Soybean Cultivation Research Articles

Comparative Transcriptomic Analysis Reveals Adaptation Mechanisms of Bean Bug Riptortus pedestris to Different Food Resources.

The bean bug, Riptortus pedestris (Hemiptera: Heteroptera), poses a significant threat to soybean production, resulting in substantial crop losses. Throughout the soybean cultivation period, these insects probe and suck on various parts of plants, including leaves, pods, and beans. However, the specific mechanisms by which they adapt to different food resources remain unknown. In this study, we conducted gut transcriptomic analyses of R. pedestris fed with soybean leaves, pods, and beans. A total of 798, 690, and 548 differently expressed genes (DEGs) were monitored in G-pod vs. G-leaf (comparison of insect feeding on pods and leaves), G-bean vs. G-leaf (comparison of insect feeding on beans and leaves), and G-pod vs. G-bean (comparison of insect feeding on pods and beans), respectively. When fed on pods and beans, there was a significant increase in the expression of digestive enzymes, particularly cathepsins, serine proteases, and lipases. Conversely, when soybean leaves were consumed, detoxification enzymes, such as ABC transporters and 4-coumarate-CoA ligase, exhibited higher expression. Our findings indicate that R. pedestris dynamically regulates different metabolic pathways to cope with varying food resources, which may contribute to the development of effective strategies for managing this pest.

Machine learning for soybean yield forecasting in Brazil

Brazil supplies half of the world's exported soybeans. Forecasting its national soybean yield before harvest could help mitigate disruptions in food supply. The objective of this study is to develop a national soybean yield forecasting system for Brazil based on machine learning (ML) models. Twenty years (2001–2020) of municipality yield, the Oceanic Niño Index (ONI), remote sensing, and gridded daily climate data across the Brazilian soybean cultivation area were used to train ML models in order to estimate municipality soybean yield. Five different ML approaches and their Ensemble were tested: Linear (Ridge) Regression (LR), Random Forest (RF), Gradient Boosted Trees (XGB), Artificial Neural Network (ANN) and Long Short-Term Memory Network (LSTM). Soybean yield forecasting performance varied according to ML model and location. The best performance in estimating municipal soybean yield was achieved with ANN and an Ensemble model with an average rRMSE of 16%, varying from 4% in central-northern to >30% in southern Brazil. Yield was simulated on the municipality level, and its weighted aggregation was used to estimate the yield on the state and national level. Estimations deviated from the observations by an rRMSE from 4.7% to 18.6% (state level) and 4.8% to 6.7% (national level) with the model Ensemble showing the best results, followed by ANN. National soybean yield is forecasted mid-season with an rRMSE of about 6% by end of December, three months prior to crop harvest in March. The accuracy and uncertainty of such in-season forecasts further improve towards the end of the season. The proposed soybean yield forecasting system is transferable to other countries and could help policymakers and food traders plan strategies ahead of harvest.

Analysis of Indonesia's Soybean Competitiveness

The current national soybean demand is reaching 4 million tons, but domestic production only meets 1/16 of that demand. The increasing domestic soybean demand, coupled with a decreasing national soybean production each year, has led to Indonesia's dependence on imports. There are numerous issues with the soybean commodity that have resulted in the weak competitiveness of Indonesian soybeans in the international market. However, several soybean production centers show that soybean cultivation is still viable for development. This research aims to analyze the competitiveness level of Indonesian soybean commodities. Revealed Comparative Advantage (RCA) analysis is utilized to assess the competitiveness level of Indonesian soybeans in the international market. The research findings that The RCA value is less than 1, indicating that Indonesian soybeans lack competitiveness or have weak competitiveness.

Integrated systems improve the sustainability of soybean cultivation in the tropical region

Inter-cropping between annual crops with tropical forages through integration crop-livestock systems (ICL) is considered a sustainable option to increase crop diversity and soybean productivity. In this study, we evaluated (1) the biomass production, desiccation efficiency, nutrient accumulation, and biomass decomposition of soil crop residues produced by Panicum maximum plants intercropped with maize in two different sowing methods during the second harvest and (2) investigated how soil crop residues impact the productivity of soybean. The experiment was conducted in a complete block design with three replicates. We compared conventional soybean cultivation with soybean cultivated over soil crop residues produced by a previous integration between maize and two Panicum maximum cultivars: Tamani and Zuri guinea grass, within and between rows of maize plants. Our results showed that Tamani guinea grass showed the highest desiccation efficiency. Zuri and Tamani guinea grass cultivated within and between maize plants resulted in higher biomass production and nutrient cycling potential, resulting in an increase of 28.4% in soybean productivity, compared to soybean grown without soil crop residues. We concluded that ICL system is an efficient method to increase the sustainability of soybean cultivation.

Valine amino acid determination in transgenic soybean exposed to glyphosate

With the increase of glyphosate tolerant transgenic soybean cultivation areas, this substance has become the main herbicide for this crop, its use may interfere in the metabolism and nutritional aspects of transgenic plants. In this scenario, the objective of this work was to verify concentrations of amino acid valine and in glyphosate tolerant soybean cultivar. Comparing the averages between protein and total amino acid levels in transgenic soybean exposed and not exposed to glyphosate, it was found that there was no significant difference by Tukey test at 5% probability. In conclusion, the data indicate that although the transgenic event affects some routes, amino acid synthesis was not affected nor in nutritional terms at the glyphosate doses studied.

Epilithic biofilms as a discriminating matrix for long-term and growing season pesticide contamination in the aquatic environment: Emphasis on glyphosate and metabolite AMPA

The indiscriminate use of pesticides represents high ecological risk in aquatic systems. Recently, the inclusion of epilithic biofilms as a reactive matrix has shown potential in diagnosing the health of water resources. The objective of this study was to use multiple matrices (water, suspended sediments, and biofilms) to discriminate contamination degrees in catchments with long and recent history of intensive pesticide use and to monitor growing season pesticides transfer to watercourses. Two catchments were monitored: one representative of “modern agriculture” in a subtropical environment, and another representative of recent agricultural expansion over the Pampa Biome in subtropical Brazil. Glyphosate and AMPA were accumulated in the biofilms and were detected at all sites and at all monitoring times, in concentrations ranging from 195 to 7673 μg kg−1 and from 225 to 4180 μg kg−1, respectively. Similarly, the fungicide tebuconazole has always been found in biofilms. The biofilms made it possible to discriminate the long-term history of pesticide use in the catchments and even to identify the influx pulses of pesticides immediately after their application to crops, which was not possible with active water sampling and even with suspended sediment monitoring. It is strongly recommended that, in regions with intensive cultivation of soybeans and other genetically modified crops, the presence of glyphosate and its metabolite AMPA be permanently monitored, a practice still very scarce in the literature.

Transformation of Brazil's biomes: The dynamics and fate of agriculture and pasture expansion into native vegetation

Land use and cover change (LUCC) in Brazil encompass a complex interplay of diverse factors across different biomes. Understanding these dynamics is crucial for informed decision-making and sustainable land management. In this study, we comprehensively analyzed LUCC patterns and drivers using 30 m resolution MapBiomas Collection 6.0 data (1985–2020). By mapping deforestation of primary and secondary natural vegetation, natural vegetation regeneration, and transitions between pasture, soybean, agriculture, and irrigation, we shed light on the intricate nature of LUCC in Brazil. Our findings highlight significant and increasing trends of deforestation in primary vegetation in the country. Simultaneously, the Atlantic Forest, Caatinga, Pampa, and other regions of the Cerrado have experienced intensification processes. Notably, the pasture area in Brazil reached its peak in 2006 and has since witnessed a gradual replacement by soybean and other crops. While pasture-driven deforestation persists in most biomes, the net pasture area has only increased in the Amazon and Pantanal, decreasing in other biomes due to the conversion of pasturelands to intensive cropping in other regions. Our analysis further reveals that primary and secondary vegetation deforestation accounts for a substantial portion of overall forest loss, with 72 % and 17 %, respectively. Of the cleared areas, 48 % were in pasture, 9 % in soybean cultivation, and 16 % in other agricultural uses in 2020. Additionally, we observed a lower rate of deforestation in the Atlantic Forest, a biome that has been significantly influenced by anthropogenic activities since 1986. This holistic quantification of LUCC dynamics provides a solid foundation for understanding the impacts of these changes on local to continental-scale land-atmosphere interactions. By unraveling the complex nature of LUCC in Brazil, this study aims to contribute to the development of effective strategies for sustainable land management and decision-making processes.

Population genetic diversity in Nezara viridula by analysis of mitochondrial control region sequences

Abstract Here, we examine genetic diversity and dispersal patterns in populations of the agricultural pest Nezara viridula from Argentina using mitochondrial control region sequences. The DNA sequence comparisons of 1837 base pairs of the control region revealed 60 haplotypes determined by a total of 108 variable sites. The observed total haplotype diversity (Hd) value was 0.99, and the nucleotide diversity was 0.00423 and 0.00571 according to π and θW, respectively. The high haplotype diversity and low nucleotide diversity, as well as both neutrality tests and unimodal mismatch distributions, suggested a recent expansion in the populations of N. viridula from Argentina. The expansion of the populations of this insect is probably due to the recent agricultural expansion and intensification of soybean cultivation in this country. No significant levels of genetic differentiation were detected, suggesting that gene flow predominates over genetic drift. In addition, the Bayesian individual assignment analysis revealed that all populations share ancestry. It is probable that the growth in the area cultivated with soybean has generated stable and continuous habitats that allow gene flow among populations of N. viridula. The results of demographic history analysis suggest that the direction of migration of N. viridula would be associated with the growth pattern of soybean crops in Argentina.

Triple-transgenic soybean in conjunction with glyphosate drive patterns in the rhizosphere microbial community assembly

Plant roots continuously influence the rhizosphere, which also serves as a recruitment site for microorganisms with desirable functions. The development of genetically engineered (GE) crop varieties has offered unparalleled yield advantages. However, in-depth research on the effects of GE crops on the rhizosphere microbiome is currently insufficient. We used a triple-transgenic soybean cultivar (JD606) that is resistant to insects, glyphosate, and drought, along with its control, ZP661, and JD606 treated with glyphosate (JD606G). Using 16S and ITS rDNA sequencing, their effects on the taxonomy and function of the bacterial and fungal communities in the rhizosphere, surrounding, and bulk soil compartment niches were determined. Alpha diversity demonstrated a strong influence of JD606 and JD606G on bacterial Shannon diversity. Both treatments significantly altered the soil's pH and nitrogen content. Beta diversity identified the soil compartment niche as a key factor with a significant probability of influencing the bacterial and fungal communities associated with soybeans. Further analysis showed that the rhizosphere effect had a considerable impact on bacterial communities in JD606 and JD606G soils but not on fungal communities. Microbacterium, Bradyrhizobium, and Chryseobacterium were found as key rhizobacterial nodes. In addition, the LEfSe analysis identified biomarker taxa with plant-beneficial attributes, demonstrating rhizosphere-driven microbial recruitment. FUNGuild, Bugbase, and FAPROTAX functional predictions showed that ZP661 soils had more plant pathogen-associated microbes, while JD606 and JD606G soils had more stress-tolerance, nitrogen, and carbon cycle-related microbes. Bacterial rhizosphere networks had more intricate topologies than fungal networks. Furthermore, correlation analysis revealed that the bacteria and fungi with higher abundances exhibited varying degrees of positive and negative correlations. Our findings shed new light on the niche partitioning of bacterial and fungal communities in soil. It also indicates that following triple-transgenic soybean cultivation and glyphosate application, plant roots recruit microbes with beneficial taxonomic and functional traits in the rhizosphere.

Crop Mapping Based on Sentinel-2 Images Using Semantic Segmentation Model of Attention Mechanism.

Using remote sensing images to identify crop plots and estimate crop planting area is an important part of agricultural remote sensing monitoring. High-resolution remote sensing images can provide rich information regarding texture, tone, shape, and spectrum of ground objects. With the advancement of sensor and information technologies, it is now possible to categorize crops with pinpoint accuracy. This study defines crop mapping as a semantic segmentation problem; therefore, a deep learning method is proposed to identify the distribution of corn and soybean using the differences in the spatial and spectral features of crops. The study area is located in the southwest of the Great Lakes in the United States, where corn and soybean cultivation is concentrated. The proposed attention mechanism deep learning model, A2SegNet, was trained and evaluated using three years of Sentinel-2 data, collected between 2019 and 2021. The experimental results show that this method is able to fully extract the spatial and spectral characteristics of crops, and its classification effect is significantly better than that of the baseline method, and it has better classification performance than other deep learning models. We cross verified the trained model on the test sets of different years through transfer learning in both spatiotemporal and spatial dimensions. Proving the effectiveness of the attention mechanism in the process of knowledge transfer, A2SegNet showed better adaptability.

Effect of struvite (Crystal Green) fertilization on soil element content determined by different methods under soybean cultivation

Struvite is regarded as a promising phosphorus fertilizer alternative to mineral fertilizers; however before fertilizing, soil tests should be undertaken to determine fertilizer recommendations. In May 2022, soil was sampled from a pot experiment with the application of phosphorus set up at the Wroclaw University and Environmental and Life Sciences. Chemical analysis of the soil included total and available phosphorus, potassium, magnesium determined by the Egner–Riehm, Mehlich 3 and Yanai methods. The purpose of the article is to compare soil element extraction by three different methods under struvite fertilization and its use in soybean cultivation. The application of these methods indicated an unambiguous increase in soil Mg content after struvite application. Broadcast soybean fertilization affected the phosphorus content of the soil. The results of the study indicated that different extraction methods presented different contents of P from soil. The content of available phosphorus was circa 122–156 mg kg−1 dm, 35.4–67.5 mg kg−1 dm and 100–159 mg kg−1 dm according to the Mehlich, Yanai and Egner–Riehm methods, respectively. A positive correlation was found between the content of Mg and K in soil determined by the Mehlich 3 and Yanai methods, which may suggest that the Yanai method could be introduced into standard soil chemical analysis in Poland. Such a correlation was not found for phosphorus, which is a difficult element to determine due to the multitude of factors affecting its availability.

Семеноводство сои в Российской Федерации – текущее состояние и перспективы развития

The article considers the current state and prospects for the development of soybean breeding and seed production in the modern economic conditions of the Russian Federation. In accord-ance with the Doctrine of Food Security, the share of seeds of domestic selection for agricultural crops should not be lower than 75 %. According to the Ministry of Agriculture of Russia, soy-beans belong to agricultural crops with a share of seeds of foreign selection from 40 to 50 %. The main objective of the development of breeding and seed production in the Russian Federa-tion is to reduce the share of imported seeds by using various methods of influence from the state in this segment and increase the number of seeds of domestic selection. The purpose of the study was to analyze the state of domestic soybean breeding and seed production in the modern economic conditions of the Russian Federation to identify current organizational and economic problems in this segment. Research results. It has been established that there are certain organi-zational and economic problems in the soybean breeding and seed production industry, such as low crop yield (the increase in yield since 2010 is no more than 0.57 t/ha), a low level of provi-sion of domestic producers with seeds of domestic selection, an increase in the share of foreign seed material in the structure of acreage over the past 5 years on 24 % – from 17.6 % in 2016 to 41.6 % in 2020. These problems need to be solved, and the effectiveness of these solutions can be ensured with direct state participation and strengthening the importance of domestic breeding and seed production through the implementation of programs aimed at improving the system of state variety testing and registration actions, obtaining competitive soybean varieties on the do-mestic market, the introduction of innovative technologies for seed crops, methods of creating scientific and educational centers for the purpose of training highly qualified personnel in the field of breeding and seed production for the agricultural sector of the economy. The field of practical application of the results of the study is the possibility of using part of the conclusions for further in-depth study of the prospects of soybean cultivation in Russia in order to solve the tasks set by the Government of the Russian Federation in the Doctrine of Food Security.

A site suitability analysis for castor (Ricinus communis L.) production during Brazil's second harvest incorporating disease prediction

Castor (Ricinus communis L.) is an important industrial crop with a wide range of industrial and pharmaceutical applications. Brazil is among the largest castor-producing countries. Between 2004 and 2010, castor cultivation was stimulated with an emphasis towards biodiesel production. However, this was not enough to leverage the production of castor in Brazil, mainly due to the lack of structured trade and the competition with other cheaper raw materials for the production of biodiesel. Despite this failure, the species presents itself as an excellent alternative for crop rotation in the second crop among soybean, corn, beans, and cotton cultivation areas as the oil is highly valuable for other products. Moreover, it has drawn the attention of producers and researchers in Brazil for this potential rotation as it is considered a plant tolerant of water-deficiency and is highly susceptible to gray mold, a disease favored by high humidity in the final stages of the crop. For instance, its cultivation in the second crop in Cerrado regions, where rains occur in the early stages of the crop and cease when the plants reach the final stage of production, has been successful and shows great promise. The current study aimed to evaluate the suitability of environments throughout Brazil to grow castor, incorporating variables associated with the incidence of gray mold and confirm these findings based on existing castor trial data obtained from the literature. The site suitability analysis determined that 74.99 million hectares - 8.8% of Brazilian territory - are highly suitable for castor production during second harvest, mostly located in the Northeastern and Midwestern regions. These results are surprising since Brazil currently has around 7.8% (∼66.81 million hectares) of its territory occupied with agriculture (grains, fruits, vegetables, and perennial crops). The findings of this study provide a method to perform site suitability for crops using data associated with agronomic and disease characteristics, as is the case with gray mold that often results in significant losses in castor production. Also, this analysis provides evidence for the great potential of Brazil to increase castor production and meet the world demand for its oil through utilization of second-crop cultivation.

Survival of Colletotrichum truncatum as Microsclerotia in Soil.

Anthracnose has become one of the main threats to soybean production and is considered the most important disease in some soybean-producing areas. Colletotrichum truncatum is the species most commonly associated with anthracnose and produces microsclerotia. However, the role of microsclerotia in the epidemiology of soybean anthracnose disease has not yet been described. The aim of this study was to determine whether C. truncatum microsclerotia can survive and maintain pathogenicity for a period of up to 246 days, corresponding to the off-season period of soybean cultivation in Brazil. Therefore, microsclerotia of two pathogenic isolates of C. truncatum (CMES1059 and LFN0297) were produced and placed in polyester bags, which were kept under field conditions either on the soil surface under maize straw or buried 8-cm deep. The bags were collected monthly for a period of up to 246 days to assess the viability of microsclerotia based on their germination and typical colony growth. The logistic regression model was used for data analysis considering viable and nonviable microsclerotia. In addition, periodic sowing of soybean was done in the soil infested with LFN0297 microsclerotia to test pathogenicity up to 246 days after soil infestation. C. truncatum microsclerotia survived from 92 to 246 days in the field soil, with the highest recovery of viable microsclerotia at 153 days. C. truncatum was reisolated from soybean plants sown in infested soil at 245 days postinoculation. The isolates from the last microsclerotia sampling from the field (246 days) and those obtained from a plant at the last sowing date (245 days) had the same genotypic profile for 12 microsatellite loci as the isolates used to perform the experiments. C. truncatum microsclerotia in soil may serve as the primary inoculum for soybean anthracnose.

Evaluation of land suitability as the basis for sustainable crop development

This study aims to determine the potential and limitations of land in Ngawi District, East Java, Indonesia, for cultivating rice, corn, and soybeans. The research consists of a four-stage field study conducted in Ngawi Regency: (1) organization of land units; (2) determination of observation points through stratified proportional sampling for each land unit; (3) field surveys; and (4) laboratory analysis. The land evaluation was conducted in accordance with the FAO Guidelines for Land Evaluation for Rainfed Agriculture. The results of the research indicate that 46,417.7 ha (88.1%) of the land area is highly suitable (S1) for rice and 49,286.6 ha (72.1%) is marginally suitable (S3) for corn due to poor drainage. Approximately 62,499 ha (91.4% of the total land area) are marginally suitable (S3) for soybean cultivation. There were suggested five models of land management: (1) intensive rice farming; (2) a relay cropping system for rice-corn or rice-soybeans; (3) multiple cropping systems for corn, soybeans, or rice; (4) a mono-cultural system for rice, corn, or soybeans; and (5) an agroforestry system for Albizia chinensis, corn, and soybeans. Farmers’ awareness of organic management is crucial for enhancing land productivity and maintaining soil fertility in Ngawi Regency.

Yield and economic analysis of soybean cultivation in succession with different autumn/winter crops in Midwest of Paraná, Brazil

Yield and economic analysis of soybean cultivation in succession with different autumn/winter crops in Midwest of Paraná, Brazil

Exploring the agro-potential of extract from Levisticum officinale WDJ Koch in soybean cultivation

The search for agrotechnical alternatives that improve crop yields while having a neutral impact on the environment is the essence of sustainable agriculture. Biostimulants are an important tool for integrated crop management. The objective was to assess the biostimulating activity of macerates from the leaves of Levisticum officinale L., using soybean as a model crop. The extract was evaluated for biologically active compounds as well as its ability to support the growth of soybean plants in natural conditions during a three-year field experiment. The effect of macerates on morphophysiological parameters of soybean plants was evaluated. The harvested crop was analyzed for its mineral profile, protein and amino acid content, including essential amino acids, fat and fatty acids, and fiber fraction content. The analysis showed that the lovage root extract contained antioxidants in the form of phenolic compounds, soluble carbohydrates, minerals, and phytohormones. The concentration of bioactive compounds indicates that the plant extract has agronomic potential and can be considered an effective natural biostimulant to improve soybean growth and yield. The bioactive components of the lovage extract played an important role in plant growth and metabolism. The number of pods per plant and soybean yield increased significantly after the application of the macerate. The concentration of minerals, amino acids, and total protein in soybean increased by the application of lovage macerate. The analyzed extract is an effective natural biostimulant and can be used in agricultural practice.

EFFECT OF NP DOSES BY NEW CaCO3 AGROFUNDS ON THE FORMATION OF SOYBEAN YIELDS

For the acid soils in the south of the country, it is more than necessary to apply calcareous amendments. Results in this sense were obtained over the years at the main crop plants in the station area. Considering the increasing importance of the soybean crop, it was considered necessary to resume these types of research, as new products based on limestone and dolomite appeared. Significant results were obtained by forming the total biomass of the plant as well as its components. In the case of the Cristina TD (00) variety, the interaction between several CaCOɜ formulations and NP fertilizers contributed as follows: plant biomass 6.46 t/ha (100%), pod biomass 4.16 t/ha (63%), and grains were 2.17 (33%). Of the two analyzed factors, NP fertilizer had the most important contribution to this variety, followed by the influence of the four CaCOɜ formulations. The interaction between the two factors was always negative demonstrating that there was some competition between the cations. The obtained correlations were in all cases positive, but of different intensities. Through the obtained results, it is recommended that new formulations of CaCOɜ be permanently used in the soybean cultivation technology on acid soils.

Enhancing Biotic Stress Tolerance in Soybean Affected by Rhizoctonia solani Root Rot Through an Integrated Approach of Biocontrol Agent and Fungicide.

Rhizoctonia solani causes root rot in soybean, a worldwide severe concern for soybean cultivation. The fungus grows and clogs the xylem tissue of the host plant by producing numerous sclerotia, which results in disease symptoms, such as yellowing of leaves, wilt, and plant death. Overuse of chemical fungicides increases the threat of developing resistance to pathogens, reduces soil productivity, and negatively impacts the health of the soil, the environment, and humans. An integrated pest management strategy improves crop yield, profit, and safety. The present study focused on a fungicide (carbendazim) compatibility test with a biocontrol agent (Pseudomonas fluorescence). It evaluated the effect of this combined approach on photosynthetic reactions and growth in soybean in the presence of the fungal pathogen R. solani. The study showed that P. fluorescence significantly inhibited the mycelial growth of R. solani (43%) and tolerated 0.05-0.15% concentration of carbendazim. This confirms the suitability compatibility of P. fluorescence with chemical fungicides for IPM. These novel blending significantly reduced the disease incidence by about 75%, and a 72% decrease in disease severity was observed compared to pathogen control. Moreover, this combined approach has also improved plant growth, yield parameters, and photosynthetic efficiency in the presence of R. solani treated with an integrated system showed better overall growth despite being infected by the pathogen.

Evaluation of the Effect of the Vigor of Soybean Seeds Treated with Micronutrients Using X-ray Fluorescence Spectroscopy and Hyperspectral Imaging

Seed treatment with micronutrients is a crucial strategy for providing early seedling supply during development, and is commonly employed in soybean cultivation. However, responses to micronutrient treatment may vary based on seed vigor levels. Therefore, this study aimed to assess the potential of hyperspectral imaging combined with preprocessing and machine learning, compared to X-ray fluorescence spectroscopy, in evaluating the dynamics of micronutrient uptake during the germination of soybean seeds with varying levels of vigor. Two seed lots with differing levels of vigor were utilized for the analysis. The absorption of micronutrients by the seeds was evaluated using X-ray fluorescence spectroscopy (XRF), microprobe X-ray fluorescence spectroscopy (μ-XRF) and hyperspectral imaging (HSI) in two regions of interest (cotyledons and the embryonic axis). Artificial neural network (ANN), decision tree (DT) and partial least squares–discriminant analysis (PLS-DA) classification models, along with the Savitzky–Golay (SG), standard normal variation (SNV) and multiplicative scatter correction (MSC) methods, were employed to determine seed vigor based on the impact of micronutrient treatment. XRF identified higher concentrations of micronutrients in the treated seeds, with zinc being the predominant element. μ-XRF analysis revealed that a significant proportion of the micronutrients remained adhered to the hilum and seed coat, irrespective of seed vigor. The PLS-DA classification model using spectral data exhibited higher accuracy in classifying soybean seeds with high and low vigor, regardless of seed treatment with micronutrients and the analyzed region.