Soybean Crop Research Articles

Controlling fall armyworm (Spodoptera frugiperda) in soybean: a comparative study

Soybeans have become an important crop in Brazil, with production increasing over the years. However, this increase has been accompanied by phytosanitary problems, leading to a decline in productivity due to damage caused by insects. The Spodoptera frugiperda is a caterpillar that has been identified in soybean crops in recent years, causing damage and increasing production costs, which in turn impedes crop growth and decreases overall productivity. This research was carried out to evaluate the effectiveness of traditional chemical insecticides (old products) and modern chemical insecticides (new products) in controlling S. frugiperda in soybean crops. The experiments were carried out in a greenhouse with a controlled environment and in the Agricultural Entomology Laboratory of the University of Passo Fundo (UPF), in Passo Fundo, RS. For the study, third-instar larvae of S. frugiperda were used, raised in the laboratory on a synthetic diet. The study was structured in a completely randomized design and consisted of two trials, each with seven treatments: the first trial tested traditional insecticides, while the second examined modern alternatives. Both trials included a control group. The results were subjected to statistical analysis, which consisted of analysis of variance and comparison of means using the Tukey test, with a significance level of 5%. In conclusion, the results suggest that both traditional and modern insecticides have potential for managing third-instar larvae of S. frugiperda in the Passo Fundo-RS region, when applied in specific sections within soybean fields.

Green and efficient fine control of regional irrigation water use coupled with crop growth-carbon emission processes

The effective, environmentally friendly, and optimally deployed management of regional agricultural water resources is crucial to ensuring food security and the sustainable use of water resources in the face of challenging agricultural issues, such as increasing greenhouse gas (GHG) emissions, water scarcity, and rapid population and economic growth. In this study, a multiobjective model for the optimal distribution of regional agricultural water resources was built, using the GIS-DSSAT and GIS-DNDC models, to simulate the regional spatial raster crop growth process and carbon emission process. The model allowed for the creation of synergies in both crop production and emission reduction. The model was solved using a fuzzy planning algorithm, and applied to the main Sanjiang Plain grain production area in Heilongjiang Province, yielding the best water allocation scheme and a set of planting structure adjustment schemes for the main grain crops of rice, maize, and soybeans in 1074 Sanjiang Plain response units. In contrast to the current method, which relies heavily on soil and water resources, the model developed in this paper reduced greenhouse gas (GHG) emissions by 10 %, energy consumption by 14.4 %, and regional irrigation water use by 34.48 %. It achieved the dual goal of reducing GHG emissions and conserving water, while increasing the synergy between increased regional food production and decreased emissions by 21 % compared to the status quo. Climate change will pose series of challenges to agricultural production, particularly the arable land and water resource usage. By optimizing cropping structures and irrigation systems, climate-adaptive management can not only reduce the area of arable land and water consumption, but also decrease carbon emissions; for the SSP2–4.5 and SSP3–7.0 scenarios, this trend resulted in increases in economic benefits of 2.4 % and 3.3 %, respectively, and decreases in carbon emission scenarios of 14.6 % and 20.7 %, respectively. The yields and GHG emissions of the response units were sensitive to these changes. This study offers decision-making support for the intense, effective, and low-carbon management of water resources.

Release Kinetics of Sulfentrazone from Chitosan Clay Sulfentrazone Nanocomposite

Introduction: With a rational objective to reduce groundwater contamination from pesticides and thereby reducing ecotoxicological effect of pesticide, present research programme was carried out. Sulfentrazone is a well-known effective pesticide that is used for soybean crops. But at the same time, sulfentrazone is known for its high leaching potential through soil and could lead to ground water contamination. Methods: So we have synthesized a novel chitosan clay nanocomposites of sulfentrazone at three different concertations of sulfentrazone, 37.64%, 52.44% and 59.85% and its release pattern was studied at three different buffer systems like pH 2, pH 4 and pH 6. Release pattern of Sulfentrazone has been quantified by using High Performance Liquid Chromatography (HPLC) technique. Various mathematical tools have been applied to understand the release kinetics of chitosan clay sulfentrazone nanocomposites. Results: Correlation coefficient (R2) of many models has been plotted and the Huguchi model was found to be the most suitable for these nanocomposites. The salient finding of this study is that the release rates of sulfentrazone at pH 4 is 68.39%, 42.62% and 37.75% after 8 hours at three different loading. This release pattern is higher than the release pattern at pH 6 and pH 2. Conclusion: Based on these release data, it is very clear that chitosan clay sulfentrazone nanocomposite can control the release of sulfentrazone at regular soil pH conditions, which is pH 6.

Incorporation of Relay Intercropping in Wheat–Fresh Maize–Fresh Soybean Cropping System Improves Climate Resource Utilization and Economic Benefits in Yangtze River Delta

Incorporation of Relay Intercropping in Wheat–Fresh Maize–Fresh Soybean Cropping System Improves Climate Resource Utilization and Economic Benefits in Yangtze River Delta

A Stinkbug Salivary Protein Is Indispensable for Insect Feeding and Activates Plant Immunity.

Salivary proteins secreted by phytophagous insects play pivotal roles in plant-insect interactions. A salivary protein RpSP27, from the stinkbug Riptortus pedestris, a devastating pest on soybean, was selected for studying due to its ability to induce cell death and activate immune responses in plants. RpSP27 localized to the endoplasmic reticulum and triggered reactive oxygen species burst. Virus-induced gene silencing assays showed RAR1 plays an essential role in RpSP27-induced cell death in Nicotiana benthamiana. Expression analyses revealed that RpSP27 is predominantly expressed in R. pedestris salivary glands. RNA interference-mediated silencing of RpSP27 in R. pedestris significantly reduced insect survival rates and altered feeding behavior by decreasing the formation of salivary sheaths on soybeans and reducing probing and feeding duration. Furthermore, the silencing of RpSP27 in R. pedestris mitigated the staygreen syndrome in soybeans, characterized by delayed senescence and pod abnormalities. This study elucidated the role of RpSP27 in the interaction between R. pedestris and soybean, presenting a potential target for pest management strategies to protect soybean crops from the detrimental effects of R. pedestris feeding.

Species composition of weeds in soybean Glycine max crops in the Belgorod region

The weed species were studied based on monitoring data in soybean crops in the Belgorod region. A total of 37 species of weed plants were found, most of which belong to the families of Compositae, Gramineae, and Cruciferae. The significance of each species in soybean crops was evaluated on its partial activity, which was determined based on both its occurrence and projective cover. Chenopodium album, Echinochloa crusgalli, Amaranthus retroflexus, Fallopia convolvulus and two Setaria species (S. viridis and S. pumila) demonstrated the highest scores of partial activities. Cirsium incanum, Persicaria hydropiper, Convolvulus arvensis, Solanum nigrum, Polygonum aviculare s. str., Xanthium strumarium were shown to have rather high scores of partial activities. About a third of species (13) are low-active: Cyclachaena xanthiifolia, Sonchus arvensis, Euphorbia virgata, Descurainia sophia, Stachys annua, Artemisia vulgaris, Tripleurospermum inodorum, Lactuca serriola, Consolida regalis, Artemisia absinthium, Sonchus asper, Centaurea cyanus, S. italica. Twelve weed species were rated as inactive in soybean crops of the Belgorod region. The results of the study may be used to develop a regional strategy for protecting soybean crops from weeds in the Belgorod region.

EFFICIENT USE OF LANDSAT-8 DATA TO MINIMIZE CLOUD COVERAGE IN THE ANALYSIS OF SOYBEAN, CORN, AND COTTON CULTIVATION

This study aimed to manipulate databases from the Landsat-8 project to select orbital scenes with minimal cloud coverage aligned with the growth periods of cotton, corn, and soybean crops in the Cerrado biome. Employing an Extract, Transform, Load (ETL) approach, the research focused on extracting and transforming large datasets by integrating georeferenced information from IBGE and data from the Agricultural Risk Zoning (ZARC). The planting windows for the 2014 to 2019 harvests were identified with a 20% or lower climate risk, considering variables such as soil and climate conditions. The results indicated that the availability of images with low cloud coverage is inversely related to the planting windows, especially during critical periods. To streamline the processing, algorithms were developed in R and Python, and a script for automatic image downloading was implemented. Despite data standardization challenges, applying big data techniques proved essential for the analysis. This study enhances efficiency in agricultural planning and emphasizes the importance of further exploring remote sensing technologies in response to current food security and sustainability demands.

Effect of Maize (Zea mays) and Soybean (Glycine max) Cropping Systems on Weed Infestation and Resource Use Efficiency

Agriculture has consistently improved to meet the needs of a growing global population; however, traditional monoculture farming, while highly productive, is facing challenges such as weed infestation and inefficient resource utilization. Herbicides effectively control weeds. However, their widespread use in weed management has the potential to contaminate soil and water, endangering the ecosystem by damaging non-target plant and animal species. Therefore, the main objective of this study was to evaluate the impact of different maize and soybean cropping systems on weed infestation and resource utilization. The experiment was a randomized complete block design with three replications consisting of three cropping systems: sole maize (SM), sole soybean (SS), and maize–soybean strip intercropping (MSI). In this study, the main difference between SM, SS, and MSI was the planting density, which was 60,000 (SM), 100,000 (SS), and 160,000 (maize–soybean in MSI). We observed that a higher total leaf area index in MSI resulted in increased soil cover, which reduced the solar radiations for weeds and suppressed the weed growth by 17% and 11% as compared to SS and SM, respectively. Whereas the radiation use efficiency for companion crops in MSI was increased by 39% and 42% compared to SS and SM, respectively. Moreover, the increased soil cover by total leaf area index in MSI also increased the efficiency of water use. Furthermore, our results indicated that reduced weed-crop competition increased the resource use in MSI, which resulted in increased crop yield and land equivalent ratio (LER 1.6). Eventually, this resulted in reduced inputs and increased land productivity. Therefore, we suggest that MSI should be adopted in resource-limiting conditions with higher weed infestation as it can simultaneously promote ecological balance and improve agricultural output, thereby reducing the environmental effects of traditional cropping systems.

Impact of planting systems and nutrient management on growth and yield of maize and soybean in a maize + soybean cropping system

A field experiment was conducted during Kharif 2023 at Lovely Professional University, Punjab, using a split-plot design (SPD) with five main plot treatments and five subplot treatments, replicated three times, to evaluate the effects of intercropping and nutrient management on maize growth and productivity. The main plot treatments consisted of cropping systems: Sole maize (M1), Sole soybean (M2), Maize + Soybean (1:1, M3), Maize + Soybean (1:2, M4) and Maize + Soybean (2:3, M5). Subplot treatments included nutrient management strategies: Absolute control (S1), 100% RDF through inorganic fertilizers (S2), 70% RDF + NPK nano fertilizer spray (S3), 70% RDF + homemade NPK spray (S4) and 70% RDF + plant extract NPK spray (S5). Results indicated that monocropped maize and soybean systems outperformed intercropping in terms of growth and grain yield, with similar trends observed for stover yield. Among nutrient management practices, foliar application of plant extract NPK showed the most significant improvement, enhancing growth attributes and crop growth rate (CGR) by 14.1% in maize and 43.4% in soybean and increasing productivity by 18% in maize and 30.6% in soybean compared to the control. The interaction of maize and soybean with foliar plant extract NPK spray led to grain yield increases of 36.6% in maize and 50.7% in soybean compared to untreated controls. Furthermore, the crop equivalent yield and land equivalent ratio were maximized in the maizesoybean intercropping system at a 1:1 ratio. This study underscores the role of strategic nutrient management and intercropping in optimizing maize and soybean productivity, with foliar NPK plant extract spray showing the most promising results for enhancing growth and yield.

Deep Learning for Weed Detection and Segmentation in Agricultural Crops Using Images Captured by an Unmanned Aerial Vehicle

Artificial Intelligence (AI) has changed how processes are developed, and decisions are made in the agricultural area replacing manual and repetitive processes with automated and more efficient ones. This study presents the application of deep learning techniques to detect and segment weeds in agricultural crops by applying models with different architectures in the analysis of images captured by an Unmanned Aerial Vehicle (UAV). This study contributes to the computer vision field by comparing the performance of the You Only Look Once (YOLOv8n, YOLOv8s, YOLOv8m, and YOLOv8l), Mask R-CNN (with framework Detectron2), and U-Net models, making public the dataset with aerial images of soybeans and beans. The models were trained using a dataset consisting of 3021 images, randomly divided into test, validation, and training sets, which were annotated, resized, and increased using the Roboflow application interface. Evaluation metrics were used, which included training efficiency (mAP50 and mAP50-90), precision, accuracy, and recall in the model’s evaluation and comparison. The YOLOv8s variant achieved higher performance with an mAP50 of 97%, precision of 99.7%, and recall of 99% when compared to the other models. The data from this manuscript show that deep learning models can generate efficient results for automatic weed detection when trained with a well-labeled and large set. Furthermore, this study demonstrated the great potential of using advanced object segmentation algorithms in detecting weeds in soybean and bean crops.

ECONOMIC ANALYSIS OF ANNUAL CROPS SUBJECT TO BIOAGRICULTURAL MANAGEMENT

The growing need for food worldwide causes changes in supply, which is not always concerned with the quality in which this food is being offered to consumers. That said, the concern with producing quality food, aiming at the maximum organic bases and available inputs, combined with the ability to produce one's own bioinputs on the farm, reduces dependence on external inputs, and greater control of production costs within the properties demonstrates a total internal interdependence for the production of food or raw materials. The research aims to evaluate the economic sustainability in the cultivation systems of the most important annual crops in the country; Soybeans, Corn, Wheat and Beans in the use of bioinputs on the farm to obtain a reduction in production costs. Research conducted in the municipality of Chapecó - SC during the 2021/2022 and 2022/2023 harvests. The research design is a factorial (3x6), factor A crop management, factor B different doses of basalt powder for the crops of Corn Harvest, Beans Off-season, Wheat Harvest and Soybean Harvest. Qualitative research on product/dose/target values. Economic results differed between production costing, attractive on a scale in R$/ha-¹ in biological management (A) and Bioagricultural (C) in the crops of corn, beans and soybeans. As well as the break-even point, the economic and financial results of the four crops evaluated were equivalent and positive in biological management (A). Expressively positive analysis in the economic indicators of profitability, between the different cultivable managements and doses of basalt powder.

CLEANER PRODUCTION: A SUSTAINABLE SOYBEAN TOOL TO REDUCE THE ENVIRONMENTAL FOOTPRINT OF CONVENTIONAL FERTILIZER USE

For a more sustainable agriculture, new agricultural management practices must be adopted to maintain productivity and grain quality while respecting the environment. This study aims to investigate the feasibility of implementing rock dust-based biofertilizers in soybean crops, using the cleaner production program as a basis, aiming to reduce the environmental footprint of the use of conventional fertilizers. To this end, this diversity of agrobiological products and management practices was tested in the field, thus being able to be exposed to climate variation, pest and disease attacks, in relation to the management adopted. The results showed that when chemical and bioagricultural treatments were compared, the latter presented significant results in relation to the variables number of active nodules in R1, NDVI V3, number of grains per pod, weight of a thousand grains, yield in kg/ha and SC/ha.

Effect of Moisture Depletion Rate and Irrigation Water Depth on the Productivity and Water Use Efficiency of Soybean Crop (Glycine max L.) Merr. under Drip Irrigation and Fixed Sprinkler Irrigation Systems

Background: Water management and its appropriate use are priorities in arid and semi-arid areas across the globe. Methods: A field experiment was carried out at Hisar in Al-Tunkopry district, Kirkuk Governorate, during 2023 summer season. Split-split plot design was adopted to implement the experiment, using randomized complete blocks design (RCBD). The main plots included irrigation method factor (sprinkler and drip) and the moisture depletion rate was placed in the sub plots (60 and 70% of the available water) while varing irrigation depth were placed in the sub-sub plots (50, 75 and 100)% of the net irrigation depth. Result: Results of the study revealed that the water requirement of the soybean crop under the sprinkler irrigation system reached 1275.9 and 1272.9 mm season-1 at 100% of net irrigation depth and at moisture depletion rates of 60 and 70%, respectively and in drip irrigation system it reached 1170.6 and 1201 mm season-1 for an irrigation level of 100% of the net irrigation depth and at a moisture depletion rate of 60 and 70%, respectively. The yield coefficient values (0.52, 0.90, 1.01, 0.90) and (0.44, 0.85, 0.96, 0.52) at a moisture depletion of 60% for the two methods (drip and sprinkler irrigation). The highest seed yield was 4.094 Mg ha-1 for the sprinkler irrigation treatment with a moisture depletion rate of 60% and an irrigation water level of 50% of the net irrigation depth, while the lowest yield was 2.41800 Mg ha-1 for the drip irrigation treatment with a moisture depletion rate of 60 and a level of 75% of the net depth. The drip irrigation achieved the highest water use efficiency 0.607072 kg m-3, in comparison to the sprinkler irrigation 0.362063 kg m-3.

A New Proposal for Soybean Plant Stand: Variation Based on the Law of the Minimum.

The hypothesis of this study is that it is possible to determine the plant stand in the soybean (Glycine max L. Merril) crop based on the spatial variability of management units, which are limiting factors in maximizing crop yield. Our objectives were as follows: (I) to evaluate the relationship between soil physical and chemical attributes to establish potential management units for variable-rate seeding; (II) to propose a method for varying plant stands based on the law of minimum soil nutrients; an (III) to relate the interaction between different plant stands on soybean grain yield, taking into account the interaction between the spatial variability of the mapped attributes. Field experiments were carried out on two plots over two agricultural years. The areas were seeded by randomly varying the soybean stand across strips in the first year. The most limiting soil nutrient was established and used, together with the soil CEC, to determine management units (MUs), which were also used to seed soybeans in VRT (Variable Rate Technology) in the same plots in the second year. MUs with the lowest restriction for maximizing yield were sown in the second year with the lowest plant stand. Data were processed using multivariate statistics. Our findings reveal that it is possible to establish MUs for seeding soybeans with different stands following the spatial variability of limiting soil nutrients according to the law of the minimum and thus increase the crop grain yield. Spatial variability of potassium (K) in the plot, identified as limiting, affected the spatial variability of grain yield. Decreasing plant stands in MUs with the lowest limitation level increases yield. However, increasing the stand in MUs with a higher limitation level can lead to increased intraspecific competition, affecting yield as well as increasing input costs.

Performance of soybean and corn in sandy soil subjected to increasing doses of micronutrients

At a global level, it is estimated that between 30% and 50% of agricultural production is influenced by the use of commercial fertilizers. The objective of this study was to evaluate the performance of soybean and corn subjected to doses of fertilizers containing multiple micronutrients. The experiment was conducted on the Água Limpa Araras property, in the 2022/2023 season. The experimental design adopted was randomized blocks, consisting of six treatments and four replicates, totaling 24 experimental units. Treatments were Fert Micro BR 12 fertilizer doses of: 0; 25; 50; 75; 100 and 125 kg ha-1. Leaf B, Mn and Zn contents were within the range considered ideal for soybean and corn crops, except in the corn crop, where the leaf Mn content in the control treatment and at a dose of 25 kg ha-1. Soybean and corn responded to the application of fertilizer containing multiple micronutrients. Soybean responded linearly with the increase in the dose of fertilizer containing multiple micronutrients, reaching a grain yield of 5,535 kg ha-1 with a dose of 125.0 kg ha-1. For corn, the maximum estimated dose of fertilizer containing multiple micronutrients was 115.8 kg ha-1, with grain yield of 12,454.48 kg ha-1.

Parasitism by Aleiodes ceres Shimbori, 2023 (Hymenoptera: Braconidae) of three species of Spodoptera Guenée, 1852: effects of preferential instar and host diet

AbstractA recently discovered koinobiont parasitoid species, Aleiodes ceres Shimbori, 2023, proved to be a promising biological control agent for larvae of Spodoptera cosmioides (Walker, 1858), S. eridania (Stoll, 1782), and S. frugiperda (J.E. Smith, 1797), all well-known pests that cause critical damage to soybean and corn crops. This study investigated the potential of parasitism by A. ceres in these three species, including different instars (1st, 2nd, 3rd, and 4th instar) and diets (artificial and natural). Parasitism was highest when it occurs in the second instar for all three host species. The egg-to-pupa period of A. ceres was shorter in the second and third instars in relation to the first instar. Parasitism was substantially enhanced by the use of natural diets (soybean and corn leaves) compared with the artificial diet in all three species of the Spodoptera complex, suggesting a possible allelochemical interaction. Based on the results from the three host species, the potential for control of Spodoptera spp. by A. ceres was evident.

Impact of Levels of Nutrient Management on Economics of Soybean-onion and Soybean-potato Cropping System

Background: Nutrient management and cropping sequence are two important factors which affect productivity and profitability of crop. Profitability is one the important part of the successful crop production. Soybean fixes atmospheric nitrogen in soil and partially fulfills the nitrogen requirement of succeeding crops. There is a need for a suitable substitute crop or cropping systems after soybean to improve the soil fertility and productivity to maximize the profitability. The plains of Maharashtra are well suited for onion and potato cultivation. There is scope for increasing the area, production and productivity of onion and potato crop. Majority of farmers in Maharashtra following soybean-wheat and soybean-chickpea crop sequence while in present investigation soybean is grown in sequence with vegetable crop such as onion and potato which could help to increase profitability through higher net return and B: C ratio. Methods: The experiment was laid out in split plot design with three replications. Six combinations of two crop sequences (soybean-onion and soybean-potato) and three levels of nutrient management viz., 50% RDF+FYM 5 t ha-1+ biofertilizer (N1), 75 % RDF+ FYM 5 t ha-1+ biofertilizer (N2) and 100 % RDF+ FYM 5 t ha-1+ biofertilizer (N3) were the main plot treatments in kharif season replicated three times in randomized block design. During rabi season each main plot treatment of nutrient management level was split into three sub plot treatments with three levels of recommended dose of fertilizer viz., 75% RDF (F1), 100% RDF (F2) and 125% RDF (F3) to rabi season crops resulting in eighteen treatment combinations replicated three times in split plot design. The data pertaining to growth characteristics, yield characteristics, economics of soybean (kharif) and onion or potato (rabi) was collected at regular interval in 2017-18, 2018-19 and 2019-20 at Agronomy Farm, Dr. PDKV, Akola which was analyzed statistically in SPD (split plot design). Result: Soybean-onion crop sequence registered higher profitability in terms of GMR, NMR and B: C in comparison with soybean - potato crop sequence. Soybean crop supplied with 100% RDN+ 5 t FYM ha-1 + Biofertilizer (Rhizobium japonicum+ PSB+ Tricoderma viridi) recorded highest GMR, NMR and B:C ratio over lower levels of treatments in all year experimentation. Rabi crops treated with 125% RDF recorded GMR, NMR and B:C ratio over lower levels of treatments in all years of experimentation.

Assessing the impact of tillage practices and nutrient levels on the growth and productivity of Ethopian mustard (Brassica carinata L.) - soybean (Glycine max (L.) Merr.) cropping system

BackgroundAn importance of tillage, inorganic and organic nutrient sources in the mustard - soybean cropping system lies in their ability to enhance soil fertility, improve nutrient availability, optimize crop growth and yield, and promote sustainable agricultural practices. Any cropping system’s sustainability could be increased by implementing better management techniques like zero and reduced tillage with residue retention and better nutrient sources.ResultsA field experiment was conducted for four consecutive seasons (Winter 2019 to Rainy 2021) to compare the two enhanced management practices, zero and reduced tillage to conventional tillage across four levels of nutrient sources: 75 and 100% recommended dose of nitrogen through FYM and 75 and 100% recommended dose of fertilizers through urea, single super phosphate and muriate of potash in a two years experiment. Experiment results were evaluated in terms of nutrient status, profitability and productivity of Mustard-Soybean cropping system. The results show a substantial improvement in yield, nutrient status, and overall yield performance of mustard and soybean when using the full recommended dose of fertilizers combined with reduced tillage and mulching, compared to other treatment methods. The implementation of reduced tillage practices recorded significantly higher yield of mustard and soybean over conventional and zero tillage.ConclusionSystem productivity and profitability i.e. mustard equivalent yield, productivity, gross returns, net returns, profitability and B: C (benefit: cost) was found to be improved with reduced tillage and 100% recommended dose of fertilizer under reduced tillage practices. To enhance cropping system productivity in various sub-humid regions worldwide, farmers can adopt reduced tillage techniques combined with the full recommended dose of fertilizers (100% RDF).

Detection of Candidate Genes and Development of KASP Markers for Pod Length and Pod Width by Combining Genome-Wide Association and Transcriptome Sequencing in Vegetable Soybean

Vegetable soybeans are one of the most important vegetable types in East Asia. The yield of vegetable soybeans is considerably influenced by the size of their pods. To facilitate the understanding of the genetic basis of the pod length and width in vegetable soybeans, we conducted a genome-wide association study (GWAS) and transcriptome sequencing. Four quantitative trait loci, namely, qGPoL1, qGPoL2, qGPoW1, and qGPoW2, were mapped via GWAS analysis. Through the integration of gene function annotation, transcriptome sequencing, and expression pattern analysis, we identified Glyma.06G255000 and Glyma.13G007000 as the key determinants of the pod length and width in vegetable soybeans, respectively. Furthermore, two kompetitive allele-specific polymerase chain reaction (KASP) markers, namely, S06-42138365 (A/T) and S13_628331 (A/T), were developed and effectively validated in 27 vegetable soybean accessions. Overall, our research identified genes that regulate the pod length and width and determined KASP markers for molecular marker-assisted selection breeding. These findings have crucial implications for the improvement of soybean crops and can contribute to the development of efficient breeding strategies.

Pesticide residues in tropical agricultural soils: Distribution, seasonality, and earthworm ecological risk

Soil contamination by pesticide residues is associated with agricultural intensification in tropical regions and endangers human health and the environment. A mixture of pesticide residues and their degradation products persist in agricultural soils and represent a risk to soil organisms. In this study, we aimed to investigate the concentration and distribution of organochlorine (OC) and organophosphate (OP) pesticide residues in agricultural soils where the industrial cultivation of maize and soybeans is intensively carried out, at three depths (0–5, 5–15, and 15–30 cm) and during two seasons (rainy and dry). Likewise, we performed the ecological risk assessment of those found pesticide residues on two earthworm species, Eisena fetida, and Aporrectoda calagionsa. We calculated the Toxicity-Exposure Ratio (TER) using Predicted no Effect Concentrations (PNEC) and measured concentrations in soils, for identifying the risk of pesticide residues separately. The Risk Quotient (RQ) method was used to evaluate the ecological risk of pesticide residue mixtures in soils from each cropping system. Endrin ketone and dieldrin were the pesticide residues with the highest frequency of detection. The highest concentration in the study was found in a soil sample from maize crops in the dry season at 15–30 cm depth (2917 ng/g). The pesticide mixture from soil samples belonging to maize (0–5 cm) and soybean (5–15 cm) crops in dry season posed the highest ecological risk for A. caliginosa with 100 %, and a maximum RQ of 82.2. Endrin ketone is the OC that contributed most to the overall toxicity of the pesticide mixture in soil samples from maize crop and dieldrin in soil samples from soybean crop. Among OP, disulfoton contributed most to RQsite in soybean crop and methyl parathion in maize crop. Results pointed out the need to apply alternatives to remediate obsolete pesticide residues and restrict the use of methyl parathion and disulfoton in maize and soybean crops, to reduce the ecological risk that represent for earthworms.