Dissertations and Theses

Summary

Modern agriculture in the international context proposes innovations for agribusiness, especially for agricultural practices. However, this progress must help the rural entrepreneur to increase efficiency, using sustainable natural resources: water, land and energy. Thus, the objective of this study was, to verify the potential of the sensors to obtain the spectral data of an argisol with coffee cultivation. We used a set of data with a grid 51 soil samples on 39 hectares, with coffee cultivation (Yellow Catuaí, lineage IAC 62). Obtaining the color variables: hue, value, chroma, red, green and blue was determined by diffuse reflectance spectroscopy (DRS) and mobile near sensor (MNS). The results were related to soil attributes in the following cases: redMNS and clay: (R2 = 0.70, p <0.01), greenMNS and CTC (R2 = 0.73, p <0.01), redMNS and P (R2 = 0.64, p <0.05), blueMNS and EC (R2 = 0.96, p <0.01) and, greenMNS and Fe (R2 = 0.75, p <0.01). For the plant atributes, were: greenMNS and P17 (R2 = 0.70, p <0.01), defects with regressions ranging from 0.71 - 0.84 and, redMNS and productivity (R2 = 0.95, p <0.01). The results showed that the use of the color determined by red, green and blue allowed to identify soil attributes and areas with productive and qualitative potentials of coffee. For the study in the Midwest Paulista Plateau, a grid was realized in an area of 13 million hectares, totaling 600 samples in the depth of 0.00-0.20 meters. In these samples, the color variables were determined. Similarity was observed in the use of DRS and MNS methods. The DRS semivariograms were range for the hue, value, chroma, red, green and blue variables of 112 km, 216 km, 19 km, 207 km, 183 km and 158 km, respectively. With the use of MNS, the ranges were: 19 km, 226 km, 30 km, 160 km, 218 km and 75 km, respectively. The crossed semivariograms estimated the physical-chemical attributes (clay, cation exchange capacity - CTC, phosphorus - P and hematite-Hm). Crossed semivariograms explained the maximum correlation distance observed between the variables. The results of the MNS showed that the color in the red, green and blue systems can be used to predict the content of clay (77%), CTC (99%), P (90%) and Hm (70%). With the use of DRS, red, green and blue systems predict the content of clay (79%), CTC (94%), P (86%) and Hm (67%). These results show that color is a safe indication of soil attributes. As an alternative of low cost, the MNS has shown to be an efficient tool that allows the evaluation of these attributes.