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Mushroom Spawn and Its Effects on Mushroom Growth and Development: A Systematic Review
Screening Almond Cultivars for Water Stress Tolerance Using Multiple Diagnostic Parameters
Nature-Based Solutions (NbS) in Agricultural Soils for Greenhouse Gas Mitigation
A Standardized Framework for Cleaning Non-Normal Yield Data from Wheat and Barley Crops, and Validation Using Machine Learning Models for Satellite Imagery

Journal Description

Agronomy

Agronomy is an international, peer-reviewed, open access journal on agronomy and agroecology published semimonthly online by MDPI. The Spanish Society of Plant Biology (SEBP) is affiliated with Agronomy and their members receive discounts on the article processing charges.

Open Access— free for readers, with article processing charges (APC) paid by authors or their institutions.
High Visibility: indexed within Scopus, SCIE (Web of Science), GEOBASE, PubAg, AGRIS, and other databases.
Journal Rank: JCR - Q1 (Agronomy) / CiteScore - Q1 (Agronomy and Crop Science)
Rapid Publication: manuscripts are peer-reviewed and a first decision is provided to authors approximately 17 days after submission; acceptance to publication is undertaken in 1.8 days (median values for papers published in this journal in the second half of 2025).
Recognition of Reviewers: reviewers who provide timely, thorough peer-review reports receive vouchers entitling them to a discount on the APC of their next publication in any MDPI journal, in appreciation of the work done.
Companion journals for Agronomy include: Seeds, Agrochemicals, Grasses and Crops.
Journal Cluster of Agricultural Science: Agriculture, Agronomy, Horticulturae, Soil Systems, AgriEngineering, Crops, Seeds, Grasses, Agrochemicals and AI and Precision Agriculture.

Impact Factor: 3.4 (2024); 5-Year Impact Factor: 3.8 (2024)

Imprint Information Journal Flyer Open Access ISSN: 2073-4395

Latest Articles

18 pages, 3919 KB

Open AccessArticle

Long-Term No-Tillage Improves the Rhizosphere Microbial Community of Maize by Enhancing Root Development and Soil Nutrients

by Lina Dong, Xiangfei Han, Shuaimin Chen, Yanjie Lv, Jinyu Zheng, Yang Luo, Yongjun Wang and Lichun Wang

Agronomy 2026, 16(11), 1037; https://doi.org/10.3390/agronomy16111037 (registering DOI) - 23 May 2026

Tillage practices can change the soil environment (including soil properties and enzyme activity) and the rhizosphere microbial community, thereby inducing changes in root growth and the nutrient uptake capacity. This study was carried out on a long-term (since 1983) tillage field experimental platform. [...] Read more.

Tillage practices can change the soil environment (including soil properties and enzyme activity) and the rhizosphere microbial community, thereby inducing changes in root growth and the nutrient uptake capacity. This study was carried out on a long-term (since 1983) tillage field experimental platform. It aimed to explore the effects of tillage practices and growth stages on maize root development, soil properties, and the rhizosphere microbial community. The results can provide a theoretical basis for the further analysis of crop–soil–microbial interactions. In our study, we investigated the abundance and diversity of the rhizosphere microbial community and their relationship with root growth characteristics and soil factors under long-term (since 1983) conventional tillage (CT), subsoil tillage (ST), and no-tillage (NT) practices using quantitative PCR and high-throughput 16S/ITS sequencing. In 2020, at the 30-days-after-silking (VT 30) stage, NT increased the root length, root dry weight, N accumulation, and N uptake rate of maize roots compared with CT by 16.7%, 16.3%, 41.9%, and 41.9%, respectively. In 2020, at the 12th leaf (V12) and VT 30 stages of maize, NT significantly increased the contents of soil total nitrogen (by 16.3% and 11.0%, respectively), total carbon (by 23.9% and 12.9%, respectively), soil organic matter (by 24.8% and 10.3%, respectively), and soil urease activity (by 5.5% and 5.6%, respectively) compared with CT. Moreover, NT significantly increased the bacterial and fungal abundances compared with CT. Redundancy analysis (RDA) showed that the variation in the microbial structure correlated markedly with the alteration in root indicators, soil properties, and enzyme activities. Long-term no-tillage improved the abundance and diversity of rhizosphere microbial communities by increasing the soil total nitrogen, total carbon, and soil organic matter, and promoted the N accumulation of roots and their uptake rate. Full article

(This article belongs to the Section Agroecology Innovation: Achieving System Resilience)

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25 pages, 924 KB

Open AccessReview

Impact and Prospects of the Invasive Alien Plant Robinia pseudoacacia L. as a Bioenergy Resource

by Marina Maura Calandrelli and Luigi De Masi

Agronomy 2026, 16(11), 1036; https://doi.org/10.3390/agronomy16111036 (registering DOI) - 23 May 2026

The growing demand for renewable energy, together with the need to mitigate climate change and promote more sustainable agriculture systems, has stimulated interest in energy crops. In this context, invasive alien plant species (IAPS), which have progressively colonized abandoned farmland, degraded ecosystems, and [...] Read more.

The growing demand for renewable energy, together with the need to mitigate climate change and promote more sustainable agriculture systems, has stimulated interest in energy crops. In this context, invasive alien plant species (IAPS), which have progressively colonized abandoned farmland, degraded ecosystems, and marginal areas, represent a key bioresource. IAPS have a dual nature combining high ecological invasiveness and fast growing rate with notable energetic potential. These aspects have generated a still ongoing debate among farm managers, ecologists, and policymakers regarding their role within the future bioeconomy. The present study provides a review of the IAPS black locust (Robinia pseudoacacia L.) on its real benefits as a source of bioenergy, ecological impact, and the management strategies adopted. We examine the trade-offs between containment efforts and use for renewable bioenergy production, particularly in marginal areas where few alternatives exist. This review highlights the need for stratified site-specific approaches that balance biodiversity conservation with bioresource exploitation. Finally, this study also contributes to the ongoing discussion on whether IAPS should be regarded primarily as a management challenge or a multifunctional bioresource, as in the production of bioenergy. Full article

(This article belongs to the Special Issue Energy Crops in Sustainable Agriculture)

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27 pages, 1481 KB

Open AccessArticle

Rapid Decomposition of Brittle Rice Straw Reduces Greenhouse Gas Emissions and Shifts Carbon Allocation in Paddy Soils

by Jerickson Manuel Dela Cruz, Cheng-Hsien Lin, Shan-Li Wang, Chang-Sheng Wang, Yu-Ting Liu, Kuo-Chen Yeh and Yu-Yu Kung

Agronomy 2026, 16(11), 1035; https://doi.org/10.3390/agronomy16111035 (registering DOI) - 23 May 2026

Rice (Oryza sativa L.) straw-return can improve soil carbon (C) sequestration, but its adoption in intensive rice systems is limited by short fallow periods (< 30 days), which likely lead to incomplete straw decomposition and increase methane emissions under continuous flooding (CF). [...] Read more.

Rice (Oryza sativa L.) straw-return can improve soil carbon (C) sequestration, but its adoption in intensive rice systems is limited by short fallow periods (< 30 days), which likely lead to incomplete straw decomposition and increase methane emissions under continuous flooding (CF). Brittle rice straw, characterized by lower recalcitrant fiber content and rapid decomposition, may overcome this constraint; however, its environmental performance under alternate wetting and drying (AWD) remains unclear, such as broader C allocation. This 150-day microcosm study evaluated the interaction of straw type (brittle vs. non-brittle) and water management (CF vs. AWD) on greenhouse gas (GHG) emissions, dissolved C production, soil C storage, and aggregate formation in two contrasting paddy soils (sandy loam vs. silty clay loam). Compared with non-brittle straw, brittle straw returns reduced net GHG emissions by approximately 28.4% under CF and 39.6% under AWD. The combination of brittle straw with AWD produced the lowest net GHG emissions (0.61 kg CO_2-eq m⁻²), indicating that intermittent oxygen input effectively mitigated the early decomposition-related emission risk. Brittle straw also increased the concentrations of dissolved inorganic C by 14.2% and nitrate by 64.3% under AWD, suggesting enhanced mineralization and potential inorganic C stabilization. Regardless of straw type, straw return improved soil C stocks by 27.3% in sandy loam and 29.6% in silty clay loam, while also promoting macroaggregate formation. Overall, this study demonstrated that coupling brittle rice straw with AWD can reduce GHG emissions while maintaining soil C benefits, offering a promising residue management strategy for intensive rice cultivation. Full article

(This article belongs to the Special Issue Agricultural Carbon Sequestration, Emission Reduction, and Efficiency Enhancement: Innovative Practices and Prospects)

15 pages, 3494 KB

Open AccessArticle

Genotypic Variation and Selection Potential for Agronomic and Quality Traits in Silage Maize Across Sowing Dates

by Junyan Liu, Yirui Zhao, Mingdao Zi, Wentao Du, Shuqi Ding, Ying Hao, Mengting Hu and Dan Zhang

Agronomy 2026, 16(11), 1034; https://doi.org/10.3390/agronomy16111034 (registering DOI) - 23 May 2026

To identify suitable silage maize varieties and optimal sowing dates for Aral in southern Xinjiang, 10 silage maize varieties were evaluated under three sowing date treatments (April 22, April 28, and May 6) from 2024 to 2025. Agronomic traits, yield components, and nutritional [...] Read more.

To identify suitable silage maize varieties and optimal sowing dates for Aral in southern Xinjiang, 10 silage maize varieties were evaluated under three sowing date treatments (April 22, April 28, and May 6) from 2024 to 2025. Agronomic traits, yield components, and nutritional quality indices were systematically determined. Multivariate statistical methods were employed for comprehensive evaluation. The results indicated that sowing date, variety, and their interaction exerted highly significant effects on most key agronomic traits, yields, and nutritional quality indicators of silage maize (p < 0.01). The sowing date had markedly different regulatory effects on the traits studied. Sowing on April 22 was conducive to improving the yield and fiber quality of silage maize. Sowing on April 28 optimized agronomic traits, including the uppermost ear leaf area and stem diameter. Sowing on May 6 significantly increased the crude protein and starch contents of silage maize. Cluster analyses combined with membership function analysis identified Dajingjiu 26 and Yu Qingzhu 23 as varieties with consistently excellent comprehensive traits and strong adaptability to regional ecological conditions across all sowing dates. These two varieties are recommended for priority deployment in local silage maize production, combined with their corresponding optimal sowing dates, to achieve the simultaneous optimization of yield and quality. The findings provide theoretical support and practical reference for silage maize variety selection and sowing date optimization in similar climate regions. Full article

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

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19 pages, 371 KB

Open AccessReview

The Nitrate-First, Ammonium-Later Strategy in Potato: Implications of Nitrogen Timing, Form, and Soil Transformation

by Jing Yu, Xiaohua Shi, Yonglin Qin, Li Li, Yang Chen, Liguo Jia and Mingshou Fan

Agronomy 2026, 16(11), 1033; https://doi.org/10.3390/agronomy16111033 - 22 May 2026

Potato nitrogen (N) demand varies with developmental stage rather than remaining uniformly high throughout the season. This review re-examines the “nitrate-first, ammonium-later” strategy by separating total N amount, N-supply timing, N form, and soil N transformation. Current evidence suggests that nitrate is better [...] Read more.

Potato nitrogen (N) demand varies with developmental stage rather than remaining uniformly high throughout the season. This review re-examines the “nitrate-first, ammonium-later” strategy by separating total N amount, N-supply timing, N form, and soil N transformation. Current evidence suggests that nitrate is better aligned with pre-tuber initiation because it supports stolon development and tuber set under non-excessive N supply, whereas ammonium-containing nutrition may benefit tuber bulking only when NH₄⁺ persists in the root zone and soil chemical constraints are controlled. Field responses attributed to N form are often shaped by crop N status, genotype × environment × management interactions, nitrification–denitrification dynamics, water regime, soil texture, fertilizer placement, and cultivar. We therefore interpret the strategy as a conditional, stage-oriented framework rather than a universal fertilizer prescription. Integrating NNI-/CNDC-based diagnosis, root-zone monitoring, enhanced-efficiency fertilizers, and soil-process evidence can improve synchronization between N supply and potato demand, supporting yield formation, N-use efficiency, and reduced environmental risk. Full article

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

18 pages, 1241 KB

Open AccessArticle

Drought and Flood Stress on Maize in the Black Soil Region of Northeast China and Optimized Management Strategies

by Zongfeng Chen and Xuanchang Zhang

Agronomy 2026, 16(11), 1032; https://doi.org/10.3390/agronomy16111032 - 22 May 2026

Maize production in the black soil region of Northeast China is highly vulnerable to drought and flood stress, yet stage-specific mechanisms under rain-fed conditions remain unclear. Daily meteorological records from 1951 to 2024 were used to calculate the Crop Water Surplus Deficit Index [...] Read more.

Maize production in the black soil region of Northeast China is highly vulnerable to drought and flood stress, yet stage-specific mechanisms under rain-fed conditions remain unclear. Daily meteorological records from 1951 to 2024 were used to calculate the Crop Water Surplus Deficit Index (CWSDI) for four maize phenological stages, and 2025 in situ soil moisture and temperature observations were used to derive root-zone soil water storage (SWS), soil water depletion rate (SWDR), and the soil temperature–moisture coupling index (STMI). The growing season showed a persistent water deficit (mean CWSDI = −39.19%). Drought risk was greatest during sowing–jointing (S1; CWSDI = −64.73%; drought frequency = 73.0%) and milk–maturity (S4; CWSDI = −49.84%; drought frequency = 58.1%), whereas jointing–tasseling (S2) had the highest flood frequency (13.5%). Soil hydrothermal indicators showed that S1 drought was evaporation-driven, S2 involved potential hot-wet compound stress, tasseling–milk (S3) had rapid root-zone water depletion, and S4 drought was driven by insufficient late-season precipitation. These findings show that maize water stress is a sequence of stage-specific mechanisms rather than a uniform seasonal phenomenon. We therefore propose a regulation strategy combining soil moisture conservation, rainwater harvesting, precision supplemental irrigation, and field drainage to improve maize resilience. Full article

(This article belongs to the Special Issue Land Degradation and Management Strategies: Contributing to Sustainable Agriculture)

22 pages, 19396 KB

Open AccessArticle

The Impact of Drought Events on Cropland Phenology and Vegetation Productivity in Northeast China (2001–2020)

by Zeyu Zhang, Xiaodong Na, Xubin Li, Sunai Ma and Yizhe Wang

Agronomy 2026, 16(11), 1031; https://doi.org/10.3390/agronomy16111031 - 22 May 2026

Ongoing global climate change and intensified human activities have increased the frequency and intensity of droughts, posing a serious threat to global ecosystems and agricultural sustainability. However, the seasonally differentiated effects of droughts on cropland phenology and productivity, especially in Northeast China, remain [...] Read more.

Ongoing global climate change and intensified human activities have increased the frequency and intensity of droughts, posing a serious threat to global ecosystems and agricultural sustainability. However, the seasonally differentiated effects of droughts on cropland phenology and productivity, especially in Northeast China, remain insufficiently understood, limiting the assessment of agro-ecosystem vulnerability and the development of effective adaptation strategies. In this study, the standardized precipitation evapotranspiration index (SPEI) was used to assess the frequency and severity of extreme drought in Northeast China based on run theory. Cropland phenology parameters and productivity were derived from time-series MODIS normalized difference vegetation index (NDVI), and gross primary productivity (GPP) products, which were smoothed using a Savitzky–Golay (S–G) filter. Correlation analyses were conducted to examine regional associations between SPEI-defined drought conditions and cropland phenology and productivity. Results show that: (1) Drought events occurred frequently in the central and southern parts of Northeast China, particularly in the Songnen Plain (5.22 events per decade) and the Liaohe Plain (4.89 events per decade); (2) the Songnen Plain showed significant increases (Sen’s slope > 0, p < 0.05) across all drought metrics over 2001–2020, which coincided with LOS shortening (−0.18 d a⁻¹) and GPP decline (−9.12 g C m⁻² a⁻¹); in contrast, the Sanjiang Plain exhibited slight declines (Sen’s slope, p > 0.05) in drought metrics, resulting in LOS lengthening (0.06 d a⁻¹) and GPP increases (7.84 g C m⁻² a⁻¹); and (3) drought impacts were strongly season-dependent, with autumn droughts showing a stronger association with reductions in crop productivity in local areas of Northeast China. These findings highlight the need to account for crop responses to drought events, which is essential for developing measures to cope with drought and protecting regional food security. Full article

(This article belongs to the Section Agroecology Innovation: Achieving System Resilience)

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18 pages, 978 KB

Open AccessArticle

Silver Nanoparticles Show Minimal, Transient Effects on Chemical Soil Health Indicators at Realistic Concentration in a Long-Term Laboratory Experiment

by Anastasiya A. Nikolaeva, Sofiia N. Skriabina, Olga I. Filippova, Anastasia M. Zhirkova, Natalia V. Kostina and Natalia A. Kulikova

Agronomy 2026, 16(11), 1030; https://doi.org/10.3390/agronomy16111030 - 22 May 2026

The increasing use of silver nanoparticles (AgNPs) as nanoagrochemicals raises important environmental and toxicological considerations of their usage. AgNPs influence soil microbiome functioning, which regulates essential nutrient availability. However, their effects on key chemical soil health indicators remain unclear, with existing studies limited [...] Read more.

The increasing use of silver nanoparticles (AgNPs) as nanoagrochemicals raises important environmental and toxicological considerations of their usage. AgNPs influence soil microbiome functioning, which regulates essential nutrient availability. However, their effects on key chemical soil health indicators remain unclear, with existing studies limited to concentrations ≥10-fold above predicted environmental levels. The aim of the work was to evaluate the effect of AgNPs at a realistic concentration of 10 μg/kg on the principal chemical soil health indicators, including acidity, redox potential, electrical conductivity, contents of NPK, and soil organic carbon (SOC). In addition, dissolved organic carbon and nitrogen (DOC and DON) and water-extractable elements (Al, Ca, Fe, K, Mg, Na, P, S, and Si) were also examined. The laboratory experiment was carried out for 3 months on Retisol, Chernozem, and Solonetz. AgNPs stabilised with carboxymethylcellulose (AgNP-CMC) or polyvinylpyrrolidone (AgNP-PVP) were used. AgNP-induced changes exhibited non-monotonic patterns, peaking at 2–3 months of incubation. A statistically significant effect observed across all soils following AgNPs application included only increased water-extractable Fe. In addition, AgNPs increased nitrate content 1.1–1.4-fold in Retisol and Chernozem, while available phosphorus increased 1.4-fold in Solonetz. However, changes were transient, indicating no pronounced long-term impact on soil properties. Partial Least Square (PLS) analysis revealed that chemical soil health indicators and water-extractable elements do not reliably discriminate between control soils and soils amended with AgNPs. Although our study shows that AgNPs had neither markedly negative nor positive effects on chemical soil health indicators or water-extractable element contents, future research should prioritise field trials. Model experiments under optimised microbial activity conditions limit direct extrapolation to field scenarios. Full article

(This article belongs to the Special Issue Multifunctional Nanoparticles and Nano-Enabled Pesticides, Herbicides and Fertilizers in Agricultural Applications)

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32 pages, 940 KB

Open AccessReview

Humic Substances and Plant Growth-Promoting Rhizobacteria (PGPR) as Biostimulants Against Plant-Parasitic Nematodes: Mechanisms, Synergistic Effects, and Applications

by Mehdi Beheshti, Lenka Demková and Lenka Bobuľská

Agronomy 2026, 16(11), 1029; https://doi.org/10.3390/agronomy16111029 - 22 May 2026

Plant-parasitic nematodes (PPNs) rank among the most economically destructive soilborne pathogens worldwide, causing annual crop losses estimated at USD 125–175 billion. Traditional management of plant parasitic nematodes has depended significantly on synthetic nematicides; however, increasing regulatory constraints, environmental pollution, and the rise of [...] Read more.

Plant-parasitic nematodes (PPNs) rank among the most economically destructive soilborne pathogens worldwide, causing annual crop losses estimated at USD 125–175 billion. Traditional management of plant parasitic nematodes has depended significantly on synthetic nematicides; however, increasing regulatory constraints, environmental pollution, and the rise of resistant nematode populations have generated an urgent need for sustainable alternatives. Humic substances (HS), comprising humic acids, fulvic acids, and humins derived primarily from leonardite and lignite, represent biologically active components of soil organic matter. Their different functional groups, like carboxylic, phenolic, and carbonyl groups, have direct nematicidal and nematostatic effects by stopping eggs from hatching, slowing down juvenile development, and lowering infectivity. They also indirectly improve soil structure, nutrient bioavailability, and the composition of the rhizosphere microbiome. Plant growth-promoting rhizobacteria (PGPR), particularly Bacillus spp. and Pseudomonas spp., suppress PPN populations through antibiotic biosynthesis, cuticle-degrading hydrolytic enzymes, nematostatic volatile organic compounds, and elicitation of induced systemic resistance (ISR). This review methodically analyzes the individual and synergistic processes by which HS and PGPR inhibit PPNs and enhance plant growth. Humic compounds strongly promote PGPR rhizosphere colonization, augmenting microbial metabolic activity and bioinoculant stability, hence producing combinatorial suppressive effects unattainable by either input independently. The combined HS-PGPR approach is reliable and environmentally sustainable for comprehensive nematode control, requiring multidisciplinary research to achieve global sustainable agriculture. Full article

(This article belongs to the Special Issue Soil Microbial and Nematode Communities: Diversity, Function, and Responses to Agronomic Practices)

21 pages, 1386 KB

Open AccessArticle

The Biocontrol Effect and Induced Disease Resistance Mechanism of Bacillus velezensis FJ17-4 on Cucumber Fusarium Wilt

by Chengzhong Lan, Lin Gan, Yuli Dai, Xiaofei Liu, Xiujuan Yang, Zhenhua Lei and Hongchun Ruan

Agronomy 2026, 16(11), 1028; https://doi.org/10.3390/agronomy16111028 - 22 May 2026

Fusarium wilt caused by Fusarium oxysporum f. sp. cucumerinum Owen (FOC) is a major disease affecting cucumber production. Developing environmentally friendly prevention and control strategies is essential for managing cucumber Fusarium wilt (CFW). Bacillus velezensis is a beneficial microorganism with biocontrol potential against [...] Read more.

Fusarium wilt caused by Fusarium oxysporum f. sp. cucumerinum Owen (FOC) is a major disease affecting cucumber production. Developing environmentally friendly prevention and control strategies is essential for managing cucumber Fusarium wilt (CFW). Bacillus velezensis is a beneficial microorganism with biocontrol potential against plant diseases. To investigate the biocontrol efficacy and induced disease resistance mechanism of B. velezensis FJ17-4 against CFW, the biocontrol effect of FJ17-4 on CFW was determined through indoor pot cultivation experiments, and the transcriptome of cucumber root samples treated with FJ17-4 was sequenced and analyzed by RNA-Seq technology. The results showed that CFW incidence was significantly reduced after FJ17-4 treatment, with 68.75% control efficacy, higher than that of Kasugamycin. A total of 1041 differentially expressed genes (DEGs) were induced, including 477 upregulated and 564 downregulated genes. DEGs associated with plant–pathogen interaction pathways (such as carbon metabolism, phenylpropanoid biosynthesis and amino acid biosynthesis), calcium (Ca²⁺) signaling pathway, and plant hormone signaling pathways [such as salicylic acid (SA), ethylene (ET), and jasmonic acid (JA)] were induced. These responses activated the disease resistance system of cucumber against CFW. Quantitative RT-PCR validation of 10 annotated DEGs confirmed consistent expression trends with the transcriptomic data. The results indicate that FJ17-4-induced disease resistance involves multiple genes and coordinated regulation of metabolisms, with hormone-mediated defense signaling pathways playing important roles. The transcriptome sequencing data provides a scientific basis for exploring the induced disease resistance mechanism of FJ17-4 and developing environmentally friendly biocontrol strategies. Full article

(This article belongs to the Special Issue Interaction Mechanisms Between Crops and Pathogens)

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14 pages, 969 KB

Open AccessArticle

Consumption of Susceptible and Bt-Resistant Spodoptera frugiperda Eggs by Ladybeetles and Lacewings: Preference and Functional Responses

by Luis O. Viteri, Pedro F. S. Toledo, Ana C. Fernandes, Silvana M. Orozco, Thadeu Carlos de Souza, Sarah M. Rezende, Eliseu J. Pereira, Lessando M. Gontijo and Eugênio E. Oliveira

Agronomy 2026, 16(11), 1027; https://doi.org/10.3390/agronomy16111027 - 22 May 2026

Immature ladybeetles and lacewings can thrive by feeding on eggs of lepidopteran pests, such as Spodoptera frugiperda (Smith) (Lepidoptera: Noctuidae). However, considering that the survival and fitness performances of generalist predators are heavily dependent on their ability to select suitable prey, we first [...] Read more.

Immature ladybeetles and lacewings can thrive by feeding on eggs of lepidopteran pests, such as Spodoptera frugiperda (Smith) (Lepidoptera: Noctuidae). However, considering that the survival and fitness performances of generalist predators are heavily dependent on their ability to select suitable prey, we first evaluated whether eggs of S. frugiperda strains with differential susceptibilities to Bacillus thurigiensis (Bt) toxins would affect the food preference of larvae of the ladybeetle Coleomegilla maculata DeGeer (Coleptera: Coccinellidae) and the lacewing Chrysoperla externa (Hagen, 1861) (Neuroptera: Chrysopidae). We further determined, for the first time, the functional responses of all immature phases of both predator species when fed with S. frugiperda eggs. In our choice bioassays, predator larvae were individually offered 25 eggs of each S. frugiperda strain. The number of consumed eggs was recorded hourly and replenished during each evaluation. For the functional responses, increasing densities of S. frugiperda eggs were offered to the larvae of lacewings and ladybeetles, and the number of consumed eggs was recorded 24 h after the release of the predator. Ch. externa larvae had a generalized preference for Bt-susceptible strains of eggs, while Co. maculata exhibited such a ,preference only during the first evaluation hour. Both predators displayed type II functional responses, and their consumption substantially increased during larval development. By demonstrating that lacewing and ladybeetle larvae can satisfactorily consume S. frugiperda eggs, including eggs from Bt-resistant individuals, our findings reinforce the potential of these predatory insects for the ecological management of S. frugiperda. Full article

(This article belongs to the Special Issue Application of Biological Control in Crop Protection)

28 pages, 5726 KB

Open AccessArticle

Semantic Reconstruction of Land Cover Classification in Karst Regions: A Natural-Attribute-Based NALCC Framework

by Denghong Huang, Zhongfa Zhou, Changyan Huang, Yi Li, Huanhuan Lu, Ya Li, Ying Luo and Yuexin Yu

Agronomy 2026, 16(11), 1026; https://doi.org/10.3390/agronomy16111026 - 22 May 2026

Karst regions are commonly characterized by highly interwoven bare rock–bare soil–vegetation mosaics, strong coupling between surface and subsurface processes, and pronounced geomorphic fragmentation. Conventional land cover classification systems, which are primarily organized around land use patterns or generic ecological types, are often unable [...] Read more.

Karst regions are commonly characterized by highly interwoven bare rock–bare soil–vegetation mosaics, strong coupling between surface and subsurface processes, and pronounced geomorphic fragmentation. Conventional land cover classification systems, which are primarily organized around land use patterns or generic ecological types, are often unable to accurately represent these key surface components and their roles in ecological processes. From the perspective of reconstructing classification semantics, this study proposes a Natural-Attribute-Based Karst Land Cover Classification framework (NALCC). The framework takes bare rock, bare soil, vegetation, water bodies, and impervious surfaces as primary classes, and further develops a hierarchical system consisting of subclasses, attribute labels, hierarchical coding, multi-scale organization, and parameter mapping with ecosystem service models. Compared with conventional land cover classification systems, the innovation of this framework lies not in increasing the number of categories, but in reconstructing the semantic organization of classification units, so that land cover classification can move beyond surface-type description toward the expression of process-sensitive information. The classification objective of NALCC is not to develop a universal land cover classification system, but to establish a process-oriented classification framework for ecosystem service monitoring, rocky desertification diagnosis, and governance zoning in karst regions, which can directly represent key surface components and their ecological-process significance. However, its regional transferability and mapping performance still need to be further validated through case studies in representative areas. Full article

(This article belongs to the Topic Large-Scale and Long-Term Land Use and Land Cover Mapping)

21 pages, 4218 KB

Open AccessArticle

Effects of Nitrogen and Phosphorus Addition on the Community Structure and Diversity of Mesofaunal Soil Arthropods in Degraded Sophora alopecuroides Grassland

by Luyao Liu, Dong Cui, Shuqi Liu, Zhicheng Jiang, Yunhao Wu, Zezheng Liu, Yaxin Han, Jinfeng Guo and Guanghui Lü

Agronomy 2026, 16(11), 1025; https://doi.org/10.3390/agronomy16111025 - 22 May 2026

Understanding how soil arthropod communities respond to nutrient enrichment is important for assessing grassland ecosystem health, but such knowledge remains limited for degraded Sophora alopecuroides grasslands. To address this gap, a two-year field experiment was conducted in the Tuhulusu grassland (Xinjiang, China) with [...] Read more.

Understanding how soil arthropod communities respond to nutrient enrichment is important for assessing grassland ecosystem health, but such knowledge remains limited for degraded Sophora alopecuroides grasslands. To address this gap, a two-year field experiment was conducted in the Tuhulusu grassland (Xinjiang, China) with four treatments: nitrogen (N) addition, phosphorus (P) addition, combined N and P (NP) addition, and an unamended control (CK). Soil arthropod communities and environmental variables were monitored during the flowering, maturity, and senescence stages of S. alopecuroides. Across all treatments, three taxa—Oppiidae, Hypoaspidae, and Rhagidiidae—remained dominant, indicating wide ecological tolerance. Nutrient addition significantly altered arthropod individual density (response variable) and soil properties, including total phosphorus, available phosphorus, nitrate−N, ammonium−N, and pH (all p < 0.001), and these effects were strongly linked to plant phenology. The dominance, evenness, and Shannon diversity indices ranked as NP > CK > P > N. The key environmental drivers varied by treatment: total phosphorus and soil moisture under N addition, soil moisture under P and NP addition, and pH and electrical conductivity under CK. Collectively, these findings provide evidence that soil arthropod communities in S. alopecuroides grasslands are sensitive to nutrient enrichment in a phenology−dependent manner, with soil moisture content emerging as a critical limiting factor under nutrient−added conditions. Full article

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

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16 pages, 8647 KB

Open AccessArticle

Soybean Intercropping Improves Bacterial Community and Nutrient Status in Soil of Citrus Orchards

by Sheng Cao, Mengyun Ouyang, Shuizhi Yang, Can Yang, Mingming Zhao, Jianli Mou and Bin Zeng

Agronomy 2026, 16(11), 1024; https://doi.org/10.3390/agronomy16111024 - 22 May 2026

Soil microbes play pivotal roles in nutrient cycling and ecosystem functioning across diverse farmland systems. Orchard grass coverage has been demonstrated to effectively alter microbial community structure and promote nutrient cycling. However, the effects of soybean intercropping on soil bacterial community characteristics and [...] Read more.

Soil microbes play pivotal roles in nutrient cycling and ecosystem functioning across diverse farmland systems. Orchard grass coverage has been demonstrated to effectively alter microbial community structure and promote nutrient cycling. However, the effects of soybean intercropping on soil bacterial community characteristics and nutrient contents in citrus orchards remain poorly understood. In this study, a field experiment was conducted in a citrus orchard involving three planting patterns: clean tillage (CT), natural grass (NG), and soybean intercropping (SI). The physicochemical properties and bacterial community structure of the topsoil (0–40 cm depth) were determined. Results showed that compared with CT, NG and SI significantly increased cation exchange capacity (CEC), soil organic matter (SOM), alkali-hydrolyzable nitrogen (AN), and available potassium (AK). SI further elevated soil pH and available phosphorus (AP) relative to CT and NG. Bacterial diversity ranked SI > NG > CT, with PCoA showing lower community variation under SI. A total of 31 bacterial phyla were detected in the citrus orchard soil, with Cyanobacteria (17.20~40.81%), Proteobacteria (15.04~24.19%), Acidobacteriota (8.95~14.66%), and Chloroflexi (3.93~21.13%) identified as the dominant phyla. SI enriched Cyanobacteria and Proteobacteria but reduced Acidobacteriota, Chloroflexi, and Actinobacteriota. Mantel tests confirmed CEC and SOM as key drivers of bacterial community structure. Overall, soybean intercropping improves soil microecology and exhibits great potential for soil quality improvement in citrus orchards under local conditions. Full article

(This article belongs to the Special Issue Sustainable Soil Fertility Management Through Organic Fertilizers, Green Manures, and Recycled Resources)

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21 pages, 15399 KB

Open AccessArticle

Diagnosis of Soil Quality in Barley Farmlands in Central and Northern Hubei Province

by Yu Zhou, Chengyang Wang, Yuxi Tong, Qingyu Cao, Xiaoqin Fu, Liangyu Liu, Genlou Sun and Xifeng Ren

Agronomy 2026, 16(11), 1023; https://doi.org/10.3390/agronomy16111023 - 22 May 2026

Soil quality is a critical determinant of crop productivity. This study assessed the soil quality of 61 barley farmlands in central and northern Hubei Province based on ten soil chemical properties: pH, soil organic matter (SOM), ammonium nitrogen (NH₄⁺-N), nitrate [...] Read more.

Soil quality is a critical determinant of crop productivity. This study assessed the soil quality of 61 barley farmlands in central and northern Hubei Province based on ten soil chemical properties: pH, soil organic matter (SOM), ammonium nitrogen (NH₄⁺-N), nitrate nitrogen (NO₃⁻-N), hydrolyzable nitrogen (HN), available phosphorus (AP), available potassium (AK), exchangeable calcium (Exc-Ca), exchangeable magnesium (Exc-Mg), and available sulfur (AS). A total of 68.85% of the farmlands were acidic (pH < 6.5). The average levels of SOM, NH₄⁺-N, NO₃⁻-N, and HN were deficient, while AP was moderate, according to the Second State Soil Survey of China (SSSSC). AK, Exc-Ca, Exc-Mg, and AS were, on average, at moderate-to-abundant levels. Differences in preceding crops led to significant differences in pH and SOM between paddy and dryland fields. A minimum data set was established using six soil properties (HN, AS, AK, Exc-Ca, Exc-Mg, and NH₄⁺-N) to calculate the soil quality index (SQI). SQI ranged from 0.27 to 0.69, with an average of 0.45, indicating overall low soil quality in the region. Both accuracy importance and R²-weighted importance revealed that HN was the most influential factor driving SQI variation among the soil properties examined. This study elucidates the status of soil nutrients, offering a diagnostic basis for developing targeted fertilization strategies for barley in this region. Full article

(This article belongs to the Special Issue Effects of Agrotechnical Factors and Farming Systems on Soil Properties and Plant Productivity—2nd Edition)

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23 pages, 3376 KB

Open AccessArticle

Tillage–Weed Interactions and Hybrid Effects Drive Maize Yield Stability Under Irrigated Chernozem Conditions

by Traian Ciprian Stroe, Ana-Maria Stoenescu, Liliana Miron, Dan Răzvan Popoviciu, Gabriela Ianculescu and Liliana Panaitescu

Agronomy 2026, 16(11), 1022; https://doi.org/10.3390/agronomy16111022 - 22 May 2026

Maize productivity in Southeastern Europe is increasingly affected by climatic variability, necessitating agronomic strategies to maintain yield under irrigated conditions. This study evaluated the effects of conventional tillage, minimum tillage, and no-tillage on maize yield, yield components, and weed dynamics, and analyzed the [...] Read more.

Maize productivity in Southeastern Europe is increasingly affected by climatic variability, necessitating agronomic strategies to maintain yield under irrigated conditions. This study evaluated the effects of conventional tillage, minimum tillage, and no-tillage on maize yield, yield components, and weed dynamics, and analyzed the interaction between tillage intensity and hybrid performance under irrigated cambic chernozem conditions in Southeastern Romania. A three-year field experiment (2023–2025) was conducted as a randomized complete block design with three replications using three maize hybrids (P0900, P0937, and P1441) under sprinkler irrigation. Grain yield, kernel weight per ear, kernel number per ear, thousand-kernel weight, plant density, and weed density were analyzed using ANOVA, linear mixed models, and regression analysis. Grain yield ranged from 10.66 to 11.46 t ha⁻¹ across years, with the hybrid exerting the strongest effect on all productivity parameters. P0900 recorded the highest yield (12.43 t ha⁻¹) and the lowest associated weed density. Weed density increased from 207.44 plants m⁻² under conventional tillage to 266.11 plants m⁻² under no-tillage and was negatively associated with yield components and grain yield. Significant tillage × weed-density interactions indicated steeper productivity declines in reduced-tillage systems, particularly no-tillage. The results suggest that the agronomic performance of conservation-oriented tillage systems under irrigation depends strongly on hybrid adaptability and effective weed-management strategies. Full article

(This article belongs to the Special Issue Synergistic Cultivation of Energy Crops: Maximizing Biomass Yield and Quality via Physiological, Agronomic and Technological Innovations)

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14 pages, 649 KB

Open AccessArticle

Evaluation of Nutrient Tracking Tool (NTT) in Predicting Corn Yield Under Various Management Practices

by Kennedi Harris and Ali Saleh

Agronomy 2026, 16(10), 1021; https://doi.org/10.3390/agronomy16101021 - 21 May 2026

The Nutrient Tracking Tool (NTT) is a free and user-friendly modeling program developed by the Texas Institute for Applied Environmental Research (TIAER) at Tarleton State University in cooperation with the USDA Office of Environmental Markets. NTT simulates various cropping systems to evaluate management [...] Read more.

The Nutrient Tracking Tool (NTT) is a free and user-friendly modeling program developed by the Texas Institute for Applied Environmental Research (TIAER) at Tarleton State University in cooperation with the USDA Office of Environmental Markets. NTT simulates various cropping systems to evaluate management practices that optimize crop production while improving water quality and quantity. The objective of this study is to evaluate the capability of NTT to predict corn yield under different agricultural management scenarios. To assess model performance, 45 management scenarios from three field studies conducted in Iowa, Colorado, and Kansas were replicated in NTT. These scenarios included variations in nutrient sources and application rates, tillage practices, seeding rates, and irrigation management. Field data, including location, slope, planting dates, tillage practices, fertilization rates, and soil properties, were entered into NTT, and simulated crop yields were compared with measured values reported in the studies. Results showed strong agreement between measured and predicted corn yields across the evaluated scenarios. For example, the average measured yield of combined strip-tillage and manure treatment reported by Al-Kaisi and Kwaw-Mensah was 9.48 Mg ha, while NTT predicted 9.45 Mg ha. Similarly, for Halvorson et al., NTT predicted a yield of 8.06 Mg ha, compared with the measured yield of 8.23 Mg ha. Overall, the results indicate that NTT can reliably predict corn yield under a range of management practices, demonstrating its potential as a decision-support tool for agricultural management. Full article

(This article belongs to the Special Issue Modeling for Risk Assessment of Crop Health and Yield Prediction)

24 pages, 1260 KB

Open AccessArticle

Predicting Greenhouse Gas Emissions in Agriculture: Production Dynamics, Labor Productivity, and Implications for Climate-Neutral Farming Systems

by Anca Antoaneta Vărzaru

Agronomy 2026, 16(10), 1020; https://doi.org/10.3390/agronomy16101020 - 21 May 2026

This study explicitly assesses how crop and livestock production, along with real labor productivity, affect greenhouse gas emissions in agriculture across the European Union (EU), considering both per capita and total emissions. Using annual Eurostat data for EU Member States from 2008 to [...] Read more.

This study explicitly assesses how crop and livestock production, along with real labor productivity, affect greenhouse gas emissions in agriculture across the European Union (EU), considering both per capita and total emissions. Using annual Eurostat data for EU Member States from 2008 to 2024, the research applies multiple regression models and a multivariate General Linear Model (GLM) to evaluate structural relationships, complemented by Holt exponential smoothing and ARIMA models to analyze temporal dynamics and generate forecasts. The empirical results indicate that crop and livestock production have a statistically significant positive effect on emissions, while real labor productivity has a significant negative impact. The models explain over 92% of the variation in total emissions and over 95% of the variation in per capita emissions, confirming strong explanatory power. Forecasts show continued growth in agricultural output but a declining trend in per capita emissions, primarily driven by productivity improvements. These findings demonstrate that improvements in labor efficiency and technological progress can partially offset the environmental pressures associated with increased agricultural production. The study concludes that achieving climate-neutral agriculture in the EU is feasible through sustained productivity gains and innovation-driven transformation. Full article

(This article belongs to the Special Issue Enhancing Crop Productivity and Mitigating Environmental Footprints in Sustainable Agriculture)

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24 pages, 602 KB

Open AccessReview

Integrating Envirotyping and Phenomics for AI-Enabled Multi-Environment Genomic Prediction in Crop Breeding

by Xiongwei Liang, Shaopeng Yu, Yongfu Ju, Yingning Wang and Dawei Yin

Agronomy 2026, 16(10), 1019; https://doi.org/10.3390/agronomy16101019 - 21 May 2026

Genomic prediction is now routine in crop improvement, but its main bottleneck has shifted from marker density to environmental complexity. Breeders rarely need predictions for one fixed environment; they need to rank genotypes across target populations of environments that differ in weather, soils, [...] Read more.

Genomic prediction is now routine in crop improvement, but its main bottleneck has shifted from marker density to environmental complexity. Breeders rarely need predictions for one fixed environment; they need to rank genotypes across target populations of environments that differ in weather, soils, management, and stress timing. This makes genotype-by-environment interaction a primary breeding problem rather than a secondary statistical nuisance. This review examines how genomic, environmental, and phenomic information can be integrated to improve multi-environment prediction in crop breeding pipelines. The review is narrative rather than PRISMA-style, but the literature search and selection logic were structured and explicitly defined. Peer-reviewed English-language studies were identified through structured searches of Web of Science Core Collection and Scopus, supplemented by backward citation screening, with emphasis on literature published from January 2023 to March 2026. Four conclusions emerge. First, environmental information is most useful when it is developmentally aligned, biologically interpretable, and matched to the target population of environments. Second, strong structured statistical baselines remain highly competitive, especially in moderate-sized or highly unbalanced datasets, whereas gains from more flexible machine-learning and deep-learning approaches are most evident in large, sparse, heterogeneous, and multimodal settings. Third, phenomic markers often improve prediction for complex traits, especially yield, because they capture realized crop responses not fully represented by markers alone. Fourth, practical value depends less on isolated gains in predictive accuracy than on evaluation under realistic deployment scenarios, including untested genotype and untested environment settings. Progress therefore requires transparent reporting, benchmark design, stage-aware envirotyping, multimodal integration, uncertainty reporting, and cost-aware deployment. Full article

(This article belongs to the Special Issue Precision Assistance for Crop Genetic Improvement: Big Data, Artificial Intelligence and Machine Learning)

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19 pages, 5216 KB

Open AccessArticle

Pre-Symptomatic Identification of CMV and PVX Infection in Nicotiana benthamiana Using Spectral–Spatial Fusion of Hyperspectral Imaging

by Chi Zhang, Linfeng Su, Jiacheng Sun and Juan Zhao

Agronomy 2026, 16(10), 1018; https://doi.org/10.3390/agronomy16101018 - 21 May 2026

Early detection of cucumber mosaic virus (CMV) and potato virus X (PVX) infection at the pre-symptomatic stage is essential for timely disease management and for limiting viral spread. Conventional molecular assays are accurate, but they generally require destructive sampling and are time-consuming. To [...] Read more.

Early detection of cucumber mosaic virus (CMV) and potato virus X (PVX) infection at the pre-symptomatic stage is essential for timely disease management and for limiting viral spread. Conventional molecular assays are accurate, but they generally require destructive sampling and are time-consuming. To enable rapid and non-destructive identification of these two viruses before visible symptom development, Nicotiana benthamiana seedling leaves were used as experimental materials, and CMV and PVX were selected as target viruses. A hyperspectral dataset of healthy, CMV-infected, and PVX-infected pre-symptomatic samples was constructed and validated by RT-PCR. After spectral preprocessing, eight selected wavelengths were identified and used to develop a 1D-CNN model, a MobileNetV3 model, and a spectral–spatial dual-branch fusion model. The 1D-CNN achieved an accuracy of 0.9074, whereas MobileNetV3 achieved 0.6835. The feature-level fusion model performed best, with an accuracy of 0.944, a precision of 0.945, a recall of 0.944, and an F1-score of 0.944. These results suggest that spectral information provides the primary discriminative basis, while image information offers complementary spatial and textural features for early non-destructive detection of plant viruses. Full article

(This article belongs to the Special Issue Current Status and Applications of Remote Sensing in Plant Pest and Disease Detection)

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