A B S T R A C TThe knowledge on the spatial variability of soil properties and crops is important for decision-making on agricultural management. The objective of this study was to evaluate the spatial variability of soil fertility and its relation with cocoa yield. The study was conducted over 14 months in an area cultivated with cocoa. A sampling grid was created to study soil chemical properties and cocoa yield (stratified in season, off-season and annual). The data were analyzed using descriptive and exploratory statistics, and geostatistics. The chemical attributes were classified using fuzzy logic to generate a soil fertility map, which was correlated with maps of crop yield. The soil of the area, except for the western region, showed possibilities ranging from medium to high for cocoa cultivation. Soil fertility showed positive spatial correlation with cocoa yield, and its effect was predominant only for the off-season and annual cocoa.Variabilidade espacial da fertilidade do solo e sua relação com a produtividade do cacaueiro R E S U M O O conhecimento da variabilidade espacial das propriedades do solo e das culturas é importante para a tomada de decisão sobre o manejo agrícola. Objetivou-se, neste estudo, avaliar a variabilidade espacial da fertilidade do solo e sua relação com a produtividade do cacaueiro. O estudo foi realizado durante 14 meses em uma área cultivada com cacaueiros. Foram estudados, a partir de um grid amostral, os atributos químicos do solo e a produtividade do cacaueiro (estratificada em safra, temporão e anual). Os dados foram analisados pela estatística descritiva e pela geoestatística. Os atributos químicos foram classificados utilizando-se a lógica fuzzy, para construção de um mapa de fertilidade do solo, o qual foi correlacionado com os mapas das estratificações da produtividade. O solo da área, com exceção da região oeste, apresentou possibilidades de média a alta, para a condução da cultura do cacau. A fertilidade apresentou correlação espacial positiva com a produtividade do cacaueiro, sendo seu efeito preponderante para o cacau temporão e anual. Key words:precision agriculture cocoa spatial variability fuzzy logic Palavras-chave: agricultura de precisão cacau geoestatística lógica fuzzy
Foliar fertilization is an interesting strategy for nutrition with micronutrients in perennial plants; among the micronutrients, zinc (Zn) deficiency is the most frequent in cocoa trees (Theobroma cacao L.). The present study aimed to evaluate the efficiency of Zn sources through foliar application for the cocoa crop. The experiment was carried out in a randomized block design, with 10 treatments and four replicates. Treatments were: foliar fertilizations containing 1 g L-1 of Zn using two inorganic sources (chloride and sulfate), in the presence or absence of additives (urea and sucrose); two organic sources (Zn-EDTA, and from chloride and sulfate); soil fertilization with 8 mg dm-3 of Zn, and a control (without addition of Zn). Foliar fertilizations with Zn were monthly applied for five months, and the experiment was conducted for 210 days. The results were subjected to analyses of variance and contrast. Zn fertilization, regardless of the form of application, increased Zn contents and accumulations in the leaves. Zn fertilization in the soil, at planting, led to a recovery rate by the plant similar to the mean value caused by foliar fertilizations. ZnCl2 caused higher Zn contents and accumulations in the leaves and was more efficient than sulfate and EDTA; addition of urea to the ZnSO4 solution increased Zn accumulation in the leaves, whereas addition of sucrose to the ZnCl2 solution reduced Zn content in the leaves.
Aim of study: To use artificial neural networks (ANN) to predict the values and spatial distribution of soil chemical attributes from apparent soil electrical conductivity (ECa) and soil clay contents. Area of study: The study was carried out in an area of 1.2-ha cultivated with cocoa, located in the state of Bahia, Brazil. Material and methods: Data collections were performed on a sampling grid containing 120 points. Soil samples were collected to determine the attributes: clay, silt, sand, P, K+, Ca2+, Mg2+, S, pH, H+Al, SB, CTC, V, OM and P-rem. ECa was measured using the electrical resistivity method in three different periods related to soil sampling: 60 days before (60ECa), 30 days before (30ECa) and when collecting soil samples (0ECa). For the prediction of chemical and physical-chemical attributes of the soil, models based on ANN were used. As input variables, the ECa and the clay contents were used. The quality of ANN predictions was determined using different statistical indicators. Thematic maps were constructed for the attributes determined in the laboratory and those predicted by the ANNs and the values were grouped using the fuzzy k-means algorithm. The agreement between classes was performed using the kappa coefficient. Main results: Only P and K+ attributes correlated with all ANN input variables. ECa and clay contents in the soil proved to be good variables for predicting soil attributes. Research highlights: The best results in the prediction process of the P and K+ attributes were obtained with the combination of ECa and the clay content.
Modo de acesso: World Wide Web Inclui bibliografia 1. Agricultura 2. Meio Ambiente 3. Zootecnia 4. Ciências Agrárias I. REDIN, Ezequiel II. Título. CDD-630 Sônia Márcia Soares de Moura -CRB 6/1896 O conteúdo dos artigos e seus dados em sua forma, correção e confiabilidade são de responsabilidade exclusiva dos seus respectivos autores www.poisson.com.br
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