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Characterization of common bean production regions in Brazil using machine learning techniques
(2025-03) Justino, Ludmilla Ferreira; Heinemann, Alexandre Bryan; Matta, David Henriques da; Stone, Luís Fernando; Gonçalves, Paulo Augusto de Oliveira; Silva, Silvando Carlos da
PROBLEM Understanding the interactions between genotype, environment, and management is crucial for guiding the development of new cultivars and defining strategies to maximize yield under specific environmental conditions. OBJECTIVE This study aimed to classify and characterize homogeneous production regions for common beans in Brazil by leveraging simulated yield data and machine learning techniques. The goal was to identify the environmental factors that define these homogeneous regions and to develop a spatiotemporal sowing calendar for rainfed (wet and dry seasons) and irrigated (winter season) production. METHODS The CSM-CROPGRO-Dry Bean model was used to simulate the yield of common beans in Brazilian municipalities during the wet (rainfed) season (sowing between August and December - 275 municipalities), dry (rainfed) season (sowing between January and April - 251 municipalities) and winter (irrigated) season (sowing between April and July - 59 municipalities), utilizing soil data, daily climate data (1980 to 2016), management information (sowing date and irrigation/rainfed), and genetic coefficients to reflect the performance of the BRS Estilo cultivar related to phenology, growth and yield components. To create homogeneous environmental groups and associate them with specific environmental features, we applied machine learning techniques, including K-means clustering and decision tree analysis. RESULTS According to the results, we identified three distinct homogeneous regions — high, medium, and low yields — for each cultivation season (wet, dry, and winter). During the wet season, regions with yields between 2326 and 3500 kg ha−1 were classified as high-yield, those between 1404 and 2325 kg ha−1 as medium-yield, and those between 500 and 1403 kg ha−1 as low-yield. In the dry season, high-yield regions had yields ranging from 2492 to 3500 kg ha−1, medium-yield regions from 1484 to 2491 kg ha−1, and low-yield regions from 500 to 1483 kg ha−1. For the winter season, high-yield regions achieved yields between 2972 and 3500 kg ha−1, medium-yield regions between 2252 and 2971 kg ha−1, and low-yield regions between 634 and 2251 kg ha−1. For rainfed seasons (wet and dry), the water stress (WSPD) had a greater impact on yield than air temperature and global solar radiation. While in the winter season, air temperature was the most relevant factor. Overall, in the wet season, delayed sowing contributed to increased yield, especially in the state of Paraná. In the dry season, delayed sowing caused a reduction in yield, particularly in the Midwest and Southeast regions. In the winter season, yield varied less significantly between sowing dates, except in the state of Mato Grosso, where harmful increases in air temperature were observed in the later months. CONCLUSIONS The integration of crop simulation models with machine learning tools is valuable for defining and characterizing homogeneous regions for common bean production. This approach has identified three distinct yield regions—high, medium, and low—for each crop season (wet, dry, and winter). By distinguishing these regions, this methodology supports breeding programs in developing cultivars optimized for specific environments and provides insights into how environmental factors influence crop performance. Additionally, it helps optimize sowing dates to align with favorable conditions, particularly during the wet and dry seasons, thereby contributing to reduced yield losses. IMPLICATIONS The classification and characterization of homogeneous production regions helps to better understand the genotype (G) x environment (E) x management (M) interactions and to adjust sowing dates to more favorable conditions, especially during the wet and dry seasons, contributing to reducing yield losses. Despite the limitations of crop modeling—such as not accounting for biotic factors and waterlogging—addressing water and air temperature stress presents an even greater challenge. In this context, crop modeling plays a crucial role in identifying effective adaptation strategies.
Envirotyping-informed mixed models to study the climatic drivers and yield seasonal variation for common beans in Brazil
(2025-10) Heinemann, Alexandre Bryan; Matta, David Henriques da; Stone, Luís Fernando; Costa Neto, Germano Martins Ferreira; Resende, Rafael Tassinari; Gonçalves, Paulo Augusto de Oliveira; Justino, Ludmilla Ferreira
Common beans (Phaseolus vulgaris L.) is a staple food crop cultivated across various regions, seasons, and management systems in Brazil. To ensure production stability, it is essential to understand how climate factors affect cultivar development. This study aimed to determine the main edaphoclimatic drivers influencing the seasonal variation of common bean yield and their impact on genotype ranking across Brazil. Utilizing extensive databases, such as historical field trial records, allows for deeper insights into the impacts of environmental features on phenotypic variation, guiding plant breeders in addressing genotype-by-environment interactions that limit cultivar targeting and genetic progress. We applied an envirotyping-informed (EI) linear mixed-effects model (LMM) to assess climatic drivers and their effects on yield variation across diverse years, elite genotypes, and regions. Our findings identified distinct seasonal environmental types within each region. Air temperature emerged as a key factor, explaining 40 % to 80 % of the phenotypic variation in grain yield. The Midwest region, where the main breeding nursery is located, is primarily limited by temperature, while other regions, such as the Southeast, exhibit different factors affecting yield variations. The inclusion of EI-LMM enabled cultivar ranking based on genetic mean incremental predict value and the calculation of genotype relative importance using analysis of variance (ANOVA). These outcomes connect data from advanced breeding trials and inform decisions about cultivar development, considering regional environmental specificities and within-season variations. Future studies should incorporate genotype-by-environment-by-management interactions to better understand climate adaptation in common beans, bridging the gap between breeding efforts and farmer needs.
Spatio-temporal dynamics of water stress for common bean production in Goiás, Brazil
(2025) Justino, Ludmilla Ferreira; Heinemann, Alexandre Bryan; Matta, David Henriques da; Stone, Luís Fernando; Gonçalves, Paulo Augusto de Oliveira; Silva, Silvando Carlos da
Water stress is among the most critical abiotic factors limiting agricultural productivity. Adjusting sowing dates to align with periods of higher water availability is a proven strategy for mitigating drought impacts on common bean production. This study aimed to evaluate the dynamics of water stress in common bean production regions across Goiás, Brazil, during the rainfed wet and dry seasons, utilizing functional data analysis (FDA). The CSM-CROPGRO-Dry Bean model was employed to simulate common bean yields and environmental factors (EF), including water stress. Simulations incorporated a dataset encompassing soil characteristics, daily climate data (1980–2016), management practices, and genetic coefficients. Water stress data were analyzed by municipality, sowing date, and year, focusing on the critical period from 20 days before flowering to 40 days after flowering. Accumulated water stress curves were generated and grouped using functional K-means clustering for each sowing date. Based on these clusters, regions were characterized by water stress levels, and a spatio-temporal sowing calendar was developed. The results indicated that during the wet season, the optimal sowing period is between October 20 and November 10, when water stress is minimal. Conversely, the dry season exhibited the highest levels of water stress, typically beginning before flowering and intensifying through grain filling. To mitigate these effects, sowing between January 1 and February 10 is recommended. By assessing the spatio-temporal dynamics of water stress, this study offers actionable insights to optimize sowing schedules, enhance yield potential, efficiently manage water resources, and promote sustainable common bean production in Goiás.
Ascophyllum Nodosum-Based biostimulant mitigates lactofen herbicide phytotoxicity in soybean crops
(2025) Silva, Alessandro Guerra da; Melo, Gabriel Bressiani; Costa, Alan Carlos da; Rosa, Márcio; Bessa, Layara Alexandre; Teixeira, Marconi Batista; Braz, Guilherme Braga Pereira; Teixeira, Itamar Rosa; Vitorino, Luciana Cristina
Biostimulants may be a management strategy to mitigate injuries caused by herbicides in soybean crops due to their antioxidant properties. This hypothesis was evaluated in field experiments conducted over two crop seasons through based on assessments of plant growth and yield of soybean crops. Increasing rates (0.00, 0.33, 0.66, and 0.99 L cp. ha− 1) of a commercial biostimulant were applied at 0, 3, 6 and 9 days after application (DAA) of the herbicide lactofen (protox or PPO enzyme inhibitor); a control treatment was implemented without application of these products. The biostimulant Megafol® composed of urea, potassium acetate, vinasse, and extract from the algae Ascophyllum nodosum, was tested. The application of lactofen reduced plant growth (average reduction of 15.6 cm in the first harvest and 6.8 cm in the second harvest), resulting in losses in grain yield (average reduction of 559.7 kg ha− 1 in the second harvest) and the profitability (average reduction of US$2,780.0 ha− 1 in the second harvest) of using the biostimulant. However, this biostimulant mitigated damage to the crop, resulting in a lower impact on grain yield and profitability. Therefore, biostimulants should be applied at 3 DAA at a of 0.33 L ha− 1 (higher productivity observed: 3,946.9 kg ha− 1) or at 6 DAA at a rate of 0.66 L ha− 1 (greater profitability observed: US$4,835.4 ha− 1) to mitigate lactofen phytotoxicity. Thus, extreme and irreversible damage to soybean plants during their development caused by exposure to this herbicide is avoided.
Soybean productivity and financial viability with rhizobacteria, farming systems, and phosphorus doses
(2025) Cruz, Dennis Ricardo Cabral; Nascente, Adriano Stephan; Ferreira, Izabely Vitória Lucas; Monteiro, Natasha Ohanny da Costa; Duarte, Gabriella Alves; Silva, Mariana Aguiar; Rocha, Izaque de Sousa
This study investigates sustainable agricultural practices through the integration of multifunctional microorganisms and crop diversification in soybean cultivation. The experiment was conducted at Embrapa Arroz e Feijão, using a 2 × 2 × 4 factorial design with randomized blocks and four replications. The treatments involved the combination of four multifunctional microorganisms (Burkholderia sp. (BRM 32111), Serratia sp. (BRM 63523), Bacillus sp. (BRM 63524), and the control, without microorganisms), two phosphorus levels (50% and 100% of the recommended P2O5 dose), and two cropping systems (soybean/rice/common beans or soybean/corn/common beans). Soybeans were cultivated in the summer (November–January), rice or corn during the off-season (January–May), and common beans in winter (June–September). The results showed that the use of rhizobacteria BRM 32111 and BRM 63523 resulted in the highest soybean yields, offering the greatest economic returns among the treatments. Additionally, cultivating rice in the off-season, combined with the use of phosphorus-solubilizing rhizobacteria, demonstrated significant potential as a sustainable agricultural practice by reducing chemical fertilizer use and improving crop nutritional efficiency, promoting agroecological sustainability.
Inter-comparison of soybean models for the simulation of evapotranspiration in a humid continental climate
(2025-04) Silva, Evandro Henrique Figueiredo Moura da; Kothari, Kritika; Pattey, Elizabeth; Battisti, Rafael; Boote, Kenneth J.; Archontoulis, Sotirios V.; Cuadra, Santiago Vianna; Faye, Babacar; Grant, Brian; Hoogenboom, Gerrit
Accurate simulation of evapotranspiration (ET) with crop models is essential for improving agricultural water management and yield forecasting. Few studies have evaluated multiple soybean [Glycine max (L.) Merr.] models for simulating ET under conditions of low evaporative demand that is characteristic for a warm-summer humid continental climate. Six soybean crop models, encompassing 15 different modeling approaches, were evaluated for ET simulation and compared against eddy covariance data collected over five growing seasons in Ottawa, Canada. Models were first calibrated with phenology, in-season growth, and yield data, followed by calibration with measured ET and soil water content (SWC) data during the second step. After initial calibration, simulated daily ET was higher on average than measured ET, particularly during full canopy cover (normalized bias, nBias = 17.1 to 49.2% depending on the model). Following the second calibration, simulated daily ET was closer to measured values, but bias remained (nBias = 5.9 to 52.1% during full canopy). The ensemble median reduced uncertainty in the simulation of daily ET compared to most models, but DNDC remained the top-ranking model (nRMSE = 0.7 mm d−1, nBias = 11.2%). The MONICA model was most accurate simulating cumulative ET (RMSE = 39.9 mm, nBias = 11.3%), whereas the CROPGRO models excelled simulating SWC (RMSE= 0.04 to 0.05 m³ m−3, nBias = 0.10 to 0.9% depending on soil depth). This study was instrumental in evaluating the best ET methodologies and parameters in soybean models. However, there was bias across the models compared to measured eddy covariance ET in a humid environment. The results reveal the need to further investigate possible biases in ET estimates by eddy covariance over soybean canopies, and to review the role of night-time dew contributions to ET in process-based models.
Filter cake enriched with rockdust on the morphometry of cherry tomato and malagueta pepper seedlings via multivariate modeling
(2025) Cunha, Daíza Freire da; Silva, Patrícia Costa; Costa, Adriana Rodolfo da; Giongo, Pedro Rogerio; Barbosa, Kássia de Paula; Rodrigues, Ádria Pereira; Silva, Amanda de Brito; Bessa Neto, José Veira; Parreira, Júlio César Leão; Silva, Thanyewer Raiwer Leite; Mesquita, Marcio
The objective of this work was to evaluate the cherry tomato and chili pepper seedlings development adopting the agroindustrial by-product filter cake (FC) enriched with rock dust (RD). Two experiments were conducted, one with cherry tomatoes and the other with chili pepper in a greenhouse. The treatments were formed by combining the agroindustrial by-product filter cake and rock dust. The total length of the seedling (TL), aboveground height (Ah.), stem diameter (SD), number of leaves (NL), root length (RL), fresh root mass (FRootM), dry root mass (DRootM), fresh (FAM) and dry aboveground mass (DAM) have been evaluated. The pepper and cherry tomato crops morphometric data was submitted to descriptive statistical analysis and principal component analysis (PCA). Only the 80% FC + 20% RD treatment, which did not have a high coefficient of variation for the plant morphometric variables, characterizing the most efficient treatment for the seedlings morphometric development. It was verified that higher proportions of filter cake (treatment at 100% and 90% of the cake application) resulted in greater variability of the growth and development of pepper seedlings. It was also found that there is a high correlation between RL and TL, with correlation coefficients close to 1. Such behavior occurred as a result of the codependency of these crop systems. The 80% FC + 20% RD treatment showed the best results for the morphometric development of chili pepper and cherry tomato seedlings, which should be recommended for future experiments, as well as to be adopted by small producers.
Assessing precipitation trends between 1960 and 2021 using multiple trend indexes in the GOIÁS State and Federal District, Brazil
(2025-04) Battisti, Rafael; Dapper, Felipe Puff; Silva, Ayramanna Carlos Souza da; Mesquita, Marcio; Silva, Marcos Vinícius da; Andrade, Rafaella Resende; Lopes, Arthur Gabriel Caldas
Climate change is reshaping the global climate patterns with varying effects, necessitating a thorough analysis of historical precipitation trends. This study aimed to assess precipitation trends over 60 years in Goiás State and the Federal District of Brazil using data from 21 precipitation gauges maintained by the National Water and Basic Sanitation Agency of Brazil. The Mann–Kendall test was applied to evaluate the precipitation trend significance (α = 5%) from 1960 to 2021, and Sen's slope was applied for trend magnitude. The Standardised Anomaly Index (SAI), Rainfall Anomaly Index (RAI) and Standard Precipitation Index (SPI) were used. The region had a mean (max-min) annual precipitation of 1462 (2007–915) mm, concentrated between October and April. The Mann–Kendall test showed that 76% of sites had a significant reduction in rainfall, with Sen's slope reaching −60.42 mm decade−1. Only Goiânia showed a positive trend of 1.15 mm decade−1, but with no significant trend at 5% by the Mann–Kendall test. The results indicate that precipitation decreases in September, October and spring. The RAI and SAI highlighted rainfall reduction in October, moving to drier classes, whereas the other months remained stable. The SPI showed a decreasing trend at 3, 6, 12 and 24 months, whereas no significant trend was observed at 1 month. The SPI for 12 and 24 months showed intensification of drier classes in the recent period (2011–2021). The results indicated consistent rainfall reduction over the region, mainly in September, October and summer. Furthermore, the SPI indicated meteorological droughts of low intensity and increased hydrological droughts. This has wide-ranging implications, particularly for groundwater reservoirs, affecting urban areas, hydroelectric power generation and irrigation systems, increasing conflict and requiring an urgent plan for water use.
Spatio-temporal variability of sugarcane (Saccharum officinarum) yield in relation to edaphoclimatic factors in the central region of Brazil
(2025) Capuchinho, Frank Freire; Casaroli, Derblai; Alves Júnior, José; Evangelista, Adão Wagner Pêgo; Xavier, Maxuel Fellipe Nunes; Irigoyen, Andrea Inés; Moreira, Alisson Neves Harmyans
Context. Production of sugarcane (Saccharum officinarum) in Brazil holds a significant global position. However, it faces challenges in yield optimization due to unfavorable edaphoclimatic conditions and technological limitations. Aim. This study aimed to correlate the spatio-temporal variability of sugarcane yield with edaphoclimatic conditions in the central region of Brazil. Methods. This study included 11 sugarcane producing municipalities in central region of Brazil. It utilized 47 years of historical data on yield, climate, and soil. To isolate the climatic effects on yield (Yr), technological trends (YrNT) were removed via simple linear regression adjustment, followed by cluster analysis. Key results. Four groups of Yr and YrNT were identified. Group 1 exhibited the highest average yield (77 Mg ha−1), while Group 4 had the lowest (47 Mg ha−1), with a yield gap of approximately 10.2 Mg ha−1. Municipalities with the highest Yr averages were in Clusters 3 and 4 for climate, and Clusters 2 and 3 for soil. Conclusions. The higher occurrence of anomalies lower than 1.0 σ for climate Group 3 of YrNT indicates that unfavorable climatic conditions combined with inadequate production technologies can lead to significant yield losses (26% of years). Evaluating sugarcane yield by considering crop cycles and edaphoclimatic factors before technological trends can provide a more accurate insight into yield variability. Implications. Understanding the relationship between edaphoclimatic factors and sugarcane yield variation can guide targeted interventions, aiding in the development of strategies to mitigate losses in sugarcane farming.
Micropropagation and in vitro fructan production by Chresta exsucca DC. (Asteraceae)
(2025) Abdalla, Dayana Figueiredo; Silveira, Andreia Alves da Costa; Sibov, Sérgio Tadeu; Moraes, Moemy Gomes de
Chresta exsucca DC. (Asteraceae) is a species native to Cerrado that stores inulin-type fructans in its underground organs. These water-soluble polysaccharides are valuable in the pharmaceutical and food industries and are crucial in plant responses to abiotic stress. Although several Asteraceae species have been micropropagated, few have been studied for in vitro fructan production. This study aimed to establish the micropropagation protocol of C. exsucca and examine fructan production in the organs of plants cultivated in vitro. Cypselae of C. exsucca, collected from field-grown plants, were disinfested for in vitro germination. The seedlings provided nodal segments that were inoculated in Murashige and Skoog (MS) medium with varying concentrations of 6-benzylaminopurine (BAP) for shoot induction, followed by indole-3-acetic acid (IAA) for rooting. Fructans were analyzed in the organs of micropropagated plants. All cypselae of C. exsucca successfully germinated in vitro after the disinfestation treatment with 1.25% active chlorine followed by inoculation in MS medium without or with 100% of macronutrients. The highest shoot proliferation occurred on MS containing 4.44 µM BAP. Root elongation was most pronounced in the absence of IAA or at the lower concentration tested (0.57 and 2.86 µM), whereas higher IAA levels inhibited root extension. Plants acclimatized in a 1:1 mixture of commercial substrate and soil from C. exsucca’s natural habitat achieved a 73.3% survival rate. Inulin-type fructans were produced in vitro in roots and calluses but not in other organs. The micropropagation techniques applied were effective in obtaining fructan-producing clones of C. exsucca.
Drought immediately increases soluble sugar and decreases starch in seedlings of the shade-tolerant compared to the sun-tolerant ecotype of Paubrasilia echinata
(2025-04) Cuzzuol, Geraldo Rogério Faustini; Sánchez-Fonseca, Carlos Luis; Moraes, Moemy Gomes de; Macieira, Bernardo Pretti Becacici
How shade-tolerant and sun-tolerant plants will respond to the predicted increase in drought for tropical forests by the end of this century is a subject of global interest. One of the physiological defense mechanisms of plants against the harmful effects of drought is their ability to adjust their contents of non-structural carbohydrates – NSC (soluble sugars and starch) and cell wall polymers – CWP (hemicelluloses, cellulose, and lignin). As a research model, we used plants of the small leaf (shade-tolerant) and medium leaf (sun-tolerant) ecotypes of Paubrasilia echinata, a tree native to the Atlantic Forest of Brazil. The plants were subjected to drought (no watering) for 17 days when the water potential (Ψw) of the leaves reached -3 MPa. Then, they were watered daily (rehydration) for 36 days. In different periods, we evaluated the NSC and CWP contents of their leaves, stem, and roots. Intraspecific similarities and divergences occurred in the contents of these molecules. The shade-tolerant ecotype showed immediate responses to drought by raising the soluble sugar and hemicelluloses, and decreasing the starch contents (aerial organs). The lignin content increased in the aerial organs of both ecotypes and the cellulose content more in the sun-tolerant ecotype. After rehydration, the NSC and CWP contents of the two ecotypes were equal to their controls. We concluded that the shade-tolerant ecotype showed greater sensitivity to drought by demonstrating a greater need for NSC and hemicelluloses adjustments at the beginning of the drought. However, the drought did not affect the survival of the two ecotype's plants. If climate change forecasts for the southeastern region of Brazil prevail in the coming decades, natural or planted seedlings of the shade-tolerant ecotype of P. echinata may suffer greater consumption of its transient energy reservoir (starch). Such responses can compromise the functioning of their seedlings if droughts become more intense and frequent.
Foliar silicon fertilization improves physiological parameters and promotes gains in yields in pumpkin (Cucurbita moschata L.)
(2025) Xavier, Maxuel Fellipe Nunes; Flores, Rilner Alves; Reges, Nívea Patrícia Ribeiro; Carmo, Riandra Tenório do; Roberto, Ludmila de Almeida; Mendes, André Luiz Milhardes; Santos, Glenio Guimarães; Mesquita, Marcio; Abdala, Klaus de Oliveira
The supply of silicon (Si) via foliar application can mitigate biotic and abiotic stresses, protecting crops against adverse weather conditions. The objective is to evaluate the effect of leaf application of Si on the growth, nutrition, economic analysis, and yield of pumpkin. The experiment was carried out in a greenhouse in a randomized blocks design with five treatments and seven replications. The treatments were doses of Si: 0-control, 378, 756, 1,134, and 1,512 g ha−1 of Si, applied in the form of potassium silicate stabilized with sorbitol. In each treatment, potassium concentrations were balanced in the solution to eliminate the effect of this nutrient. The amounts of silicon applied were divided equally into three sprays throughout the crop cycle. Foliar application of Si promoted gains in Si content and accumulation in the plant and linearly increased the aerial part, fruit, and total dry mass production. Foliar fertilization with silicon promoted linear gains in fruit yield, reaching 9,032.17 kg ha−1 with the highest dose applied (1,512 g ha−1 of Si), in relation to the control treatment, without Si. Foliar fertilization with potassium silicate stabilized with sorbitol is efficient in promoting greater absorption, especially in non-accumulator plants such as pumpkin. With the greater absorption of Si by plants, there is an increase of up to 141% in fruit production, obtaining a maximum differential profit of US$ 4,397 ha−1 with the use of the highest applied dose, of 1,512 g ha−1, under the evaluated conditions of the present study.
Influence of nitrogen sources and foliar silicon fertilization on agronomic characteristics and differential profit from sugarcane stalk production
(2025) Xavier, Maxuel Fellipe Nunes; Flores, Rilner Alves; Carmo, Riandra Tenório do; Lima, Mateus de Leles; Sousa, Renato Gomide de; Dapper, Felipe Puff; Abdala, Klaus de Oliveira; Casaroli, Derblai; Marques, Letusa Momesso; Santos, Glenio Guimarães; Mesquita, Marcio
Appropriate nitrogen (N) availability ensures sugarcane crop longevity and yield, and foliar application of silicon (Si) can maintain or increase crop yields by inducing resistance to biotic and abiotic stresses. This study evaluated the influence of N sources and doses of foliar Si application on the agronomic characteristics of and differential profit from sugarcane stalk production. A field experiment was conducted with the second ratoon of sugarcane variety CTC-04 (2021/2022 harvest). The experimental design was arranged in randomized blocks with a 2 × 5 × 3 factorial scheme: two N sources [urea or calcium ammonium nitrate (CAN) plus the nitrification inhibitor 3,4-dimethylpyrazole succinic – DMPSA]; five Si doses of 0, 450, 900, 1350, or 1,800 g ha−1, divided into three sprays during the crop cycle; and three sampling times of 150, 240, or 305 days after cut (DAC). At each sampling time, biometric parameters, leaf nutrient content, pigment concentrations, technological quality, sugar yield, and stalk yield were evaluated, and differential profit was analyzed. Of the Si doses, foliar Si application at 900 g ha−1 resulted in the highest sugarcane biometric parameters, chlorophyll index, and leaf nutrient content in second ratoon. Ammonium and calcium nitrate associated with the nitrification inhibitor DMPSA increased sugarcane stalk yield by 12.14% and sugar yield by 14.30% compared with urea. In addition, foliar Si application was found to be an economically viable option. Foliar application of 900 g Si ha−1 increased the maximum profit by US$ 1,480.49 ha−1 for sugar yield and US$ 812 ha−1 for stalk yield when combined with ammonium and calcium nitrate associated with the nitrification inhibitor DMPSA as the N source.
Application of diagnosis and recommendation integrated system (DRIS) to sugarcane: a systematic literature review
(2025) Bueno, Amanda Magalhães; Flores, Rilner Alves; Leandro, Wilson Mozena; Andrade, Aline Franciel de; Santos, Glenio Guimarães; Verma, Krishan Kumar
The Diagnosis and Recommendation Integrated System (DRIS) is widely used for the interpretation of diagnostics from chemical analyses of soil and plant tissue in different cultures. The objective is to carry out a systematic literature review on the feasibility of applying DRIS to the diagnosis of current soil fertility and nutritional status of sugarcane crops. Searches were carried out in five databases (Web of Science, Springer Link, Science Direct, Scielo, and Google Scholar). For this, eight search terms (T) were used: (T1: DRIS, T2: sugarcane, T3: soil analysis, T4: leaf analysis; T5: nutritional diagnosis; T6: soil fertility; T7: critical levels; T8: sufficiency ranges), and 14 combinations (C) of the terms. Each combination was searched in three languages (English, Portuguese and Spanish) in each database. The selection criteria for publications were as follows: scientific articles, answering at least one of the following questions (Q): Q1. Is DRIS efficient in determining the nutritional diagnosis of sugarcane as a function of leaf nutrient content? Q2. Is DRIS efficient in determining soil fertility cultivated with sugarcane as a function of soil chemical analysis? Q3. Can DRIS be used to replace the critical levels and/or sufficiency ranges method? The searches yielded 1,547 results, of which, after careful analysis, only 17 met the prerequisites and were selected. The articles dated from 1976 to 2022, written by 17 different authors. There is a scarcity in the literature of works that relate the DRIS methodology in sugarcane cultivation to the results of soil analysis and that compare DRIS to conventional methods of soil and leaf nutritional diagnosis. Based on the literature surveyed, in general, DRIS is efficient in assessing the nutritional status of sugarcane and soil fertility in cultivation areas; however, its efficiency increases when there are standards and calculations of indexes based on local or regional data.
Metarhizium anisopliae engineering mediated by a CRISPR/Cas9 recyclable system
(2025) Virgílio, Maria Letícia de Siqueira; Quintela, Eliane Dias; Maciel, Liriel Helen Rodrigues; Goulart, Gabriela Souza Silva; Silva, José Francisco Arruda e; Cortês, Márcio Vinicius de Carvalho Barros
The advent of CRISPR/Cas technology has revolutionized genome editing, offering simplicity, precision, and cost-effectiveness. While its application in biological control fungi has been limited, including the cosmopolitan fungus Metarhizium anisopliae, recent advancements show promise. However, integrating cas9 and selection-marker genes into fungal genomes poses challenges, including reduced efficiency, toxicity, and off-target effects. Besides, marker-free genetic engineering through a CRISPR recyclable system presents a viable solution, enabling efficient mutant generation without compromising fitness and virulence. This study pioneers the construction of marker-free strains of M. anisopliae using a CRISPR/Cas9 recyclable system. Precise deletion of albA and ku70, alongside gfp cassette insertion, confirms the system efficiency. This innovative approach holds significant potential for facilitating in-depth molecular studies, understanding their ecological roles in agricultural systems, and enhancing biocontrol efficacy against insect pests through genetic improvement.
Rhizobacteria and silicon modulate defense, oxidative stress, and suppress blast disease in upland rice plants in low phosphorus soils under field conditions
(2025) Oliveira, Rodrigo Silva de; Ajulo, Akintunde Abiodun; Cardoso, Marco Antônio Adorno; Gonçalves, Ariany Rosa; Bezerra, Gustavo Andrade; Lanna, Anna Cristina; Castro, Adriano Pereira de; Filippi, Marta Cristina Corsi de
Association of bioagents and silicon is synergistic for mitigating leaf and panicle blast and low phosphorus (P) levels in upland rice, under greenhouse conditions. This study aimed to evaluate the potential of the bioagents and silicon interaction on blast disease severity suppression in upland rice plants, under field low P conditions. The experiment was conducted during two growing seasons (E1 and E2), in randomized block design with four replications, and consisted of five treatments, combining a mix of three rhizobacteria, BRM 32114 and BRM62523 (Serratia marcescens), and BRM32110 (Bacillus toyonensis), and three application methods (seed treatment, drenching, spraying). Calcium and magnesium silicate (2 t/ha) was applied over a low soil P, 30 days before sowing. Leaf blast (LBS) and panicle blast (PBS), area under the disease progress curve (AUDPC), activity of enzymes related to oxidative stress, pathogenesis-related (PR), biochemical indicators such as hydrogen peroxide, chlorophyll a and b, carotenoids, and grain yield (GY), were assessed. Bioagents and silicon suppressed LBS by 77.93 and PBS by 62.37%, reduced AUDPC by 77.3 (LBS) and 60.6% (PBS). The yield in E1 was 25% higher than in E2. The treatments statistically differ only in E2, the yield with bioagents and silicon (2435.72 kg ha−1) was 71.95% higher compared to the absolute control. All enzymatic activities related to oxidative stress and PR proteins were modulated by bioagents and silicon association. The association of rhizobacteria and silicon exhibited a synergistic effect, and represents a bioprotective combination to reduce the effects of different stresses and indirectly reduces the use of chemical inputs.
Cladosporium cladosporioides for disease control and defense response induction in upland rice grown under an agroecological system
(2025) Chaibub, Amanda Abdallah; Gundim, João Abrão Batista; Araújo, Leila Garcês de; Filippi, Marta Cristina Corsi de
Diseases in rice crops result in yield loss and pesticide overuse. Although agroecological systems enable more sustainable production, pest and disease management difficulties make biological control essential. The aim of this study was to assess the efficiency of different C. cladosporioides C24G application techniques in controlling rice diseases under field conditions and their effect on yield, defense enzymes, photosynthetic, and photoprotective pigments. The experiment consisted of six treatments and four repetitions in two growing seasons. In both growing seasons, treatments with C. cladosporioides C24G differed from the control for all the parameters studied. Treatments involving microbiolization and additional foliar spraying did not differ from those with only two applications. For leaf scald, brown spot and grain spot, treatments suppressed up to 94.30%, 64.41%, and 86.36%, respectively. Treatments with foliar spraying increased yield by up to 46.72%. Greater increases were also observed for the enzyme and pigment experiments in treatments involving leaf spraying. As such, incorporating C. cladosporioides into rice disease management improves yield under agroecological systems, thereby contributing to increasing the use of this cultivation system.
Multiplex PCR to detect Curtobacterium flaccumfaciens pv. flaccumfaciens and the common bean root pathogens Fusarium oxysporum f. sp. phaseoli and Fusarium solani f. sp. phaseoli
(2025) Oliveira, Maythsulene Inácio de Souza; Paula, Kássia Lorrany Marques de; Ferreira, Suellen Rodrigues; Lobo Junior, Murillo; Wendland, Adriane
Root diseases that affect common beans (Phaseolus vulgaris L.) may share similar symptoms, such as Fusarium wilt (Fusarium oxysporum f. sp. phaseoli), dry root-rot (Fusarium solani f. sp. phaseoli) and Curtobacterium wilt (Curtobacterium flaccumfaciens pv. flaccumfaciens). The difficulties for their accurate diagnosis include multiple infections in the field or a single plant, but molecular tools can overcome such drawbacks and identify causal agents accurately. The objective of this work was to develop a multiplex PCR (m-PCR) method to simultaneously identify three common bean pathogens, F. oxysporum f. sp. phaseoli (Fop), F. solani f. sp. phaseoli (Fs) and C. flaccumfaciens pv. flaccumfaciens (Cff). The approach included the design and validation of the new primers IGS1FOR and IGS1REV for F. solani f. sp. phaseoli and adjustments on primer concentration and annealing temperature. Multiplex PCR using IGS1FOR/ IGS1REV, CffFOR2/CffREV4 and A280/B310 primers did not change the pre-established procedures for detecting F. solani f. sp. phaseoli, C. flaccumfaciens pv. flaccumfaciens and F. oxysporum f. sp. phaseoli, and reactions with 0.4 to 0.8 μM of primers and annealing at 57 ºC resulted in clear, spaced amplicons in agarose gel, respectively with 143 (Fs), 306 (Cff)and 609 base pairs (Fop). The multiplex PCR technique detected pathogens in bean seeds infected by Curtobacterium and Fusarium spp. similarly to the standard ISTA method, even with a shorter seed immersion time; however, only Fusarium oxysporum f. sp. phaseoli was identified, with Fusarium solani f. sp. phaseoli not being detected in the tested cultivars. This is the first report of an m-PCR method to detect common bean phytopathogens.
Co-inoculation of beneficial microorganisms in upland rice cultivated at different phosphorus levels
(2025-03) Asobia, Princewill C.; Paula, Kássia Lorrany Marques de; Oliveira, Maythsulene Inácio de Souza; Bittencourt, Caroline D.; Ferreira, Adriane Wendland; Ferreira, Enderson Petrônio de Brito
Beneficial microorganisms can sustainably improve rice production. This study characterized indole-acetic-acid-producing and P-solubilizing bacteria, investigating their impact on upland rice through single or co-inoculation. Four bacterial strains (BRM 063573, BRM 67205, BRM 063574, and BRM 67206) were identified by 16S rRNA gene sequencing. A greenhouse experiment was arranged in a 20 × 3 factorial design with four replications. The first factor included 18 bacterial combinations and two controls (without fertilization or inoculant, and with fertilization but no inoculant). The second factor tested three phosphorus doses (25%, 50%, and 100% of the recommended P dosage). Growth and productivity parameters were determined. Based on the 16S rRNA gene sequencing, the bacteria BRM 063574 was closely related to Stenotrophomonas maltophilia, while BRM 063573 and BRM 67206 were closely related to Bacillus pumilus and BRM 67205 was closely related to Paenibacillus pabuli. Co-inoculation treatments generally outperformed single inoculations, improving performance in number of tillers, plant height, root volume, root weight, and shoot weight. Single inoculation and co-inoculation had different effects on number of pods, number of full grain and grain weight, with co-inoculation consistently giving better results. The variability in response to single inoculation suggests an inconsistency in the performance of single inoculants. Co-inoculation, on the other hand, consistently offered advantages, improving the number of pods, number of full grains and grain weight at different phosphate doses. Based on grain production, the co-inoculants BRM 67207 + BRM 67206 and BRM 67207 + BRM 063574 are most promising for use as rice inoculants, offering consistent benefits for improving yield.
Cover crops as a strategy for root rot management in common beans: effects on crop performance and root microbial dynamics in a Cerrado soil
(2025-03) Schulman, Pablo; Lopes Filho, Luiz César; Basílio, Juliana Pires; Barbosa, Elder Tadeu; Tormen, Nédio Rodrigo; Nunes, Rafael de Souza; Altmann, Nilvo; Moura, Jadson Belém de; Lobo Junior, Murillo
No-till farming is a key restoration technique that helps preserve soil health and productivity without expanding cultivated areas. Here, we investigate the influence of different cover crops on the performance and root microbial diversity of common beans in a Brazilian Cerrado soil. The study was conducted for five years on a commercial farm, with six treatments and three replicates. Treatments were evaluated yearly for yield and dry root rot severity (Fusarium spp.). Rhizospheric soil samples were analyzed for microbiome diversity using metataxonomics in the last year of the experiment. Oat and sunn hemp consistently performed better for severity, while a mix of cover crops, oat and palisade grass resulted in higher yields than fallow. Diversity metrics did not vary between treatments for both bacterial and fungal communities. Streptomyces was prominent in oat and sunn hemp, while Fusarium dominated the fungal community across treatments with a relative abundance of >35%. Characteristics prediction highlighted significant bacterial functions and fungal traits, with palisade grass showing distinct methanol oxidation and oat exhibiting diverse fungal endophytes, saprotrophs, and organic matter decomposers that may compete against Fusarium spp. Network analysis revealed variable co-occurrence patterns, with Fusarium spp. exhibiting different associations depending on the treatment. The network analysis also highlighted competing fungal genera that may guide biocontrol strategies. Mix, oat, and pearl millet were the cover crops favoring the highest number of genera negatively correlated with Fusarium spp. in the common bean rhizosphere. Future studies should explore the long-term effects and temporal dynamics of the common bean root microbiome.

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