USO DO SOFTWARE AQUACROP PARA SIMULAR A RESPOSTA DO FEIJÃO À DIFERENTES REGIMES DE IRRIGAÇÃO

USO DO SOFTWARE AQUACROP PARA SIMULAR A RESPOSTA DO FEIJÃO À DIFERENTES REGIMES DE IRRIGAÇÃO MONALISA SOARES COSTA1*; EVERARDO CHARTUNI MANTOVANI2; FERNANDA LAMEDE FERREIRA DE JESUS3; ARTHUR CARNIATO SANCHES 4; JHON LENNON BEZERRA DA SILVA5 E JANNAYLTON ÉVERTON DE OLIVEIRA SANTOS6 1 Bolsista de longa duração – desenvolvimento tecnológico, Instituto Nacional do Semiárido, rua Antônio Aragão, 169, Nova Brasília, CEP 49680-000, Nossa Senhora da Glória, Sergipe, Brasil, Parte da dissertação de mestrado, [email protected] 2Professor Sênior doutor, Departamento de Engenharia Agrícola, Universidade Federal de Viçosa, Av. Peter Henry Rolfs, s/n - Campus Universitário, 36570-900, Viçosa, Minas Gerais, Brasil, [email protected] 3Professora Doutora, Departamento de Engenharia Agrícola, Universidade Federal Rural da Amazônia, Campus Tomé-Açu, Rod. PA 140, km 03, 68680-000, Tomé-Açu, PA, Brasil, [email protected] 4Professor Doutor, Faculdade de Ciências Agrárias, Universidade Federal da Grande Dourados, Rod. Dourados-Itahum, km 12 – Cidade Universitária, 79804-970, Dourados, MS, Brasil, [email protected] 5 Doutorando em Engenharia de Agrícola, Departamento de Engenharia, UFRPE, Rua Dom Manuel de Medeiros, s/n - Dois Irmãos, 52171-900, Recife, Pernambuco, Brasil, [email protected] 6 Professor Doutor, Departamento de Engenharia Agrícola, Universidade Federal Rural da Amazônia, Campus Tomé-Açu, Rod. PA 140, km 03, 68680-000, Tomé-Açu, PA, Brasil, [email protected] 1 RESUMO Os softwares de simulação de crescimento e desenvolvimento das culturas no campo têm tido bastante aplicação, visto o objetivo de técnicos e pesquisadores em evitar perdas no campo e almejar melhorias a cada cultivo. O feijão é bastante cultivado e consumido no Brasil, o que atrai atenção para o ajuste do software AquaCrop à cultura nas condições edafoclimáticas brasileiras. O objetivo deste trabalho foi analisar a resposta do software AquaCrop quando ajustado para condições de ambiente e irrigação em que o feijoeiro foi cultivado. Observou-se dados simulados semelhantes e em concordância estatística com o observado, com maiores diferenças no acúmulo de biomassa e balanço hídrico ao longo do ciclo da cultura. A semelhança entre os dados simulados e observados na cobertura do dossel ao longo do ciclo da cultura traduzem uma boa resposta da equação utilizada para converter o índice de área foliar em cobertura do dossel para a cultura do feijão. Conclui-se com o estudo, que o software AquaCrop é confiável para a simulação do crescimento e desenvolvimento do feijão, pois os dados obtidos em campo são semelhantes aos simulados pelo modelo. Palavras-chave: manejo, eficiência do uso da água, função de produção. COSTA, M. S.; MANTOVANI, E. C.; JESUS, F. L. F.; SANCHES, A. C.; SILVA, J. L. B.; SANTOS, J. E. O. U 2 ABSTRACT The simulation software’s of crop growth and development in the field has had many applications, since the aim of technicians and research in avoiding losses on the field and to target for improvements in each crop. The crop bean is highly cultivated and consumed in Brazil, what draws attention to the adjustment of the AquaCrop software for this crop under Brazilian edaphoclimatic conditions. This study aimed to analyze the response of the AquaCrop when adjusted for irrigation and greenhouse conditions in which the crop bean was cultivated. It was observed simulated data were similar and in statistical accordance with the observance in the field, to higher differences in biomass accumulation and water balance throughout the crop cycle. The similarity between the simulated and observed data for canopy coverage throughout the crop cycle translates a good answer of the equation used to convert the leaf area index canopy coverage for crop bean. We concluded with this study, that AquaCrop software is reliably simulating the growth and development of the crop bean because the data obtained on the field are similar to those simulated by the model. Keywords: management, water use efficiency, production function.

Exploitation of Drought Tolerance-Related Genes for Crop Improvement

Drought has become a major threat to food security, because it affects crop growth and development. Drought tolerance is an important quantitative trait, which is regulated by hundreds of genes in crop plants. In recent decades, scientists have made considerable progress to uncover the genetic and molecular mechanisms of drought tolerance, especially in model plants. This review summarizes the evaluation criteria for drought tolerance, methods for gene mining, characterization of genes related to drought tolerance, and explores the approaches to enhance crop drought tolerance. Collectively, this review illustrates the application prospect of these genes in improving the drought tolerance breeding of crop plants.

Plant Biostimulants: A Categorical Review, Their Implications for Row Crop Production, and Relation to Soil Health Indicators

Plant biostimulants are specialty products used to increase crop production and are quickly becoming common in the agricultural seed and chemical marketplace. Unlike traditional crop inputs, such as fertilizers or pesticides, biostimulants are unique in that a single product may have multiple avenues for influencing crop growth and development based on both the timing and the placement of application. This review presents a summary of the current status and descriptions of plant biostimulants with available literature on their uses in the row crop production of maize (Zea mays L.), soybean (Glycine max (L.) Merr.), wheat (Triticum aestivum), and other major crop species. Biostimulants have much potential to improve crop production through enhanced yields, grain quality, and increased sustainability of agronomic production systems, particularly in relation to nutrient management. However, there is great variability in the efficacy of biostimulants and a limited understanding of the mechanisms responsible in field-tested scenarios where differences are observed. These unknown mechanisms may align with the recognized soil health indicators, providing opportunities for unrealized biostimulant potential beyond crop growth and development. This review aims to identify the predominant types of crop biostimulants, the known understandings of their modes of action, and examples of their current field efficacy with an outlook for their future.

Evaluating Plant Potassium Status

Several methods exist for evaluating plant nutritional status. Looking for visual deficiency symptoms is perhaps the simplest approach, but once symptoms appear, crop performance has already been compromised. Several other techniques have been developed. All of them require correlation studies to provide plant performance interpretations. Reflectance is a remote sensing technique that detects changes in light energy reflected by plant tissue. It has proven successful in detecting nutrient deficiencies but does not yet have the ability to discriminate among more than one deficiency. Chemical assays of leaf tissue, known as tissue tests, require destructive sampling but are the standard against which other assessments are compared. Sufficiency ranges provide concentrations of each nutrient that are considered adequate for crop growth and development. They consider nutrients in isolation. Other approaches have been developed to consider how the concentration of one nutrient in tissue impacts the concentrations of other nutrients. These approaches strive to develop guidelines for maintaining nutrient balance within the plant. All approaches require large data sets for interpretation.

Application of nanosatellites PlanetScope data to monitor crop growth

In this research, an approach to monitor crop growth and development is presented using time series satellite data of high spatial resolution. Monitoring of winter wheat phenology based on images of PlanetScope constellations is considered. By applying various PlanetScope data processing types and ground based GreenSeeker data, differences of NDVI values at two variants of crop fertilization are determined. In particular, the following approaches were used in the research: obtaining the Top of Atmosphere Reflectance (TOA), the Planet Surface Reflectance (SR), and receiving NDVI image in Python using a Rasterio module. It was estimated that NDVI values derived from the surface reflectance imagery were significantly correlated to the ground data of a manual active GreenSeeker optical sensor (p < 0.05). The proposed simplified technique, based on PlanetScope NDVI time series, demonstrates the possibilities to monitor temporal changes in crop growth.