in machine learning research, small size jujube fruits could not be detected with a high accuracy. Moreover, in deep learning research, due to the large model size of the network and slow detection speed, deployment in embedded devices is limited. In this study, an improved Yolov5s (You Only Look Once version 5 small model) algorithm was proposed in order to achieve quick and precise detection. In the improved Yolov5s algorithm, we decreased the model size and network parameters by reducing the backbone network size of Yolov5s to improve the detection speed. Yolov5s’s neck was replaced with slim-neck, which uses Ghost-Shuffle Convolution (GSConv) and one-time aggregation cross stage partial network module (VoV-GSCSP) to lessen computational and network complexity while maintaining adequate accuracy. Finally, knowledge distillation was used to optimize the improved Yolov5s model to increase generalization and boost overall performance. Experimental results showed that the accuracy of the optimized Yolov5s model outperformed Yolov5s in terms of occlusion and small target fruit discrimination, as well as overall performance. Compared to Yolov5s, the Precision, Recall, mAP (mean average Precision), and F₁ values of the optimized Yolov5s model were increased by 4.70%, 1.30%, 1.90%, and 2.90%, respectively. The Model size and Parameters were both reduced significantly by 86.09% and 88.77%, respectively. The experiment results prove that the model that was optimized from Yolov5s can provide a real time and high accuracy small winter jujube fruit detection method for robot harvesting. Full article

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22 pages, 3399 KiB

Open AccessEditor’s ChoiceArticle

Evaluating Sustainable Options for Valorization of Rice By-Products in Sri Lanka: An Approach for a Circular Business Model

by W. A. M. A. N. Illankoon, Chiara Milanese, A. K. Karunarathna, Kumuditha D. Hikkaduwa Epa Liyanage, A. M. Y. W. Alahakoon, Puhulwella G. Rathnasiri, Maria Cristina Collivignarelli and Sabrina Sorlini

Agronomy 2023, 13(3), 803; https://doi.org/10.3390/agronomy13030803 - 9 Mar 2023

Cited by 12 | Viewed by 2921

Abstract

Due to the significant quantities of waste generated by the Sri Lankan rice industry, circular bioeconomy methodologies were applied to examine value-adding entrepreneurial activities for rice industry by-products (RIB). The study was conceived after scouring the existing literature on agricultural waste management and [...] Read more.

Due to the significant quantities of waste generated by the Sri Lankan rice industry, circular bioeconomy methodologies were applied to examine value-adding entrepreneurial activities for rice industry by-products (RIB). The study was conceived after scouring the existing literature on agricultural waste management and interviewing experts in the field and the rice industry. In the first phase, the suitability of valorizing alternatives for RIB was considered via a multi-criteria decision-making method. Valorization options, such as biochar production, energy purposes, composting, and other activities, were evaluated using an analytical hierarchy process (AHP) based on four criteria, namely environmental, social, technical, and economic issues. The results indicated that the highest priority should be given to environmental, social, and economic considerations, with local priority vectors of 0.5887, 0.2552, and 0.0955, respectively. It was found that biochar production is the optimal valorization strategy for managing RIB in Sri Lanka. From these findings, the development of a sustainable business model for making biochar out of RIB was done based on commercial motivations and value addition in biochar manufacturing processes. The Business Model Canvas elements played a vital role in categorizing and interpreting the case study data. Though the RIB seems undervalued at present, it was found that as a direct result of environmental concerns, several stakeholders have developed RIB valorization with an emphasis on bioenergy generation and biochar production. Adequate subsidies (technology and knowledge), standard regulations, more collective actions for creating economies of scale, and marketing strategies (consumer awareness) are all necessary for the successful implementation of sustainable circular business models. Full article

(This article belongs to the Special Issue Recycling Agro-Food and Urban Wastes According the Circular Economy and Sustainability Paradigms)

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17 pages, 1873 KiB

Open AccessEditor’s ChoiceArticle

Three-Year Survey of Fusarium Multi-Metabolites/Mycotoxins Contamination in Wheat Samples in Potentially Epidemic FHB Conditions

by Valentina Spanic, Marko Maricevic, Ivica Ikic, Michael Sulyok and Hrvoje Sarcevic

Agronomy 2023, 13(3), 805; https://doi.org/10.3390/agronomy13030805 - 9 Mar 2023

Cited by 5 | Viewed by 1774

Abstract

Fusarium head blight (FHB) is a fungal disease of cereals including wheat, which results in significant economic losses and reductions in grain quality. Additionally, the presence of Fusarium spp. results in productions of mycotoxins/metabolites, some of which are toxic in low concentrations. The [...] Read more.

Fusarium head blight (FHB) is a fungal disease of cereals including wheat, which results in significant economic losses and reductions in grain quality. Additionally, the presence of Fusarium spp. results in productions of mycotoxins/metabolites, some of which are toxic in low concentrations. The liquid chromatography with tandem mass spectrometry (LC-MS/MS) method was applied to 216 wheat samples from field conditions diseased with FHB. Data obtained show that out of 28 metabolites detected, deoxynivalenol (DON), deoxynivalenol-3-glucoside (D3G), enniatin B (ENN B), enniatin B1 (ENN B1), culmorin, 15-hydroxyculmorin, and aurofusarin were the most prevalent mycotoxins/metabolites over three years (2014–2016). In 2014–2016, 100, 100 and 96% of the samples were contaminated with zearalenone (ZEN). Of the masked mycotoxins, D3G occurred at a high incidence level of 100% in all three investigated years. Among emerging mycotoxins, moniliformin (MON), beauvericin (BEA) and enniatins (ENNs) showed high occurrences ranging from 27 and 100% during three investigated years. Co-occurrence of Fusarium mycotoxins/metabolites was high and almost all were highly correlated to each other but their possible synergistic, additive, or antagonistic effects of toxicity, should be taken into consideration. Our results demonstrated that modified and emerging mycotoxins/metabolites contributed substantially to the overall contamination of wheat grains. To avoid disparagement, it is necessary to analyse these forms in future mycotoxin monitoring programs and to set their maximum levels. Full article

(This article belongs to the Special Issue Treatment and Management of Fusarium Disease in Wheat)

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16 pages, 3502 KiB

Open AccessFeature PaperEditor’s ChoiceArticle

The Effect of Nitrogen and Sulphur Application on Soybean Productivity Traits in Temperate Climates Conditions

by Aleksandra Głowacka, Elvyra Jariene, Ewelina Flis-Olszewska and Anna Kiełtyka-Dadasiewicz

Agronomy 2023, 13(3), 780; https://doi.org/10.3390/agronomy13030780 - 8 Mar 2023

Cited by 12 | Viewed by 4355

Abstract

Both nitrogen and sulphur are important macronutrients necessary for the proper development and yield of soybean. Moreover, sulphur plays a special role in nitrogen metabolism in the plant, and sulphur deficiency leads to a reduction in the utilization of nitrogen from fertilizer. The [...] Read more.

Both nitrogen and sulphur are important macronutrients necessary for the proper development and yield of soybean. Moreover, sulphur plays a special role in nitrogen metabolism in the plant, and sulphur deficiency leads to a reduction in the utilization of nitrogen from fertilizer. The objective of this study was to assess the effect of nitrogen and sulphur application on the yield and quality traits of soybean seeds. The following factors were analyzed in the experiment: I. Nitrogen application rate: 0, 30 and 60 kg ha⁻¹ applied at different times (before sowing and/or at the start of the seed filling stage); II. Sulphur application rate: 0 and 40 kg ha⁻¹ applied in two portions: half during the development of lateral shoots and half at the start of flowering. Thus the 14 fertilizer combinations were obtained. Result show that the highest seeds yield was obtained in the combinations with 60 kg N applied ½ before sowing + ½ after emergence (BBCH 73-75) and ¾ before sowing +¼ after emergence. In these combinations, sulphur did not significantly affect seed yield. In the remaining nitrogen application, sulphur application significantly increased the seed yield. Taking into account the yield and the chemical composition of the soybean seeds, fertilization with 60 kg N ha⁻¹ in two portions can be recommended—½ or ¾ before sowing and the remainder during the development of pods and seeds—in combination with sulphur application. Full article

(This article belongs to the Special Issue The Role of Mineral Elements in the Crop Growth and Production)

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24 pages, 4089 KiB

Open AccessEditor’s ChoiceArticle

Enhancement of Morphological and Physiological Performance of Zea mays L. under Saline Stress Using ZnO Nanoparticles and 24-Epibrassinolide Seed Priming

by Awais Ahmad, ElKamil Tola, Thobayet S. Alshahrani and Mahmoud F. Seleiman

Agronomy 2023, 13(3), 771; https://doi.org/10.3390/agronomy13030771 - 7 Mar 2023

Cited by 24 | Viewed by 2552

Abstract

Salinity is one of the most devastating environmental factors limiting crop productivity worldwide. Therefore, our study investigates the effect of seed priming with zinc oxide nanoparticles (ZnO NPs: 0, 50, and 100 mg L⁻¹), 24-epibrassinolide (EBL: 0.0, 0.2, and 0.4 µM), [...] Read more.

Salinity is one of the most devastating environmental factors limiting crop productivity worldwide. Therefore, our study investigates the effect of seed priming with zinc oxide nanoparticles (ZnO NPs: 0, 50, and 100 mg L⁻¹), 24-epibrassinolide (EBL: 0.0, 0.2, and 0.4 µM), and their combined treatments on maize (Zea mays L.) grown with different levels of saline stress (i.e., control, 5, 10 dS m⁻¹) under semi-controlled conditions. Higher saline stress (10 dS m⁻¹) negatively influenced the growth traits, physiological attributes, and elemental (i.e., Zn and K) uptake for both roots and shoots of maize, whereas it increased Na⁺ accumulation and Na⁺/K⁺ ratio in comparison to other treatments. However, seed priming with ZnO NPs and EBL as well as their combinations showed amelioration of the detrimental effects of saline stress on the growth and physiological and biochemical performance of maize. In general, seed priming with combined treatments of ZnO NPs and EBL were significantly more effective than either ZnO NPs or EBL as individual treatments. A combination of 100 mg L⁻¹ ZnO NPS + 0.2 µM EBL resulted in the highest values of root length, root surface area, stem diameter, relative leaf water contents, total chlorophyll, net rate of photosynthesis, zinc accumulation, and K⁺ uptake, while it resulted in the lowest Na⁺ and Na⁺/K⁺ ratio, especially under the highest saline-stress treatment. Thus, we concluded that seed priming with combined ZnO NPs and EBL can effectively mitigate the saline-stress-mediated decline in the morphological, physiological, and biochemical traits of maize. Full article

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

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15 pages, 1997 KiB

Open AccessFeature PaperEditor’s ChoiceArticle

Improved Forage Quality in Alfalfa (Medicago sativa L.) via Selection for Increased Stem Fiber Digestibility

by Zhanyou Xu, Deborah J. Heuschele, JoAnn F. S. Lamb, Hans-Joachim G. Jung and Deborah A. Samac

Agronomy 2023, 13(3), 770; https://doi.org/10.3390/agronomy13030770 - 7 Mar 2023

Cited by 6 | Viewed by 1882

Abstract

The low digestibility of fiber in alfalfa (Medicago sativa L.) limits dry matter intake and energy availability in ruminant animal production systems. Previously, alfalfa plants were identified for low or high rapid (16 h) and low or high potential (96 h) in [...] Read more.

The low digestibility of fiber in alfalfa (Medicago sativa L.) limits dry matter intake and energy availability in ruminant animal production systems. Previously, alfalfa plants were identified for low or high rapid (16 h) and low or high potential (96 h) in vitro neutral detergent fiber digestibility (IVNDFD) of plant stems. Here, two cycles of bidirectional selection for 16 h and 96 h IVNDFD were carried out. The resulting populations were evaluated for total herbage, percentage of stems to total biomass, IVNDFD, neutral detergent fiber (NDF), and acid detergent lignin as a proportion of NDF (ADL/NDF) at three maturity stages. Within these populations, 96 h IVNDFD was highly heritable (h² = 0.71), while 16 h IVNDFD had lower heritability (h² = 0.46). Selection for high IVNDFD reduced NDF and ADL/NDF in plant stems at the late flowering and green pod maturity stages and reduced seasonal variability in stem digestibility but did not alter the percentage of stems. Stability analyses across 12 harvest environments found that selection for high IVNDFD had little effect on environmental stability of the trait compared to the unselected population. Thus, selection for stem IVNDFD was a highly effective strategy for developing alfalfa populations with improved nutritional quality without changing the percentage of stems to total biomass. Full article

(This article belongs to the Special Issue Breeding Advances in Legume Diversification and Biofortification)

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16 pages, 352 KiB

Open AccessEditor’s ChoiceArticle

Biostimulant Application, under Reduced Nutrient Supply, Enhances Quality and Sustainability of Ornamental Containerized Transplants

by Danilo Loconsole, Giuseppe Cristiano and Barbara De Lucia

Agronomy 2023, 13(3), 765; https://doi.org/10.3390/agronomy13030765 - 6 Mar 2023

Cited by 4 | Viewed by 3628

Abstract

Ornamental containerized transplant production needs high doses of controlled release fertilizers (CFR), but it is known that there is an environmental risk caused by inadequate fertilization management. To the best of our knowledge, amino acid-(AaB) and seaweed extract-(SeB) based biostimulant application, in ornamental [...] Read more.

Ornamental containerized transplant production needs high doses of controlled release fertilizers (CFR), but it is known that there is an environmental risk caused by inadequate fertilization management. To the best of our knowledge, amino acid-(AaB) and seaweed extract-(SeB) based biostimulant application, in ornamental transplant production, is still poorly studied. Therefore, the aim of this work was to assess the hypothesis that, under reduced nutrient supply, SeB and AaB applications, via foliar spray, can promote quality and sustainability in the production of high-quality ornamental seedlings with a 90-day growing cycle. The CRF incorporated into the peat-growing medium was Osmocote Exact Mini in formulation N:P:K = 15 + 9 + 11 (3 months). Six treatments were compared in two economically important potted (0.3 L in volume) ornamentals: Abelia × grandiflora and Lantana camara: T1 = conventional full CRF dose: 4 gL⁻¹ per pot; T2 = limited CRF dose: 50% of T1; T3 = T2 + MC-Extra^® [SeB 0.5 gL⁻¹]; T4 = T2 + MC-Extra^® [SeB 1.0 gL⁻¹]; T5 = T2 + Megafol^® [AaB 1.5 mL L⁻¹]; T6 = T2 + Megafol^® [AaB 2.5 mL L⁻¹]. The research results showed that the application of 50% CRF plus biostimulant application resulted in plant performance greater than or equal to those raised under the conventional CRF full dose. In particular, S1 (Abelia × grandiflora ‘Edward Goucher’) and S2 (Lantana camara ‘Little Lucky’) behaved differently concerning the Megafol^® dose under 50% CRF; compared to T1, in A. × grandiflora young transplants, T5 increased root morphological characteristics, as well as number of leaves, leaf area, and dry biomass accumulation; in L. camara, T6 achieved higher performance. The application of biostimulants under 50% CRF also improved, in both A. × grandiflora and L. camara, the physiological and agronomical Nitrogen Use Efficiency, compared to a full CRF dose. This study can support decision-making in terms of agronomic technique choices in line with the sustainable development of high-quality ornamental transplant production. Full article

(This article belongs to the Special Issue Effects of Soil Fertility and Plant Growth Promoters on Growth, Yield, and Quality of Crops)

18 pages, 2937 KiB

Open AccessEditor’s ChoiceArticle

The Use of Plant Growth Promoting Rhizobacteria to Reduce Greenhouse Gases in Strawberry Cultivation under Different Soil Moisture Conditions

by Dominika Paliwoda, Grzegorz Mikiciuk, Małgorzata Mikiciuk, Tymoteusz Miller, Anna Kisiel, Lidia Sas-Paszt, Agnieszka Kozioł and Adam Brysiewicz

Agronomy 2023, 13(3), 754; https://doi.org/10.3390/agronomy13030754 - 4 Mar 2023

Cited by 3 | Viewed by 2029

Abstract

One of the main causes of climate change is the emission of GHGs, and one of the sources for the generation of such gasses is agriculture via plant production. Considering the foregoing, a study was conducted to assess PGPRs in strawberry cultivation which [...] Read more.

One of the main causes of climate change is the emission of GHGs, and one of the sources for the generation of such gasses is agriculture via plant production. Considering the foregoing, a study was conducted to assess PGPRs in strawberry cultivation which were able to limit GHG emissions. The first experimental factor was the inoculation of plant roots with the Bacillus sp. strains DLGB3, DKB26, DKB58, and DKB 84; the Pantoea sp. strains DKB63, DKB64, DKB65, and DKB68; Azotobacter sp. AJ 1.2; and Pseudomonas sp. PJ 1.1. The second experimental factor constituted the different moisture levels of the growth substrate. In the experiment, emissions of NH₃, CO₂, N₂O, and CH₄ were measured. In light of the conducted research, five strains were selected (Azotobacter sp. AJ 1.2; Pantoea sp. DKB64, DKB63, and DKB68; and Pseudomonas sp. strain PJ 1.1) that showed the greatest potential for reducing GHG emissions depending on the prevailing environmental conditions. The application of the tested bacterial strains under different moisture conditions in the substrate either reduced or did not affect GWP. This research on PGPR, which was conducted to select strains of rhizosphere bacteria that would be able to reduce GHG emissions, may form the basis for creating an inoculum and can be employed as an effective strategy for mitigating certain abiotic stresses. Full article

(This article belongs to the Special Issue Agricultural Management for Climate Change Adaptation, Greenhouse Gas Mitigation, and Agricultural Productivity)

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30 pages, 3872 KiB

Open AccessEditor’s ChoiceArticle

Soil Management Strategies in Organic Almond Orchards: Implications for Soil Rehabilitation and Nut Quality

by Belén Cárceles Rodríguez, Víctor Hugo Durán Zuazo, Juan Francisco Herencia Galán, Leontina Lipan, Miguel Soriano, Francisca Hernández, Esther Sendra, Ángel Antonio Carbonell-Barrachina, Baltasar Gálvez Ruiz and Iván Francisco García-Tejero

Agronomy 2023, 13(3), 749; https://doi.org/10.3390/agronomy13030749 - 4 Mar 2023

Cited by 8 | Viewed by 2808

Abstract

The implementation of soil conservation measures is essential to promote sustainable crop production in the Mediterranean region. In an organic rainfed almond orchard located in Lanjarón (SE, Spain), a study carried out during 2016–2021 analyzed the influence of different soil management strategies (SMSs) [...] Read more.

The implementation of soil conservation measures is essential to promote sustainable crop production in the Mediterranean region. In an organic rainfed almond orchard located in Lanjarón (SE, Spain), a study carried out during 2016–2021 analyzed the influence of different soil management strategies (SMSs) (TT, traditional tillage; NT, no tillage; VF, cover of Vicia faba; VS, cover of Vicia sativa; VS-VE, cover of Vicia sativa and Vicia ervilia) on some selected physical (bulk density, available water content, and aggregate stability), chemical (pH, electrical conductivity, soil-organic content, N, P, K, and micronutrients), and biological (microbial activity) soil properties, relevant to soil health, and their implications for yield and almond quality (physical and chemical). Our results showed that the SMS with legume cover improves soil properties, which had a favorable effect on soil health. The mean almond yield was not significantly affected by the SMS applied, being 315.9, 256.4, 229.1, 212.5, and 176.6 kg ha⁻¹ year⁻¹ for TT, VF, VS-VE, VS, and NT, respectively. Regarding the almond nut quality, the strategy based on implementation of legume cover increased the almond antioxidant activity and the total polyphenol content, which would improve their nutritional value. Here we showed how the use of sustainable SMSs improved the soil properties compared to traditional tillage in rainfed organic almonds, allowing the long-term sustainability of agroecosystems while at the same time obtaining higher nutritional quality almonds. Full article

(This article belongs to the Special Issue Water Scarcity Management in Fruit Orchards: Potential Benefits on Fruit Quality and Long-Term Orchards Conservation)

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15 pages, 1629 KiB

Open AccessEditor’s ChoiceArticle

Fungicidal Activity of Caproate Produced by Clostridium sp. strain E801, a Bacterium Isolated from Cocopeat Medium Subjected to Anaerobic Soil Disinfestation

by Shota Shirane, Noriaki Momma, Toshiyuki Usami, Chiharu Suzuki, Tomoyuki Hori, Tomo Aoyagi and Seigo Amachi

Agronomy 2023, 13(3), 747; https://doi.org/10.3390/agronomy13030747 - 3 Mar 2023

Cited by 4 | Viewed by 2215

Abstract

Anaerobic soil disinfestation (ASD) consists of the application of labile organic materials to soil, flooding, and covering the soil surface with plastic film. Anaerobic soil disinfestation is a widely used ecofriendly alternative to chemical fumigation for eliminating soil-borne plant pathogens. However, the exact [...] Read more.

Anaerobic soil disinfestation (ASD) consists of the application of labile organic materials to soil, flooding, and covering the soil surface with plastic film. Anaerobic soil disinfestation is a widely used ecofriendly alternative to chemical fumigation for eliminating soil-borne plant pathogens. However, the exact mode of action of ASD has not been elucidated. In particular, the potential role of anaerobic soil bacteria in disinfestation is unclear. In this study, we isolated a predominant bacterium designated as strain E801 from cocopeat medium after laboratory-scale ASD with ethanol as the carbon source. The strain was closely related with Clostridium kluyveri, and fermentatively produced butyrate and caproate from ethanol and acetate. Interestingly, the culture supernatant of strain E801 strongly suppressed the growth of Fusarium oxysporum f. sp. lycopersici (Fol) in a pH-dependent manner. Among the volatile fatty acids produced by E801, only caproate showed significant growth suppression at pHs below 5.5. In addition, caproate eliminated Fol conidia completely at pHs 5.5 and 5.0 and suppressed Fol growth even at a low temperature (15 °C). Furthermore, cocopeat medium amended with caproate eliminated Fol conidia completely within 6 days. These results suggest that caproate is one of the key disinfestation factors in ethanol-based ASD and that the direct application of caproate to soil could be a promising strategy for rapid and stable soil disinfestation. Full article

(This article belongs to the Special Issue Anaerobic Soil Disinfestation: A Tool for Non-Fumigant-Based Integrated Soil-Borne Disease and Pest Management)

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13 pages, 3411 KiB

Open AccessEditor’s ChoiceArticle

Improving Soil Fertility and Wheat Yield by Tillage and Nitrogen Management in Winter Wheat–Summer Maize Cropping System

by Haixing Cui, Yongli Luo, Chunhui Li, Yonglan Chang, Min Jin, Yong Li and Zhenlin Wang

Agronomy 2023, 13(3), 740; https://doi.org/10.3390/agronomy13030740 - 1 Mar 2023

Cited by 7 | Viewed by 2491

Abstract

Soil degradation and high environmental costs impede agricultural production in North China. A 6-year field experiment was conducted to determine the effects of tillage practice and nitrogen application rate on changes in soil fertility and wheat yield. Four tillage systems (rotary tillage without [...] Read more.

Soil degradation and high environmental costs impede agricultural production in North China. A 6-year field experiment was conducted to determine the effects of tillage practice and nitrogen application rate on changes in soil fertility and wheat yield. Four tillage systems (rotary tillage without maize straw return through 6 years, RT; rotary tillage with maize straw return through 6 years, RS; deep tillage with maize straw return through 6 years, DS; and rotary tillage through 2 years followed by deep tillage next year with maize straw applied for two cycles, RS/DS) and three N levels (HN, 300 kg N ha⁻¹, refers to traditional farming practice; MN, 0.75 × HN, 225 kg N ha⁻¹, to recommended N rate; and LN, 0.5 × HN, 150 kg N ha⁻¹, to reduced N rate) were tested. The soil organic carbon, labile organic carbon, inorganic N, available phosphorus, and available potassium under straw return treatments were significantly higher than RT in the 0–30 cm soil layer (p < 0.05). The microbial diversity, invertase, urease, and alkaline phosphatase activities also increased when maize straw was returned. Tillage practices could distribute maize straw in different depths of the soil and then affect soil nutrients, enzyme activity, and microbial diversity. The RS treatment presented the greatest effects in the 0–10 cm layer, while more significant impacts were observed in DS and RS/DS treatments at the 10–30 cm depths. The levels of soil nutrients and enzyme activity increased with an increased N rate. Compared to that under LN, wheat yields increased under HN and MN treatments, whereas there were no significant differences between HN and MN (p > 0.05). An increasing tendency of grain yield was observed in DS and RS/DS, while conversely so in RS. RS/DS had lower farm costs than DS during the study duration. Thus, RS/DS at 225 kg N ha⁻¹ is the best method for improving soil fertility and wheat yield. Full article

(This article belongs to the Special Issue Coupled with Optimal Resource Allocation and Efficient Cropping Patterns for Sustainable Agriculture)

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13 pages, 1295 KiB

Open AccessEditor’s ChoiceArticle

Plant Composition and Feed Value of First Cut Permanent Meadows

by Aldo Dal Prà, Roberto Davolio, Alessandra Immovilli, Andrea Burato and Domenico Ronga

Agronomy 2023, 13(3), 681; https://doi.org/10.3390/agronomy13030681 - 26 Feb 2023

Cited by 5 | Viewed by 2409

Abstract

Permanent grasslands represent the main terrestrial ecosystem and serve as an important global reservoir of biodiversity, providing a wide range of benefits to humans and ecosystems. The effects of environment on permanent meadows (in our survey, they were centuries-old meadows that had not [...] Read more.

Permanent grasslands represent the main terrestrial ecosystem and serve as an important global reservoir of biodiversity, providing a wide range of benefits to humans and ecosystems. The effects of environment on permanent meadows (in our survey, they were centuries-old meadows that had not been plowed, mowed, or fertilized with manure) production have been adequately investigated in literature. However, plant species composition impact on potential feed value of first cut has still to be understood, in particular regarding different agronomic management. Our field trial was carried out in five farms, in a territory involved in the value chain of the Parmigiano Reggiano PDO (Val d’Enza, Northern Italy), over a two-year period (2017–2018). Differences in botanical composition, biomass, and Pastoral Value index (PV), which synthesizes grassland yield and nutritional parameters, were investigated in depth. The herbage dry matter (DM) yield was affected by year, farm, and their interaction factors. Its highest value across the two years was recorded in farm 5 (11.7 tons of DM ha⁻¹), which applied the highest rate of nitrogen fertilization. The botanical composition of the first cut has favored the presence of both Poaceae and ‘other species’ (each one around 40 plants per transect) compared to Fabaceae (seven plants per transect). However, higher numbers of Fabaceae plants (13 and 10) plausibly determined increases in PV in farms 3 and 5 (56.4 and 58.7, respectively). Although differences were observed among the most important nutritional parameters of grassland (crude protein, digestible and undigested neutral detergent fiber contents), suitable net energy for lactation (NE_L) values for feeding lactating cows were always recorded during the two years of survey. The present study provides a contribution of knowledge on how the botanical composition of permanent meadows may affect their potential nutritive value as fresh herbage for feeding dairy cows. Considering these results, the agronomic management should seek a level of plant biodiversity that at the same time might guarantee satisfactory yield and feed value, also in a context of climate change. Full article

(This article belongs to the Special Issue Sustainable Management of Herbaceous Field Crops)

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20 pages, 797 KiB

Open AccessEditor’s ChoiceArticle

QTL Analysis of Yield and End-Use Quality Traits in Texas Hard Red Winter Wheat

by Mehmet Dogan, Zhen Wang, Mustafa Cerit, Jorge L. Valenzuela-Antelo, Smit Dhakal, Chenggen Chu, Qingwu Xue, Amir M. H. Ibrahim, Jackie C. Rudd, Amy Bernardo, Paul St. Amand, Guihua Bai, Hongbin Zhang and Shuyu Liu

Agronomy 2023, 13(3), 689; https://doi.org/10.3390/agronomy13030689 - 26 Feb 2023

Cited by 3 | Viewed by 2467

Abstract

Genetic dissection of complex traits by quantitative trait locus (QTL) analysis permits the understanding of the genotypic effects of QTL, interactions between QTLs, and QTL-by-environment interactions in wheat. This study aimed to identify the QTL linked to yield, its components, end-use quality traits [...] Read more.

Genetic dissection of complex traits by quantitative trait locus (QTL) analysis permits the understanding of the genotypic effects of QTL, interactions between QTLs, and QTL-by-environment interactions in wheat. This study aimed to identify the QTL linked to yield, its components, end-use quality traits including kernel, flour, and dough rheology, and related agronomic traits under dryland and irrigated conditions. A mapping population of 179 F_2:6 recombinant inbred lines (RILs) derived from ‘TAM 111’/‘TX05A001822’ was evaluated for these traits to investigate their genetic stability and phenotypic plasticity using 2658 single nucleotide polymorphisms (SNPs) with 35 linkage groups. Traits associated with chromosome regions were detected for individual and across-environment QTL by inclusive composite interval mapping. A total of 30 QTL regions were identified, including 14 consistent QTLs mapped on 11 chromosomes and six pleiotropic QTLs mapped on 5 chromosomes. Three consistent QTLs in chromosomes 1A, 3B, and 6D might be novel. Three major QTLs with both consistent and pleiotropic effects were co-localized with known genes. The first QTL for dough mixing properties was physically clustered around Glu-D1 and had an phenotypic variation explained (PVE) up to 31.3%. The second QTL for kernel-related traits was physically close to the TaCWI-4A (cell wall invertase) gene, which influences the thousand kernel weight, heading date, and harvest index, with a PVE of up to 12.3%. The third QTL, which was colocalized with the TaCWI-5D gene for kernel traits, was identified with a PVE of 6.7%. Epistasis was also detected, but major QTLs were not involved in significant epistasis or interactions with environmental effects. The current study provided new information that is useful for enhanced wheat breeding, which will benefit from the deployment of the favorable alleles for end-use quality, yield, and other agronomic traits in wheat-breeding programs through marker-assisted selection. Full article

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

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17 pages, 2937 KiB

Open AccessEditor’s ChoiceArticle

Can Basic Soil Quality Indicators and Topography Explain the Spatial Variability in Agricultural Fields Observed from Drone Orthomosaics?

by Roope Näsi, Hannu Mikkola, Eija Honkavaara, Niko Koivumäki, Raquel A. Oliveira, Pirjo Peltonen-Sainio, Niila-Sakari Keijälä, Mikael Änäkkälä, Lauri Arkkola and Laura Alakukku

Agronomy 2023, 13(3), 669; https://doi.org/10.3390/agronomy13030669 - 25 Feb 2023

Cited by 7 | Viewed by 2381

Abstract

Crop growth is often uneven within an agricultural parcel, even if it has been managed evenly. Aerial images are often used to determine the presence of vegetation and its spatial variability in field parcels. However, the reasons for this uneven growth have been [...] Read more.

Crop growth is often uneven within an agricultural parcel, even if it has been managed evenly. Aerial images are often used to determine the presence of vegetation and its spatial variability in field parcels. However, the reasons for this uneven growth have been less studied, and they might be connected to variations in topography, as well as soil properties and quality. In this study, we evaluated the relationship between drone image data and field and soil quality indicators. In total, 27 multispectral and RGB drone image datasets were collected from four real farm fields in 2016–2020. We analyzed 13 basic soil quality indicators, including penetrometer resistance in top- and subsoil, soil texture (clay, silt, fine sand, and sand content), soil organic carbon (SOC) content, clay/SOC ratio, and soil quality assessment parameters (topsoil biological indicators, subsoil macroporosity, compacted layers in the soil profile, topsoil structure, and subsoil structure). Furthermore, a topography variable describing water flow was used as an indicator. Firstly, we evaluated single pixel-wise linear correlations between the drone datasets and soil/field-related parameters. Correlations varied between datasets and, in the best case, were 0.8. Next, we trained and tested multiparameter non-linear models (random forest algorithm) using all 14 soil-related parameters as features to explain the multispectral (NIR band) and RGB (green band) reflectance values of each drone dataset. The results showed that the soil/field indicators could effectively explain the spatial variability in the drone images in most cases (R² > 0.5), especially for annual crops, and in the best case, the R² value was 0.95. The most important field/soil features for explaining the variability in drone images varied between fields and imaging times. However, it was found that basic soil quality indicators and topography variables could explain the variability observed in the drone orthomosaics in certain conditions. This knowledge about soil quality indicators causing within-field variation could be utilized when planning cultivation operations or evaluating the value of a field parcel. Full article

(This article belongs to the Special Issue Application of Image Processing in Agriculture)

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17 pages, 3444 KiB

Open AccessEditor’s ChoiceArticle

Estimation of Chlorophyll Content in Soybean Crop at Different Growth Stages Based on Optimal Spectral Index

by Hongzhao Shi, Jinjin Guo, Jiaqi An, Zijun Tang, Xin Wang, Wangyang Li, Xiao Zhao, Lin Jin, Youzhen Xiang, Zhijun Li and Fucang Zhang

Agronomy 2023, 13(3), 663; https://doi.org/10.3390/agronomy13030663 - 24 Feb 2023

Cited by 34 | Viewed by 5561

Abstract

Chlorophyll is an important component of crop photosynthesis as it is necessary for the material exchange between crops and the atmosphere. The amount of chlorophyll present reflects the growth and health status of crops. Spectral technology is a feasible method for obtaining crop [...] Read more.

Chlorophyll is an important component of crop photosynthesis as it is necessary for the material exchange between crops and the atmosphere. The amount of chlorophyll present reflects the growth and health status of crops. Spectral technology is a feasible method for obtaining crop chlorophyll content. The first-order differential spectral index contains sufficient spectral information related to the chlorophyll content and has a high chlorophyll prediction ability. Therefore, in this study, the hyperspectral index data and chlorophyll content of soybean canopy leaves at different growth stages were obtained. The first-order differential transformation of soybean canopy hyperspectral reflectance data was performed, and five indices, highly correlated with soybean chlorophyll content at each growth stage, were selected as the optimal spectral index input. Four groups of model input variables were divided according to the following four growth stages: four-node (V4), full-bloom (R2), full-fruit (R4), and seed-filling stage (R6). Three machine learning methods, support vector machine (SVM), random forest (RF), and back propagation neural network (BPNN) were used to establish an inversion model of chlorophyll content at different soybean growth stages. The model was then verified. The results showed that the correlation coefficient between the optimal spectral index and chlorophyll content of soybean was above 0.5, the R2 period correlation coefficient was above 0.7, and the R4 period correlation coefficient was above 0.8. The optimal estimation model of soybean and chlorophyll content is established through the combination of the first-order differential spectral index and RF during the R4 period. The optimal estimation model validation set determination coefficient (R²) was 0.854, the root mean square error (RMSE) was 2.627, and the mean relative error (MRE) was 4.669, demonstrating high model accuracy. The results of this study can provide a theoretical basis for monitoring the growth and health of soybean crops at different growth stages. Full article

(This article belongs to the Special Issue Recent Advances in Crop Modelling)

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30 pages, 2693 KiB

Open AccessEditor’s ChoiceArticle

Framework for Assessing Collective Irrigation Systems Resilience to Climate Change—The Maiorga Case Study

by Rita Esteves, Maria João Calejo, João Rolim, José Luís Teixeira and Maria Rosário Cameira

Agronomy 2023, 13(3), 661; https://doi.org/10.3390/agronomy13030661 - 24 Feb 2023

Cited by 4 | Viewed by 1808

Abstract

In order to increase water productivity at the Collective Irrigation System (CIS) level it is crucial to adapt the existing irrigation infrastructure, enhancing water intake at the source, as well as its transport and delivery efficiency. Rehabilitation may involve structural changes and thus, [...] Read more.

In order to increase water productivity at the Collective Irrigation System (CIS) level it is crucial to adapt the existing irrigation infrastructure, enhancing water intake at the source, as well as its transport and delivery efficiency. Rehabilitation may involve structural changes and thus, a large capital investment. This investment should be proportionate to the increase in climate resilience associated to different rehabilitation alternatives. A methodology framework was developed to evaluate CIS resilience to climate change considering different rehabilitation alternatives. The assessed components were: (i) crop production systems; (ii) on-farm irrigation systems; and (iii) project rehabilitation alternatives for the conveyance and distribution of the irrigation water from the source to the farmer fields. This framework was applied to the Maiorga CIS, in central Portugal, to test the methodology performance in assessing the impacts of climate change on the supply-demand balance of the proposed rehabilitation alternatives and to evaluate their climate resilience, for the representative concentration pathways, RCP4.5 and RCP8.5, and two time periods, 2041–2070 and 2071–2100. For each scenario, period, and rehabilitation alternative, irrigation requirements at the source (demand) and stream flows (supply) were computed and the supply-demand balance was performed. Projected increases in irrigation water demand varied between 5.5% for RCP4.5/2071–2100 and 35.7% for RCP8.5/2071–2100. For RCP4.5, 11% (2050) and 9% (2080) reductions in irrigation water supply were projected, while for RCP8.5 the reduction ranges between 13% (2050) and 30% (2080). The proposed framework determined that the rehabilitation alternatives considering just one type of water source, without flow regularization and with open channel distribution to the farmer’s field, have proved to be unviable due to low resilience to climate change. Full article

(This article belongs to the Special Issue Improving Agricultural Water Productivity to Ensure Food Security under Changing Environments)

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17 pages, 837 KiB

Open AccessEditor’s ChoiceArticle

Sustainable Agriculture: Rare-Actinomycetes to the Rescue

by Oghoye P. Oyedoh, Wei Yang, Dharumadurai Dhanasekaran, Gustavo Santoyo, Bernard R. Glick and Olubukola O. Babalola

Agronomy 2023, 13(3), 666; https://doi.org/10.3390/agronomy13030666 - 24 Feb 2023

Cited by 11 | Viewed by 2975

Abstract

The failure of sustainable and agricultural intensifications in saving the ecosystem/public health has caused a paradigm shift to microbiome resource engineering through sustainable approaches. As agricultural intensification systems prioritize synthetic input applications over environmental health, sustainable intensification fails to define the end point [...] Read more.

The failure of sustainable and agricultural intensifications in saving the ecosystem/public health has caused a paradigm shift to microbiome resource engineering through sustainable approaches. As agricultural intensification systems prioritize synthetic input applications over environmental health, sustainable intensification fails to define the end point of intensification, giving room for the application of “intensification” over “sustainability” to suit farmers’ needs. However, sustainable agricultural practices through microbiome resource services have been well harnessed and appreciated for their significant role in plant health and disease management due to their ability to secret agroactive metabolites with notable functionalities in a cooperative manner or as bioinoculants. The complexity of a cooperative microbiome and the uncontrollable nature of its numerous influencing parameters as well as the non-specificity associated with bioinoculant application, results in the direct utilization of agroactive compounds to obtain greater preventive efficiency. In this regard, the known bacterial trove has been seriously ransacked, yet there exists an inexhaustible bank of unknown compounds, which are conserved in Actinomycetes. However, the rare Actinomycetes group has received less attention than other plant growth-promoting bacteria; thus, the possibility exists that the Actinomycetes may encode novel useful metabolites. To unravel the possible uses of these metabolites for phytoprotection, smart culture-based techniques and genometabolomics technology have been applied. Hence the aim of this review is to express the sustainable nature of agro-antibiotics or biopesticide from these bacterial resources for the resolution of phytopathogenic havoc that reduces crop productivity. Full article

(This article belongs to the Special Issue Biotechnology of Microorganisms in the Agriculture Environment)

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17 pages, 1470 KiB

Open AccessEditor’s ChoiceArticle

Economic Impact of the Persea Mite in Spanish Avocado Crops

by Eduardo Torres, Carlos Álvarez-Acosta, Modesto del Pino, María Eva Wong, Juan Ramón Boyero, Estrella Hernández-Suárez and José Miguel Vela

Agronomy 2023, 13(3), 668; https://doi.org/10.3390/agronomy13030668 - 24 Feb 2023

Cited by 4 | Viewed by 1821

Abstract

The Persea mite, Oligonychus perseae Tuttle, Baker & Abbatiello (Acari: Tetranychidae), is an economically important foliar pest of avocados in Spain. The effects of this mite on the foliar damage, production losses and economic impact were assessed in two avocado, cv. Hass, orchards [...] Read more.

The Persea mite, Oligonychus perseae Tuttle, Baker & Abbatiello (Acari: Tetranychidae), is an economically important foliar pest of avocados in Spain. The effects of this mite on the foliar damage, production losses and economic impact were assessed in two avocado, cv. Hass, orchards located in the main growing areas of Spain (Northern Tenerife and Málaga) for 3 and 5 consecutive years, respectively. The economic injury level (EIL) for the optimization of the use of acaricides to control this mite was also established, considering three spraying strategies: (i) mite-free treatment (<50 mites per leaf), (ii) conventional treatment (50–150 mites per leaf), and (iii) control treatment (the absence of spraying). Persea mite populations were sampled fortnightly and foliar damage was estimated. At the end of each season, fruits were harvested, weighed and production losses were quantified. The cumulate mite-days (CMDs) had a significant effect on the percentage of leaf area damaged (PLAD) and yield reduction. High numbers of the Persea mite caused extensive damage to leaves, so a loss in tree yield was evident. However, for the middle population level, there was no evidence of yield losses. The quantitative EIL was estimated at a PLAD of 17%, equivalent to a CMDs of 178 mites per leaf, which is the amount of damage that should not be exceeded. In Northern Tenerife, with a mild climate, the Persea mite can reach significant populations that are maintained throughout the months. In avocado orchards in Málaga, the summer is hotter and drier, so the presence of the mite exists for a shorter duration in the seasons, with less damage to the leaves. In Tenerife, yield loss can be compensated by chemical treatments that permit pest control. Full article

(This article belongs to the Special Issue Sustainability of Tropical Crops in a Changing Environment)

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18 pages, 638 KiB

Open AccessEditor’s ChoiceArticle

Nutrient and Nutraceutical Quality of Rocket as a Function of Greenhouse Cover Film, Nitrogen Dose and Biostimulant Application

by Roberta Paradiso, Ida Di Mola, Eugenio Cozzolino, Lucia Ottaiano, Christophe El-Nakhel, Youssef Rouphael and Mauro Mori

Agronomy 2023, 13(3), 638; https://doi.org/10.3390/agronomy13030638 - 23 Feb 2023

Cited by 4 | Viewed by 1432

Abstract

The nutrient and nutraceutical quality of greenhouse wild rocket is strongly influenced by the light environment and nitrogen fertilization. We investigated the effects of two cover materials, a diffuse light film (Film1) and a traditional clear film (Film2), and three nitrogen regimes, no [...] Read more.

The nutrient and nutraceutical quality of greenhouse wild rocket is strongly influenced by the light environment and nitrogen fertilization. We investigated the effects of two cover materials, a diffuse light film (Film1) and a traditional clear film (Film2), and three nitrogen regimes, no N supply (N0) and sub-optimal (N1) and optimal (N2) doses, also in combination with a biostimulant (Stimolo Mo), on the mineral composition, antioxidant properties and chlorophyll and carotenoid content of rocket plants grown in the autumn–spring cycle. The leaf concentration of most of the minerals was higher under Film1 compared to Film2. In general, K, Ca, Mg and Na were higher, and S was lower in the presence of N supply, and the addition of the biostimulant promoted the mineral uptake. Under Film1, the hydrophilic antioxidant activity (HAA) was higher in some harvests, and the ABTS antioxidant activity (ABTS AA) in the first one, while always lower afterward, than under Film2. Nitrogen fertilization did not affect the antioxidant activity, while it reduced the content of total phenols and ascorbic acid. The biostimulant application increased ABTS AA at the optimal N dose and reduced total phenols in unfertilized plants. Both the diffuse light and the N supply inhibited the synthesis of ascorbic acid, while N fertilization and the biostimulant promoted the synthesis of chlorophylls. The experimental treatments exerted variable effects over time and significant interactions with the harvest period were found for many of the investigated parameters. Full article

(This article belongs to the Special Issue Integrated Management Tactics for Resilient and Sustainable Vegetable Crops Production)

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17 pages, 12498 KiB

Open AccessEditor’s ChoiceArticle

Lidar-Based 3D Obstacle Detection Using Focal Voxel R-CNN for Farmland Environment

by Jia Qin, Ruizhi Sun, Kun Zhou, Yuanyuan Xu, Banghao Lin, Lili Yang, Zhibo Chen, Long Wen and Caicong Wu

Agronomy 2023, 13(3), 650; https://doi.org/10.3390/agronomy13030650 - 23 Feb 2023

Cited by 9 | Viewed by 2345

Abstract

With advances in precision agriculture, autonomous agricultural machines can reduce human labor, optimize workflow, and increase productivity. Accurate and reliable obstacle-detection and avoidance systems are essential for ensuring the safety of automated agricultural machines. Existing LiDAR-based obstacle detection methods for the farmland environment [...] Read more.

With advances in precision agriculture, autonomous agricultural machines can reduce human labor, optimize workflow, and increase productivity. Accurate and reliable obstacle-detection and avoidance systems are essential for ensuring the safety of automated agricultural machines. Existing LiDAR-based obstacle detection methods for the farmland environment process the point clouds via manually designed features, which is time-consuming, labor-intensive, and weak in terms of generalization. In contrast, deep learning has a powerful ability to learn features autonomously. In this study, we attempted to apply deep learning in LiDAR-based 3D obstacle detection for the farmland environment. In terms of perception hardware, we established a data acquisition platform including LiDAR, a camera, and a GNSS/INS on the agricultural machine. In terms of perception method, considering the different agricultural conditions, we used our datasets to train an effective 3D obstacle detector, known as Focal Voxel R-CNN. We used focal sparse convolution to replace the original 3D sparse convolution because of its adaptable ability to extract effective features from sparse point cloud data. Specifically, a branch of submanifold sparse convolution was added to the upstream of the backbone convolution network; this adds weight to the foreground point and retains more valuable information. In comparison with Voxel R-CNN, the proposed Focal Voxel R-CNN significantly improves the detection performance for small objects, and the AP in the pedestrian class increased from 89.04% to 92.89%. The results show that our model obtains an mAP of 91.43%, which is 3.36% higher than the base model. The detection speed is 28.57 FPS, which is 4.18 FPS faster than the base model. The experiments show the effectiveness of our model, which can provide a more reliable obstacle detection model for autonomous agricultural machines. Full article

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

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15 pages, 1678 KiB

Open AccessEditor’s ChoiceArticle

Economic and Environmental Sustainability Assessment of an Innovative Organic Broccoli Production Pattern

by Alessandro Scuderi, Giuseppe Timpanaro, Ferdinando Branca and Mariarita Cammarata

Agronomy 2023, 13(3), 624; https://doi.org/10.3390/agronomy13030624 - 22 Feb 2023

Cited by 3 | Viewed by 2343

Abstract

Organic farming nowadays is held up as a model of sustainability; however, this is not always an economic advantage for farmers due to the reduced yields compared to the conventional regime. The aim of the study is therefore to provide an environmental and [...] Read more.

Organic farming nowadays is held up as a model of sustainability; however, this is not always an economic advantage for farmers due to the reduced yields compared to the conventional regime. The aim of the study is therefore to provide an environmental and economic analysis of the innovative organic model proposed by the Bresov project to assess its sustainability. The study is therefore based on a Life Cycle Assessment methodology and the economic evaluation, through the calculation of the gross income of innovative organic and conventional broccoli cultivation in Sicily. The impact categories analysed reported a 60–100% reduction in impact in the case of innovative organic compared to conventional. From an economic point of view, although there is a minimal reduction in yield in organic compared to conventional, there is an increase in production costs that translates into a reduction in the gross income of approximately 61%. These gaps are filled when the organic product is granted a premium price and thanks to aid from the Common Agricultural Policy. The innovative organic approach, characterised by new products and soil management methods, confirms it as an alternative to conventional. This approach contrasts with the mere substitution of synthetic products. Full article

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23 pages, 4659 KiB

Open AccessEditor’s ChoiceArticle

BMAE-Net: A Data-Driven Weather Prediction Network for Smart Agriculture

by Jian-Lei Kong, Xiao-Meng Fan, Xue-Bo Jin, Ting-Li Su, Yu-Ting Bai, Hui-Jun Ma and Min Zuo

Agronomy 2023, 13(3), 625; https://doi.org/10.3390/agronomy13030625 - 22 Feb 2023

Cited by 22 | Viewed by 3727

Abstract

Weather is an essential component of natural resources that affects agricultural production and plays a decisive role in deciding the type of agricultural production, planting structure, crop quality, etc. In field agriculture, medium- and long-term predictions of temperature and humidity are vital for [...] Read more.

Weather is an essential component of natural resources that affects agricultural production and plays a decisive role in deciding the type of agricultural production, planting structure, crop quality, etc. In field agriculture, medium- and long-term predictions of temperature and humidity are vital for guiding agricultural activities and improving crop yield and quality. However, existing intelligent models still have difficulties dealing with big weather data in predicting applications, such as striking a balance between prediction accuracy and learning efficiency. Therefore, a multi-head attention encoder-decoder neural network optimized via Bayesian inference strategy (BMAE-Net) is proposed herein to predict weather time series changes accurately. Firstly, we incorporate Bayesian inference into the gated recurrent unit to construct a Bayesian-gated recurrent units (Bayesian-GRU) module. Then, a multi-head attention mechanism is introduced to design the network structure of each Bayesian layer, improving the prediction applicability to time-length changes. Subsequently, an encoder-decoder framework with Bayesian hyperparameter optimization is designed to infer intrinsic relationships among big time-series data for high prediction accuracy. For example, the R-evaluation metrics for temperature prediction in the three locations are 0.9, 0.804, and 0.892, respectively, while the RMSE is reduced to 2.899, 3.011, and 1.476, as seen in Case 1 of the temperature data. Extensive experiments subsequently demonstrated that the proposed BMAE-Net has overperformed on three location weather datasets, which provides an effective solution for prediction applications in the smart agriculture system. Full article

(This article belongs to the Special Issue Recent Advances in Data-Driven Farming)

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17 pages, 7463 KiB

Open AccessEditor’s ChoiceArticle

Grassland Ecosystem Progress: A Review and Bibliometric Analysis Based on Research Publication over the Last Three Decades

by Xiaoyu Zhu, Jianhua Zheng, Yi An, Xiaoping Xin, Dawei Xu, Ruirui Yan, Lijun Xu, Beibei Shen and Lulu Hou

Agronomy 2023, 13(3), 614; https://doi.org/10.3390/agronomy13030614 - 21 Feb 2023

Cited by 12 | Viewed by 6169

Abstract

Understanding the grassland ecosystem is crucial for improving grassland ecosystem functions and services such as climate regulation, water and soil conservation, carbon sequestration, and biodiversity and gene pool maintenance. However, a systematic and comprehensive review of the relevant literature is still unclear and [...] Read more.

Understanding the grassland ecosystem is crucial for improving grassland ecosystem functions and services such as climate regulation, water and soil conservation, carbon sequestration, and biodiversity and gene pool maintenance. However, a systematic and comprehensive review of the relevant literature is still unclear and lacking. The VOSviewer software and cluster analysis were used to visually analyze and perform dimension reduction classification on the 27,778 studies related to grassland ecosystem research based on the Web of Science database. The number of publications targeting grassland ecosystem increased rapidly from 2006 to 2021. Ecology, agronomy, and environmental science were the most popular research categories, and the top journal sources were Remote Sensing, Journal of Ecology, and Ecology and Evolution. The leading publishing countries were the United States, China, and Germany. The top three institutions were the Chinese Academy of Sciences, the University of Chinese Academy of Sciences, and Colorado State University. Cooperation between different countries and institutions had increased. Keyword co-occurrence network analysis showed that Biodiversity, Vegetation and Conservation were the most popular study areas, grassland management, climate change, land use pattern, and ecosystem impact were the hot research topics. All studies could be divided into three categories by cluster analysis: grassland ecological characteristics including basic physicochemical properties, vegetation community characteristics, aboveground and belowground biomass, and soil structural quality of grassland; driving mechanisms that demonstrated effects of human activities and climate change on grassland ecosystem function; and grassland ecosystem services that focused the influences of different grassland management strategies on ecological services, animal welfare and human well-being. The three topic categories of reviewed studies were interrelated and consistent with each other, and the performances were progressive. This paper reviewed the trend evolution through keyword hotspots and analyzed the future research directions to provide an important reference for scientists to better respond to the balance of herbage and sustainable utilization of grassland and maintenance of ecological security. Full article

(This article belongs to the Special Issue Modeling and Monitoring of Grassland Ecosystem Productivity, Carbon Assimilation and Allocation)

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