Soybean Crop Research Articles

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.

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).

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.

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.

Early Modeling of the Upcoming Landsat Next Constellation for Soybean Yield Prediction Under Varying Levels of Water Availability

The upcoming Landsat Next will provide more frequent land surface observations at higher spatial and spectral resolutions that will greatly benefit the agricultural sector. Early modeling of the upcoming Landsat Next products for soybean yield prediction is essential for long-term satellite monitoring strategies. In this context, this article evaluates the contribution of Landsat Next’s improved spectral resolution for soybean yield prediction under varying levels of water availability. Ground-based hyperspectral data collected over five cropping seasons at the Brazilian Agricultural Research Corporation were resampled to Landsat Next spectral resolution. The spectral dataset (n = 384) was divided into calibration and external validation datasets and investigated using three strategies for soybean yield prediction: (1) using the reflectance from each spectral band; (2) using existing and new vegetation indices developed based on three general equations: Normalized Difference Vegetation Index (NDVI-like), Band Ratio Vegetation Index (RVI-like), and Band Difference Vegetation Index (DVI-like), replacing the traditional spectral bands by all possible combinations between two bands for index calculation; and (3) using a partial least squares regression (PLSR) model composed of all Landsat Next spectral bands, in comparison to PLSR models using Landsat OLI and Sentienel-2 MSI bands. The results show the distribution of the new spectral bands over the most prominent changes in leaf reflectance due to water deficit, particularly in the visible and shortwave infrared spectrum. (1) Band 18 (centered at 1610 nm) had the highest correlation with yield (R2 = 0.34). (2) A new vegetation index, called Normalized Difference Shortwave Vegetation Index (NDSWVI), is proposed and calculated from bands 19 and 20 (centered at 2028 and 2108 nm). NDSWVI showed the best performance (R2 = 0.37) compared to traditional existing and new vegetation indices. (3) The PLSR model gave the best results (R2 = 0.65), outperforming the Landsat OLI and Sentinel-2 MSI sensors. The improved spectral resolution of Landsat Next is expected to contribute to improved crop monitoring, especially for soybean crops in Brazil, increasing the sustainability of the production systems and strengthening food security in Brazil and globally.

Risk assessment of homologous variants of biotech trait proteins using a bridging approach

ABSTRACT A transgenic protein is frequently expressed as different homologous variants in genetically modified crops due to differential processing of targeting peptides or optimization of activity and specificity. The aim of this study was to develop a science-based approach for risk assessment of homologous protein variants using dicamba mono-oxygenase (DMO) as a case study. In this study, DMO expressed in the next-generation dicamba-tolerant maize, sugar beet and soybean crops exhibited up to 27 amino acid sequence differences in the N-terminus. Structure modeling using AlphaFold, ESMFold and OpenFold demonstrates that these small N-terminal extensions lack an ordered secondary structure and do not disrupt the DMO functional structure. Three DMO variants were demonstrated to have equivalent immunoreactivity and functional activity ranging from 214 to 331 nmol/min/mg. Repeated toxicity studies using each DMO variant found no test substance-related adverse effects. These results support that homologous protein variants, which have demonstrated physicochemical and functional equivalence, can leverage existing safety data from one variant without requiring additional de novo safety assessments.

Zinc Oxide Nanoparticle-Mediated Root Metabolic Reprogramming for Arsenic Tolerance in Soybean

Arsenate (AsV) is absorbed and accumulated by plants, which can affect their physiological activities, disrupt gene expression, alter metabolite content, and influence growth. Despite the potential of zinc oxide nanoparticles (ZnONPs) to mitigate the adverse effects of arsenic stress in plants, the underlying mechanisms of ZnONPs-mediated detoxification of AsV, as well as the specific metabolites and metabolic pathways involved, remain largely unexplored. In this study, we demonstrated root metabolomic profiling of soybean germinating seedlings subjected to 25 μmol L−1 arsenate (Na2HAsO4) and ZnONPs at concentrations of 25 μmol L−1 (ZnO25) and 50 μmol L−1 (ZnO50). The objective of this study was to examine the effects on soybean root metabolomics under AsV toxicity. Metabolomic analysis indicated that 453, 501, and 460 metabolites were significantly regulated in response to AsV, ZnO25, and ZnO50 treatments, respectively, compared to the control. Pathway analysis of the differentially regulated metabolites (DRMs) revealed that the tricarboxylic acid (TCA) cycle, glutathione metabolism, proline and aldarate metabolism, and arginine and proline metabolism were the most statistically enriched pathways in ZnONPs-supplemented plants. These findings suggest that ZnONPs enhance the tolerance response to AsV. Collectively, our results support the hypothesis that ZnONPs fertilization could be a potential strategy for improving soybean crop resilience under AsV stress.

Mapping Soil Surface Moisture of an Agrophytocenosis via a Neural Network Based on Synchronized Radar and Multispectral Optoelectronic Data of SENTINEL-1,2—Case Study on Test Sites in the Lower Volga Region

In this article, the authors developed a novel method for the moisture mapping of the soil surface of agrophytocenosis using a neural network based on synchronized radar and multispectral optoelectronic data from Sentinel-1,2. The significance of this research lies in its potential to enhance precision farming practices, which are increasingly vital in addressing global agricultural challenges such as water scarcity and the need for sustainable resource management. To verify the developed method, data from two experimental plots were utilized. These plots were located on irrigated soybean crops, with the first plot situated on the right bank (plot No. 1) and the second on the left bank (plot No. 2) of the lower Volga River. Two experimental soil moisture geodatasets were created through measurements and geo-referencing points using the gravimetric method (for plot No. 1) and the proximal sensing method (for plot No. 2) employing the Soil Moisture Sensor ML3-KIT (THETAKIT, Delta). The soil moisture retrieval algorithm was based on the use of a neural network to predict the reflection coefficient of an electro-magnetic wave from the soil surface, followed by inversion into soil moisture using a dielectric model that takes into account the soil texture. The input parameter of the neural network was the ratio of the microwave radar vegetation index (calculated based on Sentinel-1 data) to the index (calculated based on the data of multispectral optoelectronic channels 8 and 11 of Sentinel-2). The retrieved soil moisture values were compared with in situ measurements, showing a determination coefficient of 0.44–0.65 and a standard deviation of 2.4–4.2% for plot No. 1 and similar metrics for plot No. 2. The conducted research laid the groundwork for developing a new technology for remote sensing of soil moisture content in agrophytocenosis, serving as a crucial component of precision farming systems and agroecology. The integration of this technology promotes sustainable agricultural practices by minimizing water consumption while maximizing crop productivity. This aligns with broader environmental goals of conserving natural resources and reducing agricultural runoff. On a larger scale, data derived from such studies can inform policy decisions related to water resource management, guiding regulations that promote efficient water use in agriculture.

Selection on synonymous codon usage in soybean (Glycine max) WRKY genes

The WRKY transcription factor gene family in soybean [Glycine max (L.) Merr.] (GmWRKY) is critical for the plant’s development and stress responses. This study examines the evolutionary dynamics of the GmWRKY gene family, focusing on its synonymous codon usage bias (CUB) in a comprehensive set of 179 coding sequences. CUB was analyzed using various indices, revealing a preference for A/T-ending codons and relatively low codon bias. Codon adaptation index (CAI) analysis suggested that these genes are optimized for efficient translation despite relatively low bias, reflecting a balance between codon diversity and translation efficiency. Neutrality and NC plots indicated that selective forces dominate over mutational forces in shaping codon usage, while selection signature analysis showed purifying selection being prevalent across the gene family. However, episodic positive selection was also detected in certain clades, highlighting potential adaptive diversification in response to environmental stress. Additionally, promoter binding site analysis uncovered correlations between codon usage and transcriptional regulation, indicating a context-dependent relationship between CUB and gene expression. Phylogenetic analysis identified 11 well-supported clades in the modern GmWRKY gene family and ancestral sequence reconstruction revealed more relaxed codon preferences and reduced selection constraints in modern GmWRKY genes, potentially linked to neofunctionalization and adaptation to environmental changes. These findings provide a framework for optimizing gene expression in transgenic soybean crops with resilience. Further functional validation of positively selected genes is recommended to elucidate their role in stress responses.

Winter Cover Cropping in Sustainable Production Systems: Effects on Soybean and Synergistic Implications for Rhizosphere Microorganisms

The aim of this study was to evaluate the effects of winter cover crops (CCs) on soybean agronomic performance and their implications for different physiological groups of rhizosphere microorganisms in two sustainable production systems. The production techniques for rye, peas, and oats are well known, but their suitability as CCs for soybean (organic and low-input) production needs to be examined. After two years of trials, soybean yields among the two tested winter CCs (peas and oats (P + O) and rye (R)) were statistically significant only for P + O. The soybean yield in succession to P + O as winter CCs was 3.0 t ha−1, whereas in succession to R, it was 2.7 t ha−1, and in the control plot, it was 2.6 t ha−1. The average soybean grain protein content was in the range of 40 to 41% dry matter (DM), while the oil content ranged from 20 to 22% DM. Protein and oil content primarily depends on the selected soybean variety and it is confirmed through this study that, in the studied system, we can obtain adequate grain nutritional quality. The results indicate an increase in the abundance of total bacteria, ammonifiers, and free N2-fixing bacteria in the rhizosphere, depending on the selected CCs, and differences between the tested production systems. According to this study, winter cover crops (CCs), including peas and oats (P + O) and rye (R), can be included in crop rotation for soybean. CCs can be the answer to agro-biodiversity empowerment in less diverse soybean cropping systems, along with other benefits that CCs can provide at the level of crop rotation. In addition, in almost all aspects of the study, organic production was ahead of low input. Low input is an adequate production system if there are no opportunities for organic certification and for producers who are aware of the advantages of sustainable systems, and it can also represent a transitional path towards regenerative agriculture or organic production.

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.

Characterisation of the Phenotypic Reaction of Brazilian Soybean Genotypes to Sclerotinia sclerotiorum Under Controlled Conditions

ABSTRACTWhite mould is a disease caused by the fungus Sclerotinia sclerotiorum, and it is considered one of the most devastating diseases in soybean crops, causing huge losses in productivity. In this study, we aimed to contribute to the genetic control of this disease by characterising the phenotypic reaction of 67 Brazilian soybean genotypes to S. sclerotiorum under controlled conditions. Plants were artificially inoculated with mycelium discs when they reached the four‐node phenological stage. Symptoms of white mould developed in all soybean genotypes. The resistance reaction was characterised by measuring the length of lesions on the main stem at 7 days after inoculation. Of the 67 genotypes evaluated, nine showed greater resistance to S. sclerotiorum, including 17S‐01443‐L8, 16S‐00630‐L4, GER_00003, 13S‐00001‐L2/FPS 2457 RR, BMX Torque I2X, P95Y02 IPRO, 17S‐00842‐L5, HO Pirapó IPRO and TMG 2359 IPRO. Twenty‐three genotypes showed an intermediate response, while 35 genotypes showed greater susceptibility to S. sclerotiorum. Further studies should be conducted under field conditions with the soybean genotypes that showed greater resistance response to S. sclerotiorum under controlled conditions.

Capsular attention Conv-LSTM network (CACN): A deep learning structure for crop yield estimation based on multispectral imagery

Precise prediction of agricultural production output is crucial for farmers, policymakers, and the Farming-related industry. This article introduces a novel methodology to crop yield forecasting using a capsular neural network equipped with Conv-LSTM and attention mechanism. Our model combines the strengths of 3DCNN, and Conv-LSTM, which can capture the temporal dependencies and 3D features of crop yield data, and attention mechanism, which Can prioritize the most significant characteristics for making predictions. We evaluated CACN on a sizable collection of data of soybean crop yield in the United States from 2003 to 2019 and evaluated against various cutting-edge deep learning models. The outcomes indicate that our suggested approach surpasses other models in performance in terms of RMSE, correlation coefficient, and prediction error map. Specifically, our model achieved approximately 14 % improvement in terms of RMSE, compared to the state-of-the-art model Deep-Yield. Our model also demonstrated the ability to extract more meaningful features and capture the complex relationships between crop yield data and meteorological variables. Overall, our proposed method shows great potential for accurate and efficient crop yield forecasting and can be applied to other crops and regions.

The WRKY Family Transcription Factor GmWRKY72 Represses Glyceollin Phytoalexin Biosynthesis in Soybean

Phytoalexins are plant defense metabolites that are biosynthesized transiently in response to pathogens. Despite that their biosynthesis is highly restricted in plant tissues, the transcription factors that negatively regulate phytoalexin biosynthesis remain largely unknown. Glyceollins are isoflavonoid-derived phytoalexins that have critical roles in protecting soybean crops from the oomycete pathogen Phytophthora sojae. To identify regulators of glyceollin biosynthesis, we used a transcriptomics approach to search for transcription factors that are co-expressed with glyceollin biosynthesis in soybean and stilbene synthase phytoalexin genes in grapevine. We identified and functionally characterized the WRKY family protein GmWRKY72, which is one of four WRKY72-type transcription factors of soybean. Overexpressing and RNA interference silencing of GmWRKY72 in the soybean hairy root system decreased and increased expression of glyceollin biosynthetic genes and metabolites, respectively, in response to wall glucan elicitor from P. sojae. A translational fusion with green fluorescent protein demonstrated that GFP-GmWRKY72 localizes mainly to the nucleus of soybean cells. The GmWRKY72 protein directly interacts with several glyceollin biosynthetic gene promoters and the glyceollin transcription factor proteins GmNAC42-1 and GmMYB29A1 in yeast hybrid systems. The results show that GmWRKY72 is a negative regulator of glyceollin biosynthesis that may repress biosynthetic gene expression by interacting with transcription factor proteins and the DNA of glyceollin biosynthetic genes.

TRANSCRIPTIONAL ANALYSIS OF SOYBEAN (Glycine max) GENES RELATED TO WATER DEFICIT

ABSTRACT The soybean crop has been gaining worldwide prominence, being widely disseminated due to its various forms of use in different segments. Genetic and environmental factors are decisive in the quality of this culture. A feature related to the environmental factor that has gained prominence is the water deficit. Molecular events are initiated by the perception of water stress, involving a complex genetic network. Studies in recent decades have already identified some genes related to water stress in plants, it is known that the dehydration-responsive element binding protein (DREB) plays an important role in the response to water deficit. Therefore, this work aimed to analyze the expression of genes related to water deficit in soybean. For the analysis of gene expression, leaves of soybean (Glycine max (L.) Merrill), cultivar M9144 RR, submitted to the following treatments were used: 25V25R – plants subjected to water deficit throughout the cycle, being irrigated with 25% of ETpc and 100V100R – plants that did not experience water deficit, being irrigated with 100% of ETpc throughout the cycle. The quantification of the relative expression of the genes GmDREB1 and GmDREB5 showed that the water stress suffered by the cultivar was greater in the reproductive stage. Keywords: Transcription factors, development stages, gene expression.

ENVIRONMENTAL RISK INDEX OF THE MAIN HERBICIDES USED IN THE STATE OF MATO GROSSO

Given the concern about environmental contamination due to the intensive use of pesticides in Brazilian agriculture, such as in the state of Mato Grosso, it is necessary to analyze the particularities that active ingredients (AI) exert on the environment to help reduce their impacts. The Environmental Risk Index (IRA) is a means of identifying these damages. Thus, the objective of this study was to perform the IRA of the herbicides most commonly used in Mato Grosso to control weeds in soybean, corn and cotton crops. The survey was carried out by AI, based on data from the Mato Grosso Institute of Agricultural Defense, while the physicochemical characteristics of the herbicides, necessary for the IRA equations, were obtained from three databases (PPDB, PPD and IBAMA). The parameters used to construct the IRA were: persistence in the soil, leaching, volatility, dose and toxicological profile of the herbicides. The survey indicated 42 herbicides were used, but 11 compounds accounted for 98.2% of the total volume sold, with glyphosate being the first in the ranking, with a total mass of 134,138,025 kg ai sold in the last three years in Mato Grosso. The IRA results for the largest mass sold in decreasing order were: atrazine, diuron, trifluralin, glyphosate, 2,4-D, clomazone, S-metolachlor, diquat, haloxifop-methyl, clethodim and glufosinate-ammonium. The herbicides atrazine, MSMA, diuron, trifluralin and pendimethalin were the ai that presented the highest IRA. In general, all herbicides presented medium to very high toxicity levels, resulting in a worrying factor for ecosystems when they reach non-target organisms.

EFFECT OF PRE-EMERGENT HERBICIDES ON SOYBEAN CROPS GROWN IN ROTATION WITH SUGARCANE

The need for sugarcane field reform has driven the expansion of soybean cultivation in rotation with sugarcane. Weeds are one of the main reasons for this reform, requiring specific management in rotation. The use of pre-emergence herbicides in soybean is a viable option, but its effectiveness in sandy soils requires further study. In this experiment, we evaluated the performance of pre-emergence herbicides on sugarcane straw, focusing on the control of Digitaria horizontalis. We conducted a field experiment with 11 treatments and four replications, applying herbicides immediately after soybean sowing. All herbicides, except diclosulam, provided efficient control of D. horizontalis, with over 80% control in all evaluated periods. The clomazone+sulfentrazone association showed the highest residual effect, keeping the area clean for up to 21 days after application. Weed-free control resulted in productivity equivalent to 66% of the maximum obtained. The use of cell division inhibitors allowed soybean cultivation to grow without weed competition. We conclude that the use of pre-emergence herbicides in soybean under sugarcane straw resulted in productivity gains due to effective D. horizontalis control. Poaceae plants may have a higher competitive capacity with crops compared to other families; therefore, even with few plants per square meter, species like D. horizontalis can reduce crop productivity. The use of cell division inhibitor molecules, either alone or combined with PROTOX inhibitors, allowed the soybean crop to remain free of weed competition.

Bacillus-inoculated organomineral fertilizer in soybean crop during short-term: comparing sources and doses with mineral fertilizer

Bacillus species and organomineral fertilizers can improve various crop responses. The objective of this study was to evaluate the efficiency of organomineral fertilizer with B. subtilis and B. licheniformis, in comparison to mineral fertilizer, on soybean growth, leaf nutrient content, grain yield, and soil characteristics. Two soybean field experiments (305 km apart) were set up in southeastern Brazil. Two sources of fertilizers (inoculated granulated organomineral, 5-26-0 + 0-0-32 N-P2O5-K2O, and coated mineral fertilizer, 10-52-0 + 0-0-60 N-P2O5-K2O), and four doses of P plus K (no fertilizer, 50, 75, 100 kg ha−1 of each P2O5 and K2O) were applied. At 60 days after sowing, plant height and leaf analysis were assessed. Weight of 1000 seeds, grain yield, and soil analysis were evaluated (120 days after sowing). In both fields, there was interaction between source and P plus K dose factors for soybean grain yield. In Site 1, the highest grain yield (4,543.69 kg ha−1) was observed for 100 kg ha−1 of P2O5 and K2O dose of coated mineral fertilizer; in Site 2, the highest grain yield (4,638.55 kg ha−1) was observed for 75 kg ha−1 of P2O5 and K2O dose of organomineral fertilizer. These factors also affected N, P, and K leaf contents. Less effects were observed on plant height, weight of 1000 seeds, and soil characteristics. Inoculated organomineral fertilizer can be used for total or partial supply of nutrients without a clear difference from mineral fertilization. Smaller doses of inoculated organomineral fertilizer could be used without compromising soybean grain yield.

Bacillus thuringiensis Cry14A family proteins as novel anthelmintics against gastrointestinal nematode parasites.

Bacillus thuringiensis crystal (Cry) proteins have been expressed in commercial transgenic crops for nearly 30 years, providing safe and effective control of insect pests and significantly reducing the application of hazardous chemical pesticides. B. thuringiensis crystal proteins have also been shown to target parasitic nematodes, including plant parasitic nematodes. Recently, transgenic soybean crops expressing Cry14Ab have been shown to provide control against the soybean cyst nematode Heterodera glycines, marking the first time a crystal protein is being commercialized in transgenic crops for control of a nematode pest. However, apart from H. glycines and the free-living nematode, Caenornabditis elegans, the breadth of nematode activity of Cry14Ab, e.g., against gastrointestinal parasitic nematodes (GINs), has not been reported. Here we study the efficacy of Cry14Ab against a wide range of gastrointestinal nematode parasites (GINs) in vitro and in vivo. We find that Cry14Ab is effective in vitro against the barber's pole worm Haemonchus contortus larvae, small strongyles cyathostomin larvae, the hookworm Ancylostoma ceylanicum adults, the roundworm Ascaris suum L4 larvae, and the whipworm Trichuris muris adults. In rodents infected with GIN parasites, Cry14Ab is effective as an in vivo anthelmintic against the hookworms A. ceylanicum and N. americanus, against the mouse parasite Heligmosomoides polygyrus bakeri, and against the roundworm A. suum. Cry14Ab also variably reduces the reproduction of the whipworm T. muris in vivo. Using optimized profile Markov Models, we looked for other putative anthelmintic Cry proteins and, within this list, identified a Bt crystal protein, GenBank accession no. MF893203, that we produced and demonstrated intoxicated GINs. This protein, with 90% amino acid identity to Cry14Ab, is active against C. elegans, A. ceylanicum adults, and A. suum L4 larvae in vitro. MF893203 was given the official designation of Cry14Ac. Cry14Ac is also an effective in vivo anthelmintic against A. ceylanicum hookworms in hamsters and intestinal A. suum in mice. Taken together, our results demonstrate that Cry14Ab and Cry14Ac have wide therapeutic utility against GINs.