Agronomy

25 pages, 3369 KB

Open AccessArticle

Effect of Biostimulants Containing Rhizobacteria on the Growth of Wheat, Barley, and Oilseed Rape Under Various Soil Moisture Conditions

by Arkadiusz Filipczak, Łukasz Sobiech, Agnieszka Wita, Roman Marecik, Wojciech Białas, Monika Grzanka, Robert Idziak and Piotr Szulc

Agronomy 2026, 16(3), 400; https://doi.org/10.3390/agronomy16030400 - 6 Feb 2026

Cited by 1 | Viewed by 1130

Abstract

Preparations containing appropriate microorganisms stimulate plant growth and are increasingly used to alleviate plant stress, including water deficit stress. Despite the growing interest in PGPR, little is known about the post-emergence efficacy of formulations based on native strains under water stress. In this [...] Read more.

Preparations containing appropriate microorganisms stimulate plant growth and are increasingly used to alleviate plant stress, including water deficit stress. Despite the growing interest in PGPR, little is known about the post-emergence efficacy of formulations based on native strains under water stress. In this study, we tested the post-emergence efficacy of preparations based on Bacillus velezensis_KT27 and Bacillus subtilis + Pseudomonas simiae + Bacillus velezensis_S103 at doses of half a liter and one liter × 200 L × ha⁻¹ in culture fluid or oil dispersion each at a final microbial cell concentration of 5 × 10⁸ (CFU/mL) for the tested strains. Our hypothesis was that the different biostimulants may positively affect plants’ tolerance to water stress. To this end, analyses of plant height, fresh weight, dry weight, chlorophyll, flavonol and anthocyanin content, and chlorophyll fluorescence were conducted under greenhouse conditions for winter wheat, winter barley, and winter oilseed rape. The preparations promoted the growth and water-stress tolerance of the selected plants, with effectiveness depending on strain, plant, dose, and formulation. B. velezensis_KT27 (0.5 L in oil dispersion) increased the dry weight of winter wheat by 17% (optimal) and 14% (water deficit stress) and of winter barley by 17% and 28%. Bacillus spp. + Pseudomonas spp. (0.5 L in oil dispersion) increased winter oilseed rape dry weight by 13% in both conditions. These findings highlight the potential of Bacillus spp. and Pseudomonas spp. for post-emergence biostimulation under variable soil levels of moisture. Full article

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

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24 pages, 9345 KB

Open AccessArticle

Influence of the Use of Double Roof with Increased Ventilation on the Development of Fungal Diseases in a Mediterranean Greenhouse

by María Ángeles Moreno-Teruel, Alejandro López-Martínez, Eugenio Ávalos-Sánchez, Francisco Domingo Molina-Aiz, Diego Luis Valera-Martínez, Kristoff Proost, Frederic Peilleron and Fátima Baptista

Agronomy 2026, 16(3), 399; https://doi.org/10.3390/agronomy16030399 - 6 Feb 2026

Cited by 1 | Viewed by 814

Abstract

Mediterranean greenhouses commonly rely on passive climate control techniques to reduce dependence on energy-intensive systems. This study was conducted in Almería (Spain) in a multi-span greenhouse divided into two sectors: a West sector equipped with a double-roof system using a pink sunlight spectrum [...] Read more.

Mediterranean greenhouses commonly rely on passive climate control techniques to reduce dependence on energy-intensive systems. This study was conducted in Almería (Spain) in a multi-span greenhouse divided into two sectors: a West sector equipped with a double-roof system using a pink sunlight spectrum photoconverter film combined with an increased natural ventilation surface, and an East control sector with standard ventilation and a calcium carbonate-whitened roof. The effects of this integrated passive climate management configuration on the development of naturally occurring fungal diseases were evaluated in tomato (Solanum lycopersicum L.), pepper (Capsicum annuum L.), and cucumber (Cucumis sativus L.). Powdery mildew (Leveillula taurica) and early blight (Alternaria linariae) were observed in tomato; powdery mildew in pepper; and downy mildew (Pseudoperonospora cubensis), powdery mildew (Podosphaera xanthii), and gummy stem blight (Stagonosporopsis spp.) in cucumber. Across crop cycles, the sector combining double roofing and enhanced ventilation consistently exhibited lower disease severity for powdery mildew, downy mildew, and gummy stem blight compared with the control sector. In contrast, early blight did not show a clear or consistent response to the greenhouse configuration. Overall, the results indicate that the combined use of a double-roof system with a sunlight spectrum photoconverter film and increased natural ventilation can contribute to improved microclimate regulation and reduced fungal disease pressure under Mediterranean greenhouse conditions. This integrated passive approach may therefore represent a useful complementary component of sustainable disease management strategies in protected horticulture. Full article

(This article belongs to the Special Issue Agricultural Innovation in Sustainable and Organic Vegetable Crops Production)

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7 pages, 173 KB

Open AccessEditorial

Recycling of Organic Wastes in Agriculture: Serving for Sustainable Agriculture

by Halyna Kominko and Grzegorz Izydorczyk

Agronomy 2026, 16(3), 398; https://doi.org/10.3390/agronomy16030398 - 6 Feb 2026

Cited by 1 | Viewed by 1521

Abstract

The transition toward sustainable agriculture is increasingly shaped by two converging pressures: the need to secure food production under climate and resource constraints and the imperative to reduce environmental burdens associated with linear “take–make–dispose” systems [...] Full article

(This article belongs to the Special Issue Recycling of Organic Wastes in Agriculture: Serving for Sustainable Agriculture)

14 pages, 2191 KB

Open AccessArticle

Molecular Mapping of a Stripe Rust Resistance Locus on Chromosome 4A in Wheat

by Xin Bai, Xue Li, Liujie Wang, Xiaojun Zhang, Tianling Cheng, Zhijian Chang, Juqing Jia and Xin Li

Agronomy 2026, 16(3), 397; https://doi.org/10.3390/agronomy16030397 - 6 Feb 2026

Viewed by 778

Abstract

Wheat is among the most important staple crops worldwide; however, its yield and quality are severely threatened by stripe rust caused by Puccinia striiformis f. sp. tritici (Pst). CH806 is a Thinopyrum intermedium-derived resistant breeding line developed in our laboratory [...] Read more.

Wheat is among the most important staple crops worldwide; however, its yield and quality are severely threatened by stripe rust caused by Puccinia striiformis f. sp. tritici (Pst). CH806 is a Thinopyrum intermedium-derived resistant breeding line developed in our laboratory that is highly resistant to the prevalent Chinese Pst races CYR32, CYR33, and CYR34 in field trials. A genetic population was developed by crossing CH806 with the susceptible cultivar Chuanmai 24. Phenotypic evaluation of the progeny under field conditions revealed segregation for stripe rust resistance in the F₂ generation. On the basis of the resistance phenotypes of the F₂ and F_2:3 populations, homozygous resistant and homozygous susceptible F₂ individuals were selected to construct resistant and susceptible DNA bulks, respectively, for genotyping using the Wheat 120K SNP array. Bulked segregant analysis indicated that the most significant SNPs were predominantly clustered on chromosome 4A. Subsequently, publicly available simple sequence repeat (SSR) markers on chromosome 4A and newly developed SSR markers within the candidate region that were enriched for polymorphic SNPs were used for linkage analysis. The resistance locus, temporarily designated YrCH806, was mapped to an interval flanked by markers Xwmc48/Xwmc89 and SSR4A-60, with genetic distances of 4.4 cM and 2.5 cM, respectively, corresponding to a physical position of 515.8–574.7 Mb on the wheat reference genome. The closest flanking marker, SSR4A-60, was successfully converted into a Kompetitive Allele-Specific PCR (KASP) marker. This high-throughput marker was subsequently utilized to screen a panel of wheat germplasms for the distribution of YrCH806. This study provides a novel resistance source and associated molecular markers for improving stripe rust resistance in wheat breeding programs. Full article

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

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21 pages, 2659 KB

Open AccessArticle

Legume Intercropping Can Boost Early-Stage Carob Plantation Establishment

by Sofia Matsi, Stella Pempetsiou, Emmanouela Christofi, Irene Nikolaou and Dimitrios Sarris

Agronomy 2026, 16(3), 396; https://doi.org/10.3390/agronomy16030396 - 6 Feb 2026

Viewed by 943

Abstract

Tree intercropping systems with leguminous cover crops and aromatic plants may provide sustainable yields, which could be improved by beneficial microbes (BMs) and zeolite, while their effects on young tree growth remain unclear. We tested whether such systems enhance early growth in young [...] Read more.

Tree intercropping systems with leguminous cover crops and aromatic plants may provide sustainable yields, which could be improved by beneficial microbes (BMs) and zeolite, while their effects on young tree growth remain unclear. We tested whether such systems enhance early growth in young carob trees compared with conservation tillage (TLG) trees growing under rainfed semi-arid conditions. Intercropping included carobs with (i) Lathyrus ochrus, Trifolium squarrosum, and Lens culinaris combined (CC-System), (ii) Thymbra capitata planted between legumes (CCT-System), and soil amended with (iii) BM (Micosat-F-Olivo) and zeolite. All systems outperformed TLG in annual tree height increase with the CC-System excelling (TLG +13%, CC-System +42%; p < 0.05). The CC-System also significantly outpaced TLG in stem thickening (TLG 62%, CC-System 167%; p < 0.01) with BM and/or zeolite also appearing as beneficial. Improved performance was related to significantly higher dry season soil moisture, while a high L. ochrus abundance reduced thyme survival (p < 0.01). The CCT-System was also found to be less capable in weed suppression during a wet year. Thus, applying our legume intercropping system (with BM/zeolite) represents an effective nature-based solution for enhancing young carob tree growth under rainfed conditions, while adding thyme may somewhat trade productivity for biodiversity and associated ecosystem services. Full article

(This article belongs to the Special Issue Promoting Intercropping Systems in Sustainable Agriculture—2nd Edition)

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16 pages, 2096 KB

Open AccessArticle

Enhancing Carbon–Nitrogen Metabolism and Productivity of Smooth Bromegrass Through Alfalfa Incorporation and Nitrogen Application

by Feng Hao, Jiabing Yu, Tiefeng Yu, Haibo An and Kai Gao

Agronomy 2026, 16(3), 395; https://doi.org/10.3390/agronomy16030395 - 6 Feb 2026

Cited by 1 | Viewed by 794

Abstract

The incorporation of alfalfa into grass systems reduces reliance on nitrogen fertilizer application. Over two consecutive years, we investigated the regulation of carbon and nitrogen metabolism in grasses and productivity enhancement under four nitrogen application rates (0, 105, 210, and 315 kg·ha⁻¹ [...] Read more.

The incorporation of alfalfa into grass systems reduces reliance on nitrogen fertilizer application. Over two consecutive years, we investigated the regulation of carbon and nitrogen metabolism in grasses and productivity enhancement under four nitrogen application rates (0, 105, 210, and 315 kg·ha⁻¹) and five alfalfa incorporation levels (0%, 10%, 20%, 30%, and 40%); incorporation (%) refers strictly to seeding proportion (% of the monoculture seeding rate). Within the range of 20–30% alfalfa incorporation and 105–210 kg·ha⁻¹ nitrogen application, key physiological and biochemical parameters, except the net photosynthetic rate (P_n), reached their peak values compared to the N0A0 (no nitrogen and no alfalfa) treatment. Transpiration rate (T_r), intercellular CO₂ concentration (C_i), and stomatal conductance (G_s) increased by 43.64%, 40%, and 48.09%, respectively. P_n peaked under the N2A0 treatment (210 kg·ha⁻¹ nitrogen application and no alfalfa), increased by 65.63%. Nitrate reductase (NR), glutamine synthetase (GS), and ribulose-1,5-bisphosphate carboxylase (RuBisCO) activity increased by 154.60%, 112.39%, and 199.19%, respectively. Total sugar (TS) and protein production (YCP) increased by 122.22% and 145.17%, respectively. The entropy-weighted TOPSIS evaluation based on multi-objective assessment showed that the combination of 20% alfalfa incorporation with 105 kg N·ha⁻¹ application is an efficient model for enhancing forage productivity in the Horqin Sandy Land. Full article

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

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6 pages, 174 KB

Open AccessEditorial

Intelligent Information Systems for Agriculture Based onVision Technology

by Arjun Neupane, Tej Bahadur Shahi and Richard Koech

Agronomy 2026, 16(3), 394; https://doi.org/10.3390/agronomy16030394 - 6 Feb 2026

Viewed by 1138

Abstract

The traditional approach to agriculture is changing due to rapid advances in technologies such as unmanned aerial vehicles (UAVs), proximal and remote sensors, and the Internet of Things (IoT) [...] Full article

(This article belongs to the Special Issue Intelligent Information System for Agriculture Based on Vision Technology)

12 pages, 2308 KB

Open AccessArticle

Fine-Mapping and Candidate Gene Analysis of qAT3 for Alkalinity Tolerance in Rice

by Lei Lei, Jinsong Zhou, Guohua Ding, Liangzi Cao, Yu Luo, Lei Chen, Yang Ren, Jiangxu Wang, Kai Liu, Qingjun Lei, Yusong Miao, Tingting Xie, Wei Zheng and Shichen Sun

Agronomy 2026, 16(3), 393; https://doi.org/10.3390/agronomy16030393 - 6 Feb 2026

Viewed by 725

Abstract

Salinity–alkalinity stress is one of the major abiotic stresses that limit rice production in the world. The salinity–alkalinity tolerance of rice at the germination stage has a direct effect on the survival and final yield of seedlings in direct sowing. However, there are [...] Read more.

Salinity–alkalinity stress is one of the major abiotic stresses that limit rice production in the world. The salinity–alkalinity tolerance of rice at the germination stage has a direct effect on the survival and final yield of seedlings in direct sowing. However, there are few reports of quantitative trait locus (QTL) mapping and mapping-based cloning of alkaline tolerance at the bud burst stage. Here, new alkaline tolerance loci were constructed for F_2:3 and BC₃F₄ by using IR36 and Long-Dao124 (LD124) rice varieties with significant differences in alkaline tolerance. Through linkage analysis and a fine-mapping strategy, qAT3 was identified as the major QTL for alkaline tolerance at the bud burst stage, which could explain 14.79% of the phenotypic variation on average. Then the interval was fine-mapped to 110.265 kb, and the candidate gene LOC_Os03g03150 was predicted by quantitative real-time polymerase chain reaction (qRT-PCR) analysis and sequencing analysis. This provides a key theory for the molecular breeding of alkali-tolerant genes and the study of the molecular mechanism of alkali tolerance in LD124. Full article

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

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28 pages, 2701 KB

Open AccessReview

Mycofumigation with Beneficial Yeasts: An Eco-Friendly Approach Against Postharvest Pathogens

by Rochelle C. Olana, Dulanjalee Lakmali Harishchandra, Sukanya Haituk, Christian Joseph R. Cumagun and Ratchadawan Cheewangkoon

Agronomy 2026, 16(3), 392; https://doi.org/10.3390/agronomy16030392 - 6 Feb 2026

Cited by 2 | Viewed by 1721

Abstract

Postharvest fungal diseases result in substantial crop losses, with disease severity often exacerbated by inadequate handling practices and unfavorable environmental conditions. Conventional fungicides have been widely employed; however, the frequent use has led to serious challenges, including the emergence of fungicide resistance and [...] Read more.

Postharvest fungal diseases result in substantial crop losses, with disease severity often exacerbated by inadequate handling practices and unfavorable environmental conditions. Conventional fungicides have been widely employed; however, the frequent use has led to serious challenges, including the emergence of fungicide resistance and ecological concerns. Mycofumigation is a biocontrol approach that utilizes antimicrobial volatile organic compounds (VOCs) produced by beneficial fungi, including yeasts, offering a promising, eco-friendly alternative. Fungal pathogens can be controlled even without direct contact between the biocontrol agent and the crop, making it suitable and feasible for postharvest applications. The review examines how yeast VOCs exert their antifungal effects at structural and genetic levels, categorizes the major classes of VOCs with demonstrated efficacy, and evaluates their application strategies, including both single-compound and composite formulations. Additionally, practical implementation of yeast-based mycofumigants was discussed, highlighting successful applications against important postharvest pathogens under controlled conditions. Full article

(This article belongs to the Special Issue Advancing Sustainable Agriculture: Biopesticides and the Biological Control for Pest Management)

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15 pages, 455 KB

Open AccessEditor’s ChoiceSystematic Review

Mushroom Spawn and Its Effects on Mushroom Growth and Development: A Systematic Review

by Hong Tham Dong, Delwar Akbar, Yujuan Li and Cheng-Yuan Xu

Agronomy 2026, 16(3), 391; https://doi.org/10.3390/agronomy16030391 - 6 Feb 2026

Cited by 4 | Viewed by 5486

Abstract

Mushrooms are among the most important indoor-grown horticultural cash crops. Recent increases in consumption are driven by shifts toward healthier diets and a growing vegan population. Mushroom spawn is one of key factors that influence consistency, quality, and the yield of mushrooms. Many [...] Read more.

Mushrooms are among the most important indoor-grown horticultural cash crops. Recent increases in consumption are driven by shifts toward healthier diets and a growing vegan population. Mushroom spawn is one of key factors that influence consistency, quality, and the yield of mushrooms. Many studies of mushroom spawn have been published but the performance of mushroom spawn under different conditions has not been summarised. Comprehensive literature searches were conducted to identify the effects of spawn on biological efficiency, and 40 publications were included in this systematic review. Most of the studies were conducted on oyster mushroom (Pleurotus spp.), and grain spawn was popularly used when studying mushroom. Spawn type and rate were demonstrated to affect mycelium growth, which directly influenced mushroom yield. The use of liquid spawn increased mycelium growth, reduced spawn running time, and enhanced mushroom yield. Most studied cases used spawn rates of 3–5% and the biological yield efficiency (BE) of Pleurotus spp. was varied from 5.18 to 173.38% if using grain spawn. The BEs of Hericicum erinacea and Volvariella volvacea inoculated with grain spawn were lower at 22.3–44.4% and 9.42–15.79%, respectively. Recently developed stick and block spawn types seem to be promising spawn with a BE ranging from 68.65 to 70.94%. Full article

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

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23 pages, 6060 KB

Open AccessArticle

YOLO-CSB: A Model for Real-Time and Accurate Detection and Localization of Occluded Apples in Complex Orchard Environments

by Yunxiao Pan, Yiwen Chen, Xing Tong, Mengfei Liu, Anxiang Huang, Meng Zhou and Yaohua Hu

Agronomy 2026, 16(3), 390; https://doi.org/10.3390/agronomy16030390 - 5 Feb 2026

Cited by 7 | Viewed by 1527

Abstract

Apples are cultivated over a large global area with high yields, and efficient robotic harvesting requires accurate detection and localization, particularly in complex orchard environments where occlusion by leaves and fruits poses substantial challenges. To address this, we proposed a YOLO-CSB model-based method [...] Read more.

Apples are cultivated over a large global area with high yields, and efficient robotic harvesting requires accurate detection and localization, particularly in complex orchard environments where occlusion by leaves and fruits poses substantial challenges. To address this, we proposed a YOLO-CSB model-based method for apple detection and localization, designed to overcome occlusion and enhance the efficiency and accuracy of mechanized harvesting. Firstly, a comprehensive apple dataset was constructed, encompassing various lighting conditions and leaf obstructions, to train the model. Subsequently, the YOLO-CSB model, built upon YOLO11s, was developed with improvements including the integration of a lightweight CSFC Block to reconstruct the backbone, making the model more lightweight; the SEAM component is introduced to improve feature restoration in areas with occlusions, complemented by the efficient BiFPN approach to boost detection precision. Additionally, a 3D positioning technique integrating YOLO-CSB with an RGB-D camera is presented. Validation was conducted via ablation analyses, comparative tests, and 3D localization accuracy assessments in controlled laboratory and structured orchard settings, The YOLO-CSB model demonstrated effectiveness in apple target recognition and localization, with notable advantages under leaf and fruit occlusion conditions. Compared to the baseline YOLO11s model, YOLO-CSB improved mAP by 3.02% and reduced the parameter count by 3.19%. Against mainstream object detection models, YOLO-CSB exhibited significant advantages in detection accuracy and model size, achieving a mAP of 93.69%, precision of 88.82%, recall of 87.58%, and a parameter count of only 9.11 M. The detection accuracy in laboratory settings reached 100%, with average localization errors of 4.15 mm, 3.96 mm, and 4.02 mm in the X, Y, and Z directions, respectively. This method effectively addresses complex occlusion environments, enabling efficient detection and precise localization of apples, providing reliable technical support for mechanized harvesting. Full article

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

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26 pages, 1679 KB

Open AccessReview

Thermochemical Conversion of Food Waste into Biochar/Hydrochar for Soil Amendment: A Review

by Jiachen Qian, Shunfeng Jiang, Baoqiang Lv and Xiangyong Zheng

Agronomy 2026, 16(3), 389; https://doi.org/10.3390/agronomy16030389 - 5 Feb 2026

Cited by 6 | Viewed by 2018

Abstract

Current agriculture faces the challenge of producing sufficient food from diminishing land resources, due to deteriorating soil quality and accelerated population growth. Numerous studies have demonstrated that biochar/hydrochar can serve as efficient soil amendments by improving soil fertility and enhancing crop productivity. Various [...] Read more.

Current agriculture faces the challenge of producing sufficient food from diminishing land resources, due to deteriorating soil quality and accelerated population growth. Numerous studies have demonstrated that biochar/hydrochar can serve as efficient soil amendments by improving soil fertility and enhancing crop productivity. Various food wastes are promising raw materials for biochar/hydrochar production due to their abundant organic matter. Recently, thermochemical techniques such as pyrolysis, hydrothermal carbonization (HTC), and microwave-assisted pyrolysis (MAP) have been widely proposed for converting food waste into biochar/hydrochar for soil amendment. However, the composition of food waste is complex and the parameters for its thermal treatment are highly variable, leading to uncertainties in the performance of the derived biochar/hydrochar for soil applications. This study aims to establish a structure–activity relationship linking food waste carbonization technology, the properties of the obtained biochar/hydrochar, and its functions as a soil amendment. Furthermore, the detailed mechanisms by which biochar improves plant growth or poses potential ecological risks to agricultural land are discussed. This review is intended to provide a guideline for the large-scale application of food waste-derived char for soil amendment. Full article

(This article belongs to the Special Issue Biochar-Based Fertilizers for Resilient Agriculture)

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29 pages, 1906 KB

Open AccessReview

Enhancing Cereal Crop Tolerance to Low-Phosphorus Conditions Through Fertilisation Strategies: The Role of Silicon in Mitigating Phosphate Deficiency

by Ilona Kulus and Iwona Ciereszko

Agronomy 2026, 16(3), 388; https://doi.org/10.3390/agronomy16030388 - 5 Feb 2026

Cited by 3 | Viewed by 1948

Abstract

Phosphorus is a fundamental macronutrient, yet its low bioavailability in most soils makes phosphorus deficiency one of the most persistent constraints limiting global crop productivity. Although mineral fertilisation has long been the primary strategy for maintaining adequate P supply, inefficient fertiliser use and [...] Read more.

Phosphorus is a fundamental macronutrient, yet its low bioavailability in most soils makes phosphorus deficiency one of the most persistent constraints limiting global crop productivity. Although mineral fertilisation has long been the primary strategy for maintaining adequate P supply, inefficient fertiliser use and strong soil phosphorus fixation result in substantial losses. As a result, current research is shifting toward integrated phosphorus management approaches that combine optimised fertilisation techniques, unconventional phosphorus sources, and biological tools that mobilise soil-bound phosphorus. At the same time, silicon has emerged as a promising modulator of plant stress resilience, which can also influence phosphorus homeostasis. Silicon enhances plant physiological robustness by strengthening tissues, improving photosynthetic performance, and activating antioxidant pathways. Silicon may also modify phosphorus mobility in soils, promoting more efficient uptake and utilisation in plant tissues. This review synthesises current knowledge on physiological and molecular plant responses to phosphorus deficiency. It compares modern fertilisation strategies, ranging from precision fertilisation to unconventional phosphorus fertilisers. Particular attention is devoted to the emerging role of silicon in improving phosphorus availability and in enhancing crop plant phosphorus-use efficiency. The review concludes with future research directions that may help integrate silicon-based interventions into sustainable nutrient-management systems. Full article

(This article belongs to the Special Issue Phosphorus–Silicon Crosstalk in Plants: Enhancing Nutrient Efficiency and Alleviating Stress)

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23 pages, 3533 KB

Open AccessArticle

Research on an Automatic Seeding Performance Detection and Intelligent Reseeding Device for Leafy Vegetable Plug Seedlings

by Lei Zhong, Junming Huang, Yijuan Qin, Jie Wang, Shengye He, Yuming Luo, Xu Ma, Xueshen Chen and Suiyan Tan

Agronomy 2026, 16(3), 387; https://doi.org/10.3390/agronomy16030387 - 5 Feb 2026

Viewed by 1492

Abstract

To address the issues of a low single-seed qualification index and a high missed-seeding index in the process of leafy vegetable plug seedling sowing, this study proposes a lightweight seeding performance detection model named VS-YOLO based on YOLO11n. The model is then deployed [...] Read more.

To address the issues of a low single-seed qualification index and a high missed-seeding index in the process of leafy vegetable plug seedling sowing, this study proposes a lightweight seeding performance detection model named VS-YOLO based on YOLO11n. The model is then deployed on the edge device, the NVIDIA Jetson Xavier NX. A concise and intuitive graphical user interface (GUI) was developed and an automated detection system for vegetable seeding performance was constructed. Based on the empty cells identified by the system, a real-time data transmission mechanism between the Jetson device and a PLC-based control unit is established, enabling the intelligent reseeding device to perform precise reseeding at the designated cell location, achieving row-wise and cell-specific intelligent planting. VS-YOLO incorporates several innovative improvements, including the introduction of a Context Anchor Attention (CAA) module to form the C2PSA_CAA module, the adoption of the Wise Intersection over Union version 3 (WIoU v3) loss function, and the addition of an extra-small object detection head. These enhancements significantly improve the classification and recognition capability for small-sized vegetable seeds while notably reducing the number of model parameters. Experimental results show that VS-YOLO achieves a mAP@0.5 of 96.5% and an F1 Score of 93.45% in detecting the seeding performance of three types of vegetable seeds, outperforming YOLO11n’s 91.5% and 85.19% by 5.0% and 8.26%. The parameter count of VS-YOLO is only 1.61 M, which is 37.6% lower than YOLO11n’s 2.58 M, making it lightweight. Operating at a productivity rate of 120 trays per hour, the system achieved an accuracy of 99.03%, 89.83%, and 92.26% for single-seed prediction, multiple-seeding prediction, and missed-seeding prediction. The single-seed qualification index and missed-seeding index were 93.43% and 4.68%. After reseeding, these indices improved to 97.61% and 0.32%, representing an increase of 4.18% in the single-seed qualification index and a decrease of 4.36% in the missed-seeding index. The significant enhancement offers new ideas and technical approaches for the advancement of seeding performance detection and reseeding systems for vegetable plug seedling production. Full article

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

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25 pages, 10360 KB

Open AccessEditor’s ChoiceArticle

A Standardized Framework for Cleaning Non-Normal Yield Data from Wheat and Barley Crops, and Validation Using Machine Learning Models for Satellite Imagery

by Patricia Arizo-García, Sergio Castiñeira-Ibáñez, Enric Cruzado-Campos, Beatriz Ricarte, Constanza Rubio and Alberto San Bautista

Agronomy 2026, 16(3), 386; https://doi.org/10.3390/agronomy16030386 - 5 Feb 2026

Cited by 2 | Viewed by 1768

Abstract

Modern combine harvesters can collect real-time geolocated yield data, but it is subject to errors. Various protocols have been proposed to clean this data, each with varying levels of complexity. This data is valuable for precision agriculture to implement site-specific management and to [...] Read more.

Modern combine harvesters can collect real-time geolocated yield data, but it is subject to errors. Various protocols have been proposed to clean this data, each with varying levels of complexity. This data is valuable for precision agriculture to implement site-specific management and to train models to predict yield using remote sensing data. Machine learning and deep learning techniques have shown their potential for precision agriculture, and their performance shows no significant differences between models trained with data cleaned using a computationally demanding protocol or a simpler one, such as parametric filtering. However, parametric filtering approaches primarily rely on statistics that are highly sensitive to data distribution and do not effectively filter inliers. The objective of this study is to develop a data-cleansing method that leverages robust statistical measures, specifically the median and interquartile range, to effectively identify and filter outliers and inliers while retaining valid observations in datasets collected from combine harvesters, thereby minimizing the influence of non-normal data distributions. Different levels of data cleaning were applied to a total of 7399 ha of wheat and barley crops, and the quality of each cleaning level was compared. The selected protocol improved the spatial structure of the data, deleting up to 42% and 33% of the data at the polygon level, for wheat and barley, respectively. It increased the mean and median, and decreased the standard deviation and coefficient of variation of the data. Between 78.7% and 82.9% of the fields showed a normal distribution after applying the selected method, and machine learning performance improved compared with the raw data. Compared with previous data cleaning studies, the present work proposes an automatic, low-computational, parametric filtering method that uses robust statistics for non-normal distributions. In addition, its scalability has been demonstrated by applying the method to a large dataset, improving data quality and the performance of yield-prediction ML models in all cases. Full article

(This article belongs to the Special Issue Integrating Yield Maps, Soil Data, and IoT for Smarter Farming)

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16 pages, 1847 KB

Open AccessArticle

Fertilization Effects of Recycled Phosphorus with CaAl-LDH Under Controlled Conditions

by Yunsheng Jia, Liangkai Wang, Sijie Huang, Yun Chen, Mingqing Liu, Fei Liu, Jianyu Zhang, Jibing Zhang, Lifei Yang and Huoyan Wang

Agronomy 2026, 16(3), 385; https://doi.org/10.3390/agronomy16030385 - 5 Feb 2026

Viewed by 790

Abstract

To mitigate the exhausting of phosphate rock (PR) reserves and the widespread water eutrophication due partially to excessive phosphorus (P), efficient adsorbents are valuable. Calcium (Ca) and aluminum (Al) containing layered double hydroxides (CaAl-LDHs) showed high P adsorption capacity and potential as slow-release [...] Read more.

To mitigate the exhausting of phosphate rock (PR) reserves and the widespread water eutrophication due partially to excessive phosphorus (P), efficient adsorbents are valuable. Calcium (Ca) and aluminum (Al) containing layered double hydroxides (CaAl-LDHs) showed high P adsorption capacity and potential as slow-release P fertilizers, which merits further investigation. Two P proportions (5% and 10%) of P-adsorbed CaAl-LDHs (P-LDHs) were prepared, and its effects on various soil P contents and oilseed rape (Brassica napus L.) growth were evaluated. The main components of 5%P-LDH were P-intercalated CaAl-LDH and brushite, while 10%P-LDH mainly consisted of brushite. The proportions of P were extracted from 10%P-LDH and increased in the order of 4.9% (deionized water) < 48.9% (Olsen method) < 63.5% (Bray method) < 67.4% (citric acid), which suggested that 10%P-LDH could be citrate-soluble P fertilizer. 10%P-LDH showed similar effects on soil available P with single superphosphate (SSP). Both 5%- and 10%P-LDHs showed comparable improvement with SSP on aboveground dry weight of oilseed in the red soil, while being inapparent in the Fluvo-aquic soil. The CaAl-LDH appeared capable of providing Ca for rape growth in the low initial P concentration red soil, which showed the highest dry weight when combined with SSP. The recycled P-LDHs, especially 10%P-LDH, could supply P in a comparable manner with SSP for oilseed rape P uptake. Based on trials conducted under controlled conditions, our study suggested a promising production route of commercial P fertilizer alternatives via water P removal by CaAl-LDH. Further validations with realistic wastewater P removal by CaAl-LDH and via field scale growth trials are still needed before wide application of the alternative P fertilizer production procedure reported in the present study. Full article

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

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23 pages, 6778 KB

Open AccessArticle

Application of the Improved YOLOv8-DeepSORT Framework in Motion Tracking of Pepper Leaves Under Droplet Occlusion

by Fengfeng Guo, Kuan Liu, Jing Ma and Baijing Qiu

Agronomy 2026, 16(3), 384; https://doi.org/10.3390/agronomy16030384 - 5 Feb 2026

Viewed by 1177

Abstract

In agricultural plant protection spraying, dynamic occlusion by droplet swarms on leaf surfaces poses a major challenge to accurately acquiring leaf motion parameters, limiting the optimization of precision spraying and pesticide utilization. Traditional contact-based methods interfere with natural leaf dynamics, while non-contact optical [...] Read more.

In agricultural plant protection spraying, dynamic occlusion by droplet swarms on leaf surfaces poses a major challenge to accurately acquiring leaf motion parameters, limiting the optimization of precision spraying and pesticide utilization. Traditional contact-based methods interfere with natural leaf dynamics, while non-contact optical approaches suffer from tracking failures under occlusion. This study proposes an improved framework combining YOLOv8 integrated with a Spatial Attention Module (SAM) and optimized DeepSORT for robust non-contact tracking of marked points on pepper leaves. High-speed binocular cameras were used to collect leaf motion data under controlled droplet occlusion conditions. Results demonstrate that, under 5% occlusion, the improved model achieves a 19.6% increase in detection mAP@0.5 and significantly enhances tracking MOTA, with trajectory breakage rate reduced to 3.2% and ID switches decreased by approximately 71.4% in long-sequence tracking. Quantitative analysis of leaf midrib motion reveals a clear spatial gradient: average speed increases from 0.012 m s⁻¹ at the base to 0.153 m s⁻¹ at the tip, with intensified fluctuations toward the tip and a consistent dominant vibration frequency of 0.403 Hz across all points. This method provides an efficient, reliable non-contact solution for measuring leaf motion parameters in complex spraying scenarios, offering valuable data support for targeted spray parameter optimization and improved deposition efficiency in precision agriculture. Full article

(This article belongs to the Special Issue Research Progress in Agricultural Robots in Arable Farming)

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21 pages, 3538 KB

Open AccessEditor’s ChoiceArticle

Mobile AI-Powered Impurity Removal System for Decentralized Potato Harvesting

by Joonam Kim, Kenichi Tokuda, Yuichiro Miho, Giryeon Kim, Rena Yoshitoshi, Shinori Tsuchiya, Noriko Deguchi and Kunihiro Funabiki

Agronomy 2026, 16(3), 383; https://doi.org/10.3390/agronomy16030383 - 5 Feb 2026

Cited by 1 | Viewed by 1611

Abstract

An advanced artificial intelligence (AI)-powered mobile automated impurity removal system was developed and integrated into potato harvesting machinery for decentralized agricultural environments in Japan. As opposed existing stationary AI systems in centralized processing facilities, this mobile prototype enables on-field impurity removal in real [...] Read more.

An advanced artificial intelligence (AI)-powered mobile automated impurity removal system was developed and integrated into potato harvesting machinery for decentralized agricultural environments in Japan. As opposed existing stationary AI systems in centralized processing facilities, this mobile prototype enables on-field impurity removal in real time through a systematic dual-evaluation methodology. The system integrates the YOLOX-small architecture with precision pneumatic actuators and achieves 40–50 FPS processing under dynamic field conditions. Algorithm validation across 10 morphologically diverse potato varieties (Danshaku, Harrow Moon, Hokkaikogane, Kitaakari, Kitahime, May Queen, Sayaka, Snowden, Snow March, and Toyoshiro) using count-based analysis showed exceptional recognition, with potato misclassification rates of 0.08 ± 0.03% (range: 0.01–0.32%) and impurity detection rates of 89.99 ± 1.25% (range: 80.00–93.30%). Cross-farm validation across seven commercial farms in Hokkaido confirmed robust algorithm consistency (PMR: 0.08 ± 0.03%, IDR: 90.56 ± 0.82%) without farm-specific calibration, establishing variety-independent and environment-independent operation. Field validation using weight-based analysis during actual harvesting at 1–4 km/h confirmed successful AI-to-field translation, with 0.22–0.42% potato misclassification and adaptive impurity removal of 71.43–85.29%. The system adapted intelligently, employing conservative sorting under high-impurity loads (71.43% removal, 0.33% misclassification) to prioritize potato preservation while maximizing efficiency under standard conditions (85.29% removal, 0.30% misclassification). The dual-evaluation framework successfully bridged the gap between AI accuracy in laboratory settings and effectiveness in agricultural operations. The proposed AI algorithm surpassed project targets for all tested conditions (>60% impurity removal, <1% potato misclassification). This successful integration demonstrates technical feasibility and commercial viability for widespread agricultural automation, with a validated 50% reduction in labor (four workers to two workers). This implementation provides a comprehensive validation methodology for next-generation autonomous harvesting systems. Full article

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

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30 pages, 1036 KB

Open AccessReview

Plant Transcription Factors: Molecular Mechanisms in Cadmium (Cd) Detoxification and Applications for Reducing Cd Accumulation in Rice Grains

by Zebin Cai, Xinxin Xu, Yao Cao, Qingxian Mo and Jicai Yi

Agronomy 2026, 16(3), 382; https://doi.org/10.3390/agronomy16030382 - 4 Feb 2026

Cited by 2 | Viewed by 1197

Abstract

Cadmium (Cd) toxicity threatens global food security and agricultural sustainability. Transcription factors (TFs) act as master regulators of the complex molecular networks involved in Cd detoxification. This review provides a focused synthesis of the molecular mechanisms governing Cd tolerance in plants, encompassing antioxidant [...] Read more.

Cadmium (Cd) toxicity threatens global food security and agricultural sustainability. Transcription factors (TFs) act as master regulators of the complex molecular networks involved in Cd detoxification. This review provides a focused synthesis of the molecular mechanisms governing Cd tolerance in plants, encompassing antioxidant defense, Cd chelation and sequestration, Cd uptake and transport, signal transduction, and damage repair pathways. We highlight the pivotal roles of key TFs in these specific processes, such as OsMYB45 in antioxidant defense, OsIRO2 in regulating chelation and storage, OsNAC5 in modulating Cd transport, and OsE2F in facilitating the repair of DNA and protein damage. Furthermore, we evaluate the potential of harnessing these TF-mediated regulatory mechanisms for developing low-Cd rice varieties. By delineating precise correlations between specific TFs and detoxification pathways, this review proposes actionable molecular strategies to mitigate Cd contamination, thereby contributing to ecological and food safety. Full article

(This article belongs to the Special Issue Molecular Mechanisms of Nutrient Stress Responses in Crops: From Physiology to Epigenetics)

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19 pages, 5508 KB

Open AccessArticle

Optimizing Diversified Crop Rotation Strategies Under Temperature and Precipitation Change Scenarios in a Typical Agro-Pastoral Ecotone Using the APSIM Model

by Sijia Wang, Junli Jin, Yue Li, Shanshan Lv, Yanan Li, Di Wu and Roland Bol

Agronomy 2026, 16(3), 381; https://doi.org/10.3390/agronomy16030381 - 4 Feb 2026

Viewed by 887

Abstract

Future climate change poses unprecedented challenges to agricultural production worldwide. Therefore, designing region-specific rotation patterns is crucial for achieving synergies among multiple objectives, including agricultural productivity and ecological conservation. Based on a long-term field experiment in the Northern Agro-pastoral Ecotone of China, we [...] Read more.

Future climate change poses unprecedented challenges to agricultural production worldwide. Therefore, designing region-specific rotation patterns is crucial for achieving synergies among multiple objectives, including agricultural productivity and ecological conservation. Based on a long-term field experiment in the Northern Agro-pastoral Ecotone of China, we calibrated and validated the Agricultural Production Systems Simulator (APSIM) and simulated rotation patterns involving four representative crops under eight climate scenarios, including warming, extreme precipitation, and combined temperature–precipitation changes. Analysis combined with carbon footprint assessment was employed to quantitatively evaluate the productivity, ecological benefits, and economic returns of different rotation patterns. The results showed that warming generally reduced crop productivity and economic returns, weakened soil carbon sequestration, and increased net carbon emissions across rotation patterns. Increasing intensity of extreme precipitation further constrained the capacity of rotation patterns to enhance yields, improve incomes, and reduce carbon emissions. Under scenarios of warming and extreme precipitation, the faba bean–oat rotation pattern was found to be the most effective for increasing crop yields, while the faba bean–potato rotation is beneficial for enhancing the incomes from local agriculture. The potato–faba bean rotation pattern was most effective for environmental sustainability due to low net carbon emissions. The findings provide a scientific basis for developing diversified planting strategies with synergistic multi-objectives in the Northern Agro-pastoral Ecotone of China, contributing to food security and sustainable agricultural development under a changing climate focused on changes in temperature and precipitation. Nevertheless, the potential effects of rising atmospheric CO₂ concentrations may be incorporated in future studies. Full article

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

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24 pages, 18806 KB

Open AccessArticle

Effects of Gramineous and Leguminous Crops on Soil Microbial Community Structure and Diversity

by Zexian Mi, Zeyang Zheng, Botao Liu, Weitao Han, Xuehao Shan, Zhuofan Pu, Nuerbiyamu Rouzi, Xin Tan, Jianing Wei, Shaorong Hao and Hongliang Tang

Agronomy 2026, 16(3), 380; https://doi.org/10.3390/agronomy16030380 - 4 Feb 2026

Cited by 1 | Viewed by 648

Abstract

Different crops have varying effects on soil factors, and their associated microbial community compositions also differ. Currently, there is limited comparative research on crops with distant phylogenetic relationships, such as those between gramineous and leguminous species. In this study, a pot experiment combined [...] Read more.

Different crops have varying effects on soil factors, and their associated microbial community compositions also differ. Currently, there is limited comparative research on crops with distant phylogenetic relationships, such as those between gramineous and leguminous species. In this study, a pot experiment combined with high-throughput sequencing was conducted to enable a detailed comparison of microbial communities and soil factors across four crops: wheat, soybean, and two maize varieties. Compared to leguminous crops, differences between gramineous crops may be relatively smaller. The results showed that among the gramineous and leguminous crops, soybean had the lowest effect on soil electrical conductivity (EC) and available phosphorus (AP) (121.68 ± 2.70, 34.74 ± 1.02). The dominant fungi and bacteria phyla were Ascomycota and Proteobacteria; both were most abundant in the ZD958 variety, at 75.12% and 30.47%, respectively. The fungal diversity of ZD958 was most similar to that of W998, whereas the bacterial diversity of XY335 more closely resembled that of SB13. EC and AP were the key factors influencing fungal community composition, while alkali-hydrolyzable nitrogen (AN) was the key factor affecting bacterial community composition. These findings provide a basis for further in-depth research. Full article

(This article belongs to the Special Issue Endophytic Fungi and Beneficial Microbes for Sustainable Crop Resilience)

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20 pages, 7488 KB

Open AccessArticle

Genetic Diversity and Lineage Distribution of Hypera postica (Gyllenhal) Populations in Xinjiang, China

by Jinlong Ren, Yang Wang, Li Zhao and Shiqian Feng

Agronomy 2026, 16(3), 379; https://doi.org/10.3390/agronomy16030379 - 4 Feb 2026

Viewed by 685

Abstract

Hypera postica (Gyllenhal) is a major pest of alfalfa. We combined mitochondrial COI and CytB gene sequences to characterize the genetic diversity of 20 geographic populations of H. postica across Xinjiang, China, and to elucidate their lineage relationships at both regional and global [...] Read more.

Hypera postica (Gyllenhal) is a major pest of alfalfa. We combined mitochondrial COI and CytB gene sequences to characterize the genetic diversity of 20 geographic populations of H. postica across Xinjiang, China, and to elucidate their lineage relationships at both regional and global scales. We found that Nucleotide diversity (Pi) was markedly higher in western Xinjiang populations (Pi > 0.016), specifically Wusu (0.023), Tekes (0.023), Jinghe (0.023), Wenquan (0.021), Bole (0.021), Habahe (0.020), Nilka (0.020), Tacheng (0.019), Toli (0.018), Altay (0.017), Emin (0.016), Xinyuan (0.016), and Zhaosu (0.016), whereas central Xinjiang populations exhibited substantially lower diversity (Pi < 0.014), including Shawan (0.014), Qitai (0.011), Jimsar (0.007), Urumqi (0.004), Hutubi (0.003), Fukang (0.001), and Manas (0.001). Pairwise F_ST analysis revealed pronounced genetic divergence between the western Xinjiang group (Altay, Bole, Wenquan, Tacheng, Emin, Toli, Nilka, Xinyuan, Tekes, Zhaosu) and the central Xinjiang group (Qitai, Urumqi, Fukang, Habahe, Hutubi, Jimsar, Shawan, Manas). At the global level, H. postica can be divided into two major phylogroups: the Western and Eastern lineages. All Xinjiang populations belong to the Eastern lineage. Haplotype network analysis identified two distinct sublineages, western and central Xinjiang, with H2 and H26 as their respective dominant shared haplotypes; both are unique to China. Both maximum likelihood (ML) and Bayesian phylogenetic trees robustly support the central Xinjiang lineage as a distinct clade. Neutrality tests provided strong evidence of recent demographic expansion across the Xinjiang H. postica population as a whole (Fu’s Fs = −21.987, p < 0.05), with particularly pronounced signals in Hutubi (HTB: Tajima’s D = −1.966, Fu’s Fs = −0.781, p < 0.05), Jimsar (JMSE: Tajima’s D = −2.176, Fu’s Fs = −0.962, p < 0.01), and Wenquan (WQ: Fu’s Fs = −11.159, p < 0.01). Our results reveal a clear phylogeographic split within Xinjiang H. postica populations, comprising western and central sub-lineages, with the western sub-lineage likely representing ancestral lineage. The western Xinjiang sub-lineage appears to be shaped primarily by mountainous topography, whereas the central Xinjiang sub-lineage likely results from the combined effects of piedmont plain geography and infection with the endosymbiont Wolbachia strain wHypera4. Full article

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14 pages, 1313 KB

Open AccessArticle

Aboveground Competition Masks Belowground Competition Between Agropyron cristatum and Artemisia frigida

by Hao Chen, Xingxing Feng, Jie Wei, Qing Chen and Yonghong Hao

Agronomy 2026, 16(3), 378; https://doi.org/10.3390/agronomy16030378 - 4 Feb 2026

Viewed by 897

Abstract

Artemisia frigida (subshrub) communities, which are indicators of grassland degradation, are widespread in overgrazed Eurasian steppes. After 4–6 years of enclosure, the community can recover to an Agropyron cristatum-dominated grass community. Understanding the competitive mechanisms between these two key species provides critical [...] Read more.

Artemisia frigida (subshrub) communities, which are indicators of grassland degradation, are widespread in overgrazed Eurasian steppes. After 4–6 years of enclosure, the community can recover to an Agropyron cristatum-dominated grass community. Understanding the competitive mechanisms between these two key species provides critical insights for the management of semi-arid steppes, where vegetation dynamics are primarily driven by soil moisture. Nevertheless, how soil moisture distribution mediates above- and belowground competition between A. cristatum and A. frigida remains unclear. To address this, we conducted a pot experiment that simulated natural vertical soil moisture heterogeneity with four soil moisture regimes in two soil layers (0–30 cm and 30–60 cm): uniformly dry (D–D), wet upper/dry lower (W–D), dry upper/wet lower (D–W), and uniformly wet (W–W), using both monoculture and mixed planting methods. Key results showed that (1) A. cristatum was more sensitive to soil moisture regimes than A. frigida. Its above- and belowground biomass were significantly higher under moist treatments (W–W, W–D, D–W) than under drought (D–D), whereas the biomass of A. frigida did not differ significantly among water treatments. (2) Compared with monoculture, mixed planting significantly increased the root–shoot ratio of A. frigida but did not affect that of A. cristatum. (3) Competitive ability differed between aboveground and belowground parts: competitive indices (aggressivity and relative competition intensity) revealed that A. cristatum exhibited stronger aboveground competitiveness under moist treatments, while A. frigida dominated aboveground under drought conditions. However, A. frigida consistently exhibited greater belowground competitive ability than A. cristatum across all water treatments in the mixture. These results emphasize that assessments of grass–shrub competition based solely on aboveground indicators may underestimate the competitive advantage of shrubs. Therefore, integrating belowground competitive processes is essential for accurately predicting grass–shrub competition and succession in semi-arid steppes. Full article

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

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15 pages, 1483 KB

Open AccessArticle

Seed Germination Characteristics of Lolium multiflorum Populations from Wheat Fields of Eastern China

by Bingbing Cao, Jiahao Xue, Linjing Ye and Guoqi Chen

Agronomy 2026, 16(3), 377; https://doi.org/10.3390/agronomy16030377 - 4 Feb 2026

Viewed by 1332

Abstract

Lolium multiflorum is of worldwide agricultural importance as both a pasture crop and as a weed. We collected the seeds of 67 L. multiflorum populations from wheat lands in eastern China and three populations as commercial crop seeds; tested seed germination responses to [...] Read more.

Lolium multiflorum is of worldwide agricultural importance as both a pasture crop and as a weed. We collected the seeds of 67 L. multiflorum populations from wheat lands in eastern China and three populations as commercial crop seeds; tested seed germination responses to temperature, osmotic potentials, and light/dark conditions; and also tested seed dormancy. Under constant temperatures, the germination percentages at 3 d after treatement (DAT) at 10, 15, 20, 25, 30, and 35 °C were 0%, 2.6 ± 0.5%, 37.1 ± 2.4%, 66.6 ± 1.9%, 68.2 ± 2.3%, and 37.3 ± 2.2%, respectively, and increased to 72.4 ± 2.0%, 95.6 ± 0.7%, 97.0 ± 0.7%, 98.3 ± 0.6%, 94.9 ± 1.0%, and 86.3 ± 1.2% at 14 DAT. The seed germination percentages in complete darkness at 14 DAT (averagely 87.4%) did not show significant differences with those in 12 h light/12 h dark treatment. The osmotic potential required for 50% germination (GO₅₀) was −0.53 to −0.13 MPa, with an average of −0.38 MPa, and the average germination percentage under −0.6 MPa at 14 DAT was 0.9%. The germination percentages of freshly mature seeds stored for 0, 15, 30, and 60 d were 61.3%, 66.5%, 68.4%, and 88.0%. L. multiflorum populations collected from wheat fields with rice as the preceding crop (paddy fields) showed significantly higher germination percentages under 10 °C, and lower germination percentages under osmotic stresses, compared with those collected from wheat fields with corn as the preceding crop (drylands). This is the first report of L. multiflorum seed germination biology based on multiple populations with different sources in China and provides insights for improving its management strategies. Full article

(This article belongs to the Special Issue Seed Production and Technology)

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32 pages, 7698 KB

Open AccessArticle

Delineating Soybean Mega-Environments Across State Lines: A Statistical Learning Approach to Multi-State Official Variety Trial Analysis

by Isaac Mirahki, Richard Bond, Ryan Heiniger, David Moseley and Virginia R. Sykes

Agronomy 2026, 16(3), 376; https://doi.org/10.3390/agronomy16030376 - 4 Feb 2026

Viewed by 864

Abstract

The current state-centric analysis of Official Variety Trials (OVTs) restricts the identification of stable performance zones across political boundaries. This study employed multivariate statistical learning techniques to delineate soybean (Glycine max L.) “mega-environments” using yield data from 2269 varieties collected across seven [...] Read more.

The current state-centric analysis of Official Variety Trials (OVTs) restricts the identification of stable performance zones across political boundaries. This study employed multivariate statistical learning techniques to delineate soybean (Glycine max L.) “mega-environments” using yield data from 2269 varieties collected across seven U.S. states (2019–2022). Utilizing Quadratic Discriminant Analysis (QDA), Principal Component Analysis (PCA), and Agglomerative Hierarchical Clustering (AHC), we examined the edaphoclimatic factors influencing yield stability. QDA classified over 79% of environments into distinct temporal categories, highlighting significant inter-annual climatic variability driven by Growing Degree Days (GDD) and latitude. PCA distinguished broad climatic drivers (PC1) from localized soil texture constraints (PC2). AHC identified optimal production clusters that frequently diverged from geographic proximity, indicating that distant sites often share more critical yield-determining factors than neighboring counties. By operationalizing these latent environmental patterns, this study provides a data-driven framework for cross-state environmental zoning that can support more precise variety placement once genotype performance has been evaluated within these zones. Full article

(This article belongs to the Special Issue Advanced Machine Learning in Agriculture—2nd Edition)

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19 pages, 4225 KB

Open AccessArticle

Identification of Specific Long-Lived mRNAs Associated with Seed Longevity in Sweet Corn Based on RNA-seq

by Zili Zhang, Xinmei Wang, Xiaoni Guan, Yuliang Li, Zhixian Peng, Guangzu Li, Feng Jiang, Qingchun Chen, Faqiang Feng and Pengfei Liu

Agronomy 2026, 16(3), 375; https://doi.org/10.3390/agronomy16030375 - 3 Feb 2026

Cited by 1 | Viewed by 1209

Abstract

Seeds possess long-lived messenger RNAs (mRNAs), some of which are involved in triggering germination and supporting seed longevity. Nevertheless, comprehensive studies on longevity-associated long-lived mRNAs in sweet corn are still scarce. To address this, eight sweet corn inbred lines were subjected to artificial [...] Read more.

Seeds possess long-lived messenger RNAs (mRNAs), some of which are involved in triggering germination and supporting seed longevity. Nevertheless, comprehensive studies on longevity-associated long-lived mRNAs in sweet corn are still scarce. To address this, eight sweet corn inbred lines were subjected to artificial aging (AA) and natural aging (NA). Based on half-inhibition time (ID₅₀), two representative lines—a high-longevity (HL, T7) and a low-longevity (LL, T3) line—were selected. Physiological and biochemical assays revealed significant reductions in superoxide dismutase (SOD) and peroxidase (POD) activities, along with increased malondialdehyde (MDA) content and electrical conductivity, with more severe membrane damage in the LL line. RNA sequencing (RNA-seq) showed a strong correlation in differentially expressed genes (DEGs) between AA and NA. The combined DEGs were enriched in mitogen-activated protein kinase (MAPK) signaling and tryptophan metabolism, while five common long-lived mRNAs, including Zm00001eb157210 and Zm00001eb164610, were consistently downregulated, suggesting their potential role in regulating seed vigor. These findings highlight key molecular players in sweet corn seed longevity. Full article

(This article belongs to the Collection Abiotic Stress Tolerance in Plants: Towards a Sustainable Agriculture)

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13 pages, 2422 KB

Open AccessArticle

Soil Enzymes and Stable Isotopes as Suitable Soil–Plant Indicators of Ecosystem Functionality in Mediterranean Forests

by Serena Doni, Francesca Vannucchi, Cristina Macci, Andrea Scartazza, Roberto Pini, Manuele Scatena, Nicola Arriga, Alessandro Dell’Acqua, Grazia Masciandaro and Eleonora Peruzzi

Agronomy 2026, 16(3), 374; https://doi.org/10.3390/agronomy16030374 - 3 Feb 2026

Cited by 1 | Viewed by 1260

Abstract

Monitoring the soil–plant system in forest ecosystems is crucial for preserving their ecological functions and services. This study assessed carbon and nitrogen stable isotopes and ecoenzymatic stoichiometry as suitable indicators for characterizing the soil–plant system as a functional unit of ecological processes. To [...] Read more.

Monitoring the soil–plant system in forest ecosystems is crucial for preserving their ecological functions and services. This study assessed carbon and nitrogen stable isotopes and ecoenzymatic stoichiometry as suitable indicators for characterizing the soil–plant system as a functional unit of ecological processes. To this end, in June 2021 six plots (1 m² each) were selected in two typical Mediterranean forest ecotypes: a coastal stone pine forest (Pinus pinea L., PF) and a meso-hygrophilous broadleaf forest (RV). Soil samples (0–15 and 15–30 cm depth) and litter samples (40 × 40 cm) were collected and characterized in terms of physical, chemical and biochemical properties. t-tests revealed significant differences between RV and PF, indicating distinct microbial nutrient acquisition strategies. The higher C:N ratio in PF suggested lower litter quality and greater recalcitrance to microbial decomposition. Consistently, RV showed a more pronounced ¹³C and ¹⁵N enrichment from litter to SOM down to a 30 cm depth, confirming faster organic matter decomposition and mineralization. Enzyme activity patterns supported these findings. The higher β-glucosidase and butyrate esterase activities in RV reflected its greater microbial potential to activate biogeochemical cycles. Both forests exhibited a higher microbial demand for C and P than for N to maintain ecological stoichiometric balance, with stronger C limitation at the surface and P limitation in the subsoil, particularly in RV soil. This integrated monitoring approach provides insights into nutrient cycling and ecosystem resilience and offers tools to evaluate ecosystem functionality under changing environmental conditions, supporting sustainable forest management. Full article

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

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16 pages, 25372 KB

Open AccessArticle

Non-Invasive Diagnosis of Nitrogen and Phosphorus in Hydrangea macrophylla at Seedling Stage Using RGB Images

by Jun Yang, Qunlu Liu, Zhao Liu, Qiang Xing and Jun Qin

Agronomy 2026, 16(3), 373; https://doi.org/10.3390/agronomy16030373 - 3 Feb 2026

Viewed by 1013

Abstract

Rapid and accurate diagnosis of nitrogen (N) and phosphorus (P) is crucial for Hydrangea macrophylla nursery management. Traditional methods are time-consuming, and existing non-destructive studies rarely target ornamental plants or support joint N-P diagnosis at the early growth stage. A total of 339 [...] Read more.

Rapid and accurate diagnosis of nitrogen (N) and phosphorus (P) is crucial for Hydrangea macrophylla nursery management. Traditional methods are time-consuming, and existing non-destructive studies rarely target ornamental plants or support joint N-P diagnosis at the early growth stage. A total of 339 RGB images were captured from potted hydrangeas grown under varying N and P levels at the seedling stage, with 65 phenotypic traits (color, texture, and morphology) extracted. Nutritional status (deficient, optimal, and surplus) was categorized with reference to plant nutrition indices. Discriminant models were then developed using four machine learning algorithms: convolutional neural network (CNN), support vector machine (SVM), random forest (RF), and probabilistic neural network (PNN). The model performances were evaluated using overall accuracy, precision, recall, F1-score, and Cohen’s Kappa coefficient (κ). As a result, CNN achieved 82.65% accuracy (κ = 0.7392) for N classification, and SVM reached 83.65% accuracy (κ = 0.7357) for P classification. Color-related traits dominated the top five contributing features, indicating a stronger correlation with N and P status. This work offers a practical solution for real-time, low-cost, and non-destructive nutrient diagnosis, supporting precision fertilization and enhancing environmental sustainability in nursery production. Full article

(This article belongs to the Special Issue Advancements in Precision Fertilization and Water Management for Sustainable Agriculture)

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13 pages, 2483 KB

Open AccessArticle

Different Driving Mechanisms for Spatial Variations in Soil Autotrophic and Heterotrophic Respiration: A Global Synthesis for Forest and Grassland Ecosystems

by Yun Jiang, Jiajun Xu, Chengjin Chu, Xiuchen Wu and Bingwei Zhang

Agronomy 2026, 16(3), 372; https://doi.org/10.3390/agronomy16030372 - 3 Feb 2026

Viewed by 1326

Abstract

As a pivotal component of the global carbon cycle, the spatial variation in soil respiration (Rs) is crucial for forecasting climate change trajectories. Despite extensive research on the spatial patterns of total Rs, the distinct drivers of its two components, heterotrophic respiration (Rh) [...] Read more.

As a pivotal component of the global carbon cycle, the spatial variation in soil respiration (Rs) is crucial for forecasting climate change trajectories. Despite extensive research on the spatial patterns of total Rs, the distinct drivers of its two components, heterotrophic respiration (Rh) and autotrophic respiration (Ra), are still not well defined. We compiled a global dataset from studies published between 2007 and 2023 to investigate the drivers of spatial variations in Rs, Ra, and Rh. This dataset comprises 308 annual flux measurements from 172 sites. The results showed that Rh contributed 63% and 60% to Rs in forest and grassland ecosystems, respectively. Further analyses using structural equation modelling (SEM) showed that the spatial variation in Rh and Ra exhibited divergent responses to climatic factors and plant community structure (mostly driven by gross primary production, GPP). Rh was more affected by mean annual temperature (MAT) than by mean annual precipitation (MAP), with standardized total effects of 0.17 (forests) and 0.57 (grasslands) for MAT versus 0.10 and 0.07 for MAP, respectively. In contrast, Ra exhibited greater sensitivity to MAP (0.08 and 0.18) than to MAT (−0.01 and 0.04). GPP exerted biome-specific effects: in forests, high GPP enhanced Rh (0.18) more substantially than Ra (0.08), while in grasslands, elevated GPP significantly increased Ra (0.34) but suppressed Rh (−0.30). Moreover, these variables incorporated into the SEMs accounted for a greater proportion of the variation in Rh and Ra in grasslands (R² = 0.73 for Rh, 0.48 for Ra) as compared to forests (R² = 0.21 for Rh, 0.22 for Ra), suggesting the greater complexity in forest soil C dynamics. By using the whole yearly measured soil respiration data around the world, this study highlights the differential environmental regulation of Rh and Ra, providing critical insights into the mechanisms governing Rs variations under climate change. Full article

(This article belongs to the Special Issue Soil Carbon Sequestration and Greenhouse Gas Emissions)

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13 pages, 1258 KB

Open AccessArticle

Exploration of Acid-Tolerant Peanut Varieties Associated with Key Beneficial Rhizosphere Microbiome and Their Plant Growth-Promoting Effects in Acidic Soil

by Zihao Wei, Hao Cao, Chao Wang, Hongjun Liu, Qirong Shen and Rong Li

Agronomy 2026, 16(3), 371; https://doi.org/10.3390/agronomy16030371 - 3 Feb 2026

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Abstract

Soil acidification is among the primary abiotic stress factors that constrain plant growth. The adoption of acid-tolerant plant varieties and the inoculation of plant growth-promoting rhizobacteria have the distinct advantages of simultaneously increasing soil fertility and ensuring crop growth in acidic soil. However, [...] Read more.

Soil acidification is among the primary abiotic stress factors that constrain plant growth. The adoption of acid-tolerant plant varieties and the inoculation of plant growth-promoting rhizobacteria have the distinct advantages of simultaneously increasing soil fertility and ensuring crop growth in acidic soil. However, how acid-tolerant plant varieties interact with the associated rhizosphere microbiota still needs to be explored. In this study, acid-tolerant peanut varieties were screened and planted in natural and sterile environments. The results revealed significant differences in growth performance among the varieties in acidic soil and between natural and sterile environments, revealing that the rhizosphere microbiota is dependent on acid tolerance. Through high-throughput sequencing analysis, the key taxa Sinomonas and Aspergillus were identified, and subsequent greenhouse verification experiments demonstrated their function in promoting peanut plant growth in acidic soil. In total, our findings suggest that the holobiont of tolerant plants and the rhizosphere microbiota is important for stress resistance. This perspective opens up new avenues for improving crop cultivation in soils with different stresses, in which both plant and associated microbial properties are considered. Full article

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

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Agronomy, Volume 16, Issue 3 (February-1 2026) – 123 articles

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