Search Results (556)

Since the outbreak of the Russia–Ukraine conflict in 2022, Ukraine’s agricultural production has faced significant disruption, leading to widespread cropland abandonment. These croplands were abandoned at different stages, primarily due to war-related destruction and displacement of people. Existing methods for detecting abandoned cropland fail to account for crop type differences and distinguish abandonment stages, leading to inaccuracies. Therefore, this study proposes a novel framework combining crop-type classification with the Bias-weighted Time-Weighted Dynamic Time Warping (BTWDTW) method, distinguishing between sowing and harvest abandonment. Additionally, the proposed framework improves accuracy by integrating a more nuanced analysis of crop-specific patterns, thus offering more precise insights into abandonment dynamics. The overall accuracy of the proposed method reached 88.9%. The results reveal a V-shaped trajectory of cropland abandonment, with abandoned areas increasing from 28,184 km² in 2022 to 33,278 km² in 2024, with 2023 showing an abandoned area of 24,007.65 km². Spatially, about 70% of sowing abandonment occurred in high-conflict areas, with hotspots of unplanted abandonment shifting from southern Ukraine to the northeast, while unharvested abandonment was observed across the entire country. Significant variations were found across crop types, with maize experiencing the highest rate of unharvested abandonment, while wheat exhibited a more balanced pattern of sowing and harvest losses. The proposed method and results provide valuable insights for post-conflict agricultural recovery and decision-making in recovery planning. Full article

Crop residue management and soil tillage (CRM and ST) are key steps in agricultural production. The effects of different CRM and ST modes on the quality of seedbed, seeding, and harvest yield are not well determined. In this study, the system of maize (Zea mays L.)–soybean (Glycine max (L.) Merr) rotation under ridge-tillage in the semi-arid regions of Northeast China was chosen as the study conditions. Four modes were investigated: deep tillage and seeding (DT and S), stubble field and no-tillage seeding (SF and NTS), three-axis rotary tillage and seeding (TART and S), and shallow rotary tillage and seeding (SRT and S). Results show that the DT and S mode produced the best quality of seedbed and seeding. Among the conservation tillage modes, the SRT and S mode produced the shortest average length of roots and straw, the best uniformity of their distribution in the seedbed, and the highest soybean yield. Both the SRT and S and SF and NTS modes yielded a higher net profit as their cost-effectiveness. When considering only the quality of seedbed and seeding under conservation tillage as a prerequisite, it can be concluded that the SRT and S mode is both advantageous and sustainable. Full article

Soil pH strongly influences phosphorus (P) availability and, consequently, plant response to P fertilization. This study aimed to assess how soil pH affects P availability, uptake, and fertilizer use efficiency in maize (Zea mays L.) grown under controlled conditions. A pot experiment was conducted using three soil pH_KCl levels (4.2, 5.2, and 6.4) and five P application doses (0, 0.5, 1, 1.5, and 2 g P pot⁻¹). Each pot contained 10 kg of soil. Results showed that soil P concentration after harvest increased with both P dose and pH, with the highest values recorded at pH 6.4. Maize grain and straw yields responded differently to P fertilization depending on pH. At pH 5.2, the highest grain yield and agronomic efficiency (AE) were observed at the 0.5 g P dose, while higher doses led to yield reductions. At pH 4.2, P fertilization significantly increased both grain yield and P uptake, but excessive doses reduced yields. In contrast, at pH 6.4, yield increased steadily with rising P doses, though AE and apparent phosphorus recovery (APR) were lowest. The highest APR was observed at pH 4.2 and the lowest at pH 6.4. Overall, the results suggest that optimal maize response to P fertilization occurs near pH 5.2, where both yield and efficiency indices peak. Full article

Pesticide residues pose risks to the environment and human health. Little is known about how tillage and straw management affect herbicide behavior in soil. This study investigated the effects of different tillage practices under varying straw incorporation scenarios on the degradation of five commonly used herbicides in a long-term experimental field located in the maize belt of Siping, Jilin Province. Post-harvest soil samples were analyzed for residual herbicide concentrations and basic soil physicochemical properties. A human health risk assessment was conducted, and a controlled incubation experiment was carried out to evaluate herbicide degradation dynamics under three management systems: straw incorporation with traditional rotary tillage (ST), straw incorporation with strip tillage (SS), and no-till without straw (CK). Residual concentrations of atrazine ranged from not detected (ND) to 21.10 μg/kg (mean: 5.28 μg/kg), while acetochlor showed the highest variability (2.29–120.61 μg/kg, mean: 25.26 μg/kg). Alachlor levels were much lower (ND–5.71 μg/kg, mean: 0.34 μg/kg), and neither nicosulfuron nor mesotrione was detected. Soil organic matter (17.6–20.89 g/kg) positively correlated with available potassium and acetochlor residues. Health risk assessments indicated negligible non-cancer risks for both adults and children via ingestion, dermal contact, and inhalation. The results demonstrate that tillage methods significantly influence herbicide degradation kinetics, thereby affecting environmental persistence and ecological risks. Integrating straw with ST or SS enhanced the dissipation of atrazine and mesotrione, suggesting their potential as effective residue mitigation strategies. This study highlights the importance of tailoring tillage and straw management practices to pesticide type for optimizing herbicide fate and promoting sustainable agroecosystem management. Full article

Fusarium spp. represent a critical threat to maize production and food safety due to their mycotoxin production. This study introduces a refined molecular identification protocol integrating four genomic regions—ITS1, IGS, TEF-1α, and β-TUB—for robust species differentiation of Fusarium spp. isolates from post-harvest maize in Bulgaria. The protocol enhances species resolution, especially for closely related taxa within the Fusarium fujikuroi species complex (FFSC). A newly optimized multiplex PCR strategy was developed using three primer sets, each designed to co-amplify a specific pair of toxigenic genes: fum6/fum8, tri5/tri6, and tri5/zea2. Although all five genes were analyzed, they were detected through separate two-target reactions, not in a single multiplex tube. Among 17 identified isolates, F. proliferatum (52.9%) dominated, followed by F. verticillioides, F. oxysporum, F. fujikuroi, and F. subglutinans. All isolates harbored at least one toxin biosynthesis gene, with 18% co-harboring genes for both fumonisins and zearalenone. This dual-protocol approach enhances diagnostic precision and supports targeted mycotoxin risk management strategies. Full article

This study investigates the influence of agricultural mechanization on maize productivity in Tanzania’s Ruvuma region, a major maize-producing area vital to national food security. It addresses gaps in understanding the cumulative effects of mechanization across the maize production cycle and identifies region-specific barriers to adoption among smallholder farmers. Focusing on five key stages—land preparation, planting, plant protection, harvesting, and drying—this research evaluated mechanization uptake at each stage and its relationship with yield disparities. Statistical analyses using Python libraries included regression modeling, ANOVA, and hypothesis testing to quantify mechanization–yield relationships, controlling for farm size and socioeconomic factors, revealing a strong positive correlation between mechanization and maize yields (r = 0.86; p < 0.01). Mechanized land preparation, planting, and plant protection significantly boosted productivity (β = 0.75–0.35; p < 0.001). However, harvesting and drying mechanization showed negligible impacts (p > 0.05), likely due to limited adoption by smallholders combined with statistical constraints arising from the small sample size of large-scale farms (n = 20). Large-scale farms achieved 45% higher yields than smallholders (2.9 vs. 2.0 tons/acre; p < 0.001), reflecting systemic inequities in access. These inequities are underscored by the barriers faced by smallholders, who constitute 70% of farmers yet encounter challenges, including high equipment costs, limited credit access, and insufficient technical knowledge. This study advances innovation diffusion theory by demonstrating how inequitable resource access perpetuates low mechanization uptake in smallholder systems. It underscores the need for context-specific, equity-focused interventions. These include cooperative mechanization models for high-impact stages (land preparation and planting); farmer training programs; and policy measures such as targeted subsidies for harvesting equipment and expanded rural credit systems. Public–private partnerships could democratize mechanization access, bridging yield gaps and enhancing food security. These findings advocate for strategies prioritizing smallholder inclusion to sustainably improve Tanzania’s maize productivity. Full article

Aflatoxins, toxic secondary metabolites produced primarily by Aspergillus flavus and Aspergillus parasiticus, pose significant risks to food safety, public health, and global trade. These mycotoxins contaminate staple crops such as maize and peanuts, particularly in warm and humid regions, leading to economic losses and severe health effects, including hepatocellular carcinoma, immune suppression, and growth impairment. In addition to aflatoxins, Aspergillus species produce other toxic metabolites such as ochratoxin A, sterigmatocystin, and cyclopiazonic acid, which are associated with nephrotoxic, carcinogenic, and neurotoxic effects, respectively. This review provides a comprehensive analysis of aflatoxin toxicity, mitigation strategies, and chemical detection methods. The toxicity of aflatoxins is discussed in relation to their biochemical mechanisms, carcinogenicity, and synergistic effects with other mycotoxins. Various mitigation approaches, including pre-harvest biocontrol, post-harvest storage management, and novel detoxification methods such as enzymatic degradation and nanotechnology-based interventions, are evaluated. Furthermore, advances in aflatoxin detection, including chromatographic, immunoassay, and biosensor-based methods, are explored to improve regulatory compliance and food safety monitoring. This review underscores the need for integrated management strategies and global collaboration to reduce aflatoxin contamination and its associated health and economic burdens. Future research directions should focus on genetic engineering for resistant crop varieties, climate adaptation strategies, and improved risk assessment models. Full article

This paper offers an exhaustive review of various pivotal aspects of forage whole-plant maize silage. It commences with an exploration of the foundational elements of planting, including the growing environment, variety selection, planting techniques, management practices, and harvesting considerations. The paper assesses the nutritional value of maize silage, its effects on animal health, and its current applications in livestock farming. Additionally, it elucidates the principles of fermentation, pathogen control, and the impact of fermentation technology on silage quality. The paper also discusses utilization strategies and technological advancements. A historical perspective is provided, alongside an analysis of current challenges, opportunities, and the global market positioning of maize silage. Furthermore, the paper delves into future prospects by addressing sustainable development strategies, adaptation to climate change, and ethical and economic controversies. The primary aim is to serve as a comprehensive reference for further research, production practices, and industrial chain development in the domain of forage whole-plant maize silage. Full article

Unlike traditional yield mapping, which is conducted using costly yield sensors mounted on combine harvesters to collect post-harvest data, yield potential prediction using remote sensing data is considered a low-cost alternative. In this study, an effort was made to address the research gap concerning the effectiveness of phenological modeling in crop yield potential prediction using machine learning. Combinations of seven vegetation indices from Sentinel-2 imagery and seven phenology metrics were evaluated for the prediction of maize and soybean yield potential. Ground truth yield data were provided by the Quantile Loss Domain Adversarial Neural Network (QDANN) database, with 1000 samples randomly selected per year from 2019 to 2022 for Iowa and Illinois. Four machine learning algorithms were tested: random forest (RF), support vector machine regression (SVM), multivariate adaptive regression splines (MARS), and Bayesian regularized neural networks (BRNNs). Across all evaluations, RF was found to outperform the other models in both cross-validation and final model accuracy metrics. Vegetation index values at peak of season (POS) and phenological timing, expressed as the day of year (DOY) of phenological events, were identified as the most influential covariates for predicting yield potential in particular years for both maize and soybean. Full article

Estimating the actual evapotranspiration (ET_{c act}) of cropland in arid areas, exploring the time trend, and analyzing periodic variation are the key to long-term assessment of water resource availability and regional drought. The Penman formula has a strong ability to characterize reference crop evapotranspiration (ET_o). However, the application of this formula may be limited in the absence of a complete set of climate data. While previous studies have investigated K_{c act} in China, few have employed localized K_c values to systematically analyze long-term periodic fluctuations in ET_{c act} under climate variability conditions. Therefore, this study aimed to evaluate the applicability of nine ET_o estimation models in the Loess Plateau of China, calculate actual crop coefficients (K_{c act}) for spring maize and winter wheat, and examine the temporal trend and periodicity of ET_{c act} for long-term (1961–2018) continuous cropping of spring maize and winter wheat in the study area. The Mann–Kendall test and continuous wavelet transform (CWT) were used to obtain the temporal trend and periodicity of ET_{c act}. The results were as follows: (1) Priestley–Taylor (Prs–Tylr), based on radiation, and the 1985 Hargreaves–Samani (Harg), based on temperature, can be used when meteorological data are limited. It should be noted that among the models evaluated in this study, except for FAO56-PM, only the Harg equation is compatible with K_c-ET_o due to established conversion factors. (2) The K_{c act} of spring maize at the seeding–jointing stage and the earning–filling stage was 12% and 10% lower than the value recommended by FAO, respectively. For K_{c act} of winter wheat, it was 65% higher, 31% lower, and 85% higher than the FAO experience values in the rejuvenation–jointing stage, heading–grouting stage, and grouting–harvest stage. (3) Winter wheat, through its ET_{c act} cycle synchronized with precipitation and excellent water balance, can effectively alleviate regional drought. It is recommended to be included in the promotion of drought resistance policies. Full article

In response to the limited research on silage maize classification in China and the lack of data support for refined agricultural and livestock management, this study proposes a Temporal Difference-based Silage Maize Identification Model (TempDiff-SMID) using the Google Earth Engine (GEE) platform. By analyzing the phenological phases of silage maize and grain maize, we identified their critical harvest periods and established decision rules for classifying silage maize, grain maize, and other land cover types. Preprocessed Sentinel-2 imagery was smoothed using the Whittaker filter to construct the TempDiff-SMID model. After iterative threshold optimization, the decision tree model achieved an overall accuracy of 0.9291 and a Kappa coefficient of 0.8923, indicating robust classification performance. The user’s accuracies for silage maize, grain maize, and other land cover types were 0.9216, 0.9219, and 0.9404, respectively, while the producer’s accuracies reached 0.94, 0.9008, and 0.9467, demonstrating minimal omission and commission errors across all categories. Furthermore, the F1 scores for silage maize, grain maize, and other land cover types were 0.9307, 0.9112, and 0.9435, respectively, confirming the effectiveness of the TempDiff-SMID framework in leveraging harvest time differences for accurate silage maize identification. To evaluate performance, we compared the TempDiff-SMID with the RF Model for Silage Maize Classification (SMRF). The TempDiff-SMID outperformed the SMRF in both overall accuracy (0.9043 vs. 0.9291) and Kappa coefficient (0.8511 vs. 0.8923), while also providing an intuitive representation of spectral and phenological differences between silage maize and grain maize. When applied to multi-year data, TempDiff-SMID demonstrated strong temporal transferability, achieving overall accuracies of 0.8621 (2022) and 0.8816 (2021), thereby confirming its robustness across growing seasons. The proposed model offers simplicity in methodology, clear interpretability, and efficient deployment, making it a practical tool for agricultural and livestock management systems. Its ability to rapidly adapt to new regions or years underscores its significance in supporting precision agriculture and sustainable farming practices. Full article

Maize (Zea mays L.) relies heavily on nitrogen and phosphorus inputs, typically supplied through organic and inorganic fertilizers. However, excessive agrochemical use threatens soil fertility and environmental health. Sustainable alternatives, such as poultry manure (PM) and plant growth-promoting rhizobacteria (PGPR), offer promising solutions. This study examines the effects of a phytobiotic bacterial formulation (PHY), composed of Bacillus subtilis and Microbacterium sp., applied alone and in combination with PM, on maize’s rhizosphere bacteriobiome across key growth stages. Field trials included four treatments: a control, PHY-coated seeds, PM, and combined PHY_PM. The results show that early in development, the PM-treated rhizospheres increased the abundance of beneficial genera such as Sphingomonas, Microvirga, and Streptomyces, though levels declined in later stages. The PHY_PM-treated roots in the seedling phase showed a reduced abundance of taxa like Chryseobacterium, Pedobacter, Phyllobacterium, Sphingobacterium, and Stenotrophomonas, but this effect did not persist. In the PM-treated roots, Flavisolibacter was significantly enriched at harvesting. Overall, beneficial bacteria improved microbial evenness, and the PHY_PM treatment promoted bacterial diversity and maize growth. A genome analysis of the PHY strains revealed plant-beneficial traits, including nutrient mobilization, stress resilience, and biocontrol potential. This study highlights the complementarity of PM and PGPR, showing how their integration reshapes bacteriobiome and correlates with plant parameters in sustainable agriculture. Full article

This study evaluates various strains of soil bacterial for use in the development of new biopreparations. Mesophilic spore-forming bacteria were isolated from cultivated soil and analysed for their enzymatic activity, ability to decompose crop residues, and antagonistic properties towards selected phytopathogens. Notably, this is the first cytotoxicity assessment of soil bacterial metabolites on Spodoptera frugiperda Sf-9 (fall armyworm). Bacillus subtilis, Bacillus licheniformis, Bacillus velezensis, Paenibacillus amylolyticus, and Prestia megaterium demonstrated the highest hydrolytic potential for the degradation of post-harvest residues from maize, winter barley, and triticale. They exhibited antimicrobial activity against at least three of the tested phytopathogens and demonstrated the ability to solubilize phosphorus. Metabolites of B. licheniformis (IC50 = 8.3 mg/mL) and B. subtilis (IC50 = 144.9 mg/mL) were the most cytotoxic against Sf-9. We recommend the use of the tested strains in industrial practice as biocontrol agents, plant growth biostimulants, crop residue decomposition stimulants, and bioinsecticides. Future studies should focus on assessing the efficacy of using these strains under conditions simulating the target use, such as plant microcosms and greenhouses and the impact of these strains on the abundance and biodiversity of native soil microbiota. This research can serve as a model procedure for screening other strains of bacteria for agricultural purposes. Full article

The tropical house cricket (Gryllodes sigillatus) can convert organic diets formulated from weeds and agro by-products into high-quality biomass. This study assessed the potential of diets developed from weeds and agro by-products as a feed source for G. sigillatus. We compared the development and nutritional value of crickets fed these alternative diets with control crickets fed chicken feed. Ten different diets with varying protein contents were used, including chicken feed (Control) with a protein content of 215 g/Kg dry matter (DM) basis), Cassava–Sugar Diet (250 g/Kg DM protein) Desmodium–Bran Diet (245 g/Kg DM protein), Morning Glory–Bean Diet (240 g/Kg DM protein), Morning Glory–Cassava Diet (235 g/Kg DM protein), Morning Glory–Cowpea Diet (225 g/Kg DM protein), Mixed Weed–Bran Diet (Optimal) (215 g/Kg DM protein) Cassava–Gallant Soldier Diet (200 g/Kg DM protein), Wheat–Bran Diet (145 g/Kg DM protein), and Maize–Cassava Diet (135 g/Kg DM protein). The weight and length of the crickets were measured for 9 weeks from day 1 after hatching to day 56. Then, the crickets were harvested and analyzed for dry matter, crude protein, fat, ash, fiber, minerals, and fatty acid composition. Cricket developmental time, survival rate, weight and length, yield, proximate components, and mineral and fatty acids differed depending on the diet provided. The Mixed Weed–Bran Diet (Optimal) resulted in the crickets developing faster (48.8 days), with a higher survival rate (88.1%), greater adult length (19.2 cm) and weight (0.44 g), and a nutrition content richer in minerals and unsaturated fatty acids when compared to other treatments. Oleic, linoleic, and palmitic acids were the major fatty acids. The highest protein content (64.4 g/100 g) was observed in the Mixed Weed–Bran Diet (Optimal) and Morning Glory–Cassava Diet treatments, while the Maize–Cassava Diet treatment crickets possessed the highest quantities of fats (19.1 g/100 g) and ash (15.4 g/100 g). The fatty acid profile of G. sigillatus revealed the cricket to have high unsaturated fatty acids except in crickets fed Morning Glory–Cowpea Diet and Wheat–Bran Diet. Generally, G. sigillatus grew best and had the most nutritious body composition on the Mixed Weed–Bran Diet (Optimal). The findings indicate that diets developed from weeds and agro by-products have great potential to be used as an alternative feed source for crickets and are capable of replacing expensive chicken feed, enhancing the circular farming potential of insect farming. Full article

Crop rotation and simplified tillage affect soil properties and consequently crop yields. The use of heavy machinery in the tillage can affect soil degradation and reduce soil productivity. The aim of this study was to investigate the effect of soil packing and different soil tillage methods applied before the sowing of maize cultivated after grassland and in monoculture on soil compaction, soil organic carbon content, and maize yield. A strip–split–plot experiment was conducted on-farm in northeastern Poland from 2017 to 2021. The soil compaction was measured in the soil layers: 0–10, 10–20 and 20–30 cm in the leaf development stage (BBCH 19), the flowering stage (BBCH 67) and the maize kernel development stage (BBCH 79). The experimental factors were as follows: 1. preceding crop—grassland, maize; 2. degree of soil packing—without soil packing, soil packing after harvesting the preceding crop; 3. different soil tillage—conventional plough tillage method, reduced tillage method. Maize cultivation following a multi-species grassland resulted in a modest 1.47% increase in soil organic carbon content compared to continuous maize monoculture. In monoculture maize, all investigated reduced tillage methods led to increased soil compaction by 0.61–0.67 MPa. However, this adverse effect was mitigated by prior grassland cultivation. Maize grown after a multi-species grassland exhibited 14% higher silage mass yields. Considering the reduction in soil compaction and the enhanced yield potential, this preceding crop is recommended for maize cultivation. Although soil packing did not significantly impact maize yields, reduced tillage methods, such as subsoiling at 40 cm, medium ploughing at 20 cm, and passive tillage, led to a significant reduction in silage mass compared to other treatments. Full article