Produção de matéria seca da braquiária de acordo com os atributos químicos de um Latossolo em Selvíria, Mato Grosso do Sul

• Autor(a) principal: Montanari, Rafael [UNESP]
• Data de Publicação: 2013
• Outros Autores: Carvalho, Morel de Passos e [UNESP], Filho, Marcelo Carvalho Minhoto Teixeira [UNESP], Dalchiavon, Flávio Carlos
• Tipo de documento: Artigo
• Idioma: por
• Título da fonte: Repositório Institucional da UNESP
• DOI: 10.1590/S0034-737X2013000400011
• Texto Completo: http://dx.doi.org/10.1590/S0034-737X2013000400011; http://hdl.handle.net/11449/76577
• topic: Brachiaria decumbens; Crude protein; Kriging; Nitrogen content; Precision farming; Soil fertility

Rustic forages as the signal-grass are predominant in areas of Cerrado in extensive livestock systems that favor soil degradation. However, with time, not even these forages can have a good development in those areas. The objective of this study was to analyze the variability of plant and soil attributes; to define the linear and spatial correlations between signal-grass yield and the chemical attributes of the studied soil, and to evaluate, among the chemical attributes of the soil, which one that best explain the variability in this forage yield. The experiment was conducted in an area that had been under pasture for more than 30 years, belonging to UNESP - Ilha Solteira Campus, located in Selvíria - MS. A geostatistical grid was installed in an oxisol, for soil and plant data collection, with 121 sampling stations, consisted of eleven transections with 160 m width in the direction of the Cartesian axes. The dry mass yield of signal-grass was low, presenting high variation. The attributes MSr, N, PB, MO1, MO2, pHa1, pHa2, pHk1 and pHk2 did not vary at random. They presented data variability from low to high and followed clearly defined spatial patterns, ranging between 17.7-162.9 m. There was significant linear correlation at 1% between MSr and N leaf, and between MSr and PB. The cross semivariograms MSr=f(N) and MSr=f(PB) confirmed that the dry matter can be estimated from data of nitrogen leaf and crude protein content of this forage.