Cor do solo na identificação de áreas com diferentes potenciais produtivos e qualidade de café

Abstract

Resumo -O objetivo deste trabalho foi verificar a eficácia da cor do solo na identificação de áreas com diferentes potenciais produtivos e qualidade de café, em Argissolo Vermelho-Amarelo desenvolvido de arenito, no Planalto Ocidental Paulista, no Estado de São Paulo. Coletaram-se 173 amostras em 39 ha, para a determinação de matiz, valor, croma e índice de avermelhamento do solo, com base nos dados da espectroscopia de reflectância difusa (ERD). Avaliaram-se, também, a produtividade e a qualidade do fruto de café, e calculou-se o índice de diagnose foliar (DRIS). A maior correlação espacial observada pelo variograma cruzado ocorreu entre matiz e DRIS, em pontos distantes em até 497 m. A menor correlação espacial foi observada em croma e produção, em pontos distantes em até 207 m. As áreas com o maior potencial de produtividade (20 a 33 sacas por hectare) apresentaram matiz entre 6,99 e 7,06, croma entre 5,00 e 5,08 e valor entre 4,40 e 4,45. As áreas com o menor potencial de produtividade (3 a 7 sacas por hectare) apresentaram matiz entre 7,27 e 7,68, croma entre 5,20 e 5,28 e valor entre 4,51 e 4,67. Nestes locais, o teor de argila foi de 16 g kg -1, os teores de P variaram entre 65 e 75 mg dm . O uso da cor determinada por ERD é eficaz para identificar áreas com diferentes potenciais produtivos e qualidade de café, com precisão de 61 a 97%.Termos para indexação: Coffea arabica, cor do solo, geoestatística, pedometria. Soil color for the identification of areas with different yield potential and coffee qualityAbstract -The objective of this work was to verify soil color effectiveness for the identification of areas with different yield potentials and coffee quality, in an Ultisol developed from sandstone, in Planalto Ocidental Paulista, in the state of São Paulo, Brazil. One hundred seventy-three samples were collected from 39 ha, for the determination of hue, value, chroma, and the soil redness index, based on data of diffuse reflectance spectroscopy (DRS). Productivity and quality of coffee fruit were also evaluated, and the leaf diagnosis index (DRIS) was calculated. The highest spatial correlation, observed in the cross variogram, occurred between hue and DRIS in points up to 497 m apart. The lowest spatial correlation was observed for chroma and production, in points spaced by up to 207 m. The areas with the highest yield potential (20 to 33 bags per hectare) showed hue between 6.99 and 7.06, croma between 5.00 and 5.08, and value between 4.40 and 4.45. The areas with the lowest productivity potential (3 to 7 bags per hectare) showed hue between 7.27 and 7.68, chroma between 5.20 and 5.28, and value between 4.51 and 4.67. In these places, clay content was of 16 g kg -1, P levels varied between 65 and 75 mg dm . The use of the color determined by DRS is effective to identify areas with different productive potentials and coffee quality, with 61 to 97% accuracy.

Sampling Density for Characterizing the Physical Quality of a Soil Under Coffee Cultivation in Southwestern Minas Gerais

“…Silt presented the lowest value of range, showing a higher spatial variability. TPV presented a range slightly higher than 150 m and the other attributes showed ranges higher than 200 m. In addition, TS was the most homogeneous attribute, demonstrated by a range value close to 300 m. Similar results were observed in areas with similar geology and pedology (Sanchez et al, 2005;Carmo et al, 2016;Siqueira et al, 2010b), which reinforce the relationship between soil physical quality and the geology of the area.…”

“…Santos et al (2017) studied the physical attributes of a sandy textured Oxisol cultivated with conilon coffee and found a lower coefficient of variation for macropores (27.60%), total sand (8.72%), silt (18.43%), and clay (18.30%) when compared to the results obtained in our study, being the result of differences in the soil type found in the area. Carmo et al (2016), studying the quality of the beverage coffee as a function of soil color and attributes of an Ultisol (Argissolo Vermelho Amarelo, Brazilian Soil Classification System) from sandstone in the State of São Paulo, verified coefficients of variation for clay that ranged from 17 to 24%. On the other hand, Sanchez et al (2005) studied the soil physical attributes of an Oxisol (Latossolo Vermelho-Amarelo, Brazilian Soil Classification System) cultivated with coffee in the State of Minas Gerais and observed, on average, coefficients of variation of 10% for clay content.…”

Magnetic and spectral signatures of Cerrado soils in the state of Goiás, Brazil

“…Although determining colors in the field and in the laboratory involves different steps, the color obtained by DRS can be useful in various study conditions. Carmo et al (2016), for example, assessed DRSestimated colors to distinguish areas regarding the yield and quality of coffee (Coffea arabica L.) bean, and Peluco et al (2015) showed that the DOR, measured by DRS, can assist in mapping and identifying areas with different potential of phosphorus adsorption. It should be noted that Hm and Gt, two mineral pigment agents of soils (Lepsch, 2011), have different phosphorus adsorption capacities in the soil.…”

“…Diffuse reflectance spectroscopy (DRS) and magnetic susceptibility (MS) are alternative techniques that can be used to estimate soil properties such as: iron oxides (Viscarra Rossel et al, 2010;Bahia et al, 2015); silicate minerals, including kaolinite, illite, and smectite (Viscarra Rossel, 2011;Mulder et al, 2013); chemical attributes and grain size Demattê et al, 2016;Viscarra Rossel et al, 2016); phosphorus adsorption (Camargo et al, 2015;Peluco et al, 2015); and soil color (Aquino et al, 2016;Carmo et al, 2016).…”

Carbono orgânico e atributos físico-químicos de um solo do município de Paragominas – PA

“…A cor do solo é apontada, por muitos pedólogos, como uma das propriedades morfológicas mais significativas, que, por meio dela, é possível verificar informações a seu respeito. Os principais fatores que influenciam na tonalidade que o solo irá apresentar está atrelada, principalmente, ao material de origem (rochas), posição na paisagem, vegetação, clima, umidade, presença de matéria orgânica e mineralógica (Carmo et al, 2016).…”