Avaluation nutritional of forage peanut (Arachis pintoi) genotypes by multivariate techniques

• Autor(a) principal: Gondim Filho, Antônio Guedes Correa
• Data de Publicação: 2020
• Outros Autores: Moreira, Guilherme Rocha, Gomes-Silva, Frank, Cunha Filho, Moacyr, Gomes, Diego Alves, Ferreira, Alexandre Lima, Costa, Maria Lindomárcia Leonardo da, Ferreira, Denise Stéphanie de Almeida, Gonçalves, Nélio Cunha, Gomes, Silas Primola, Pimentel, Patrícia Guimarães, Santos, André Luiz Pinto dos, Amaral, Lucas Silva
• Tipo de documento: Artigo
• Idioma: por
• Título da fonte: Research, Society and Development
• Texto Completo: https://rsdjournal.org/index.php/rsd/article/view/6039
• topic: Análise multivariada; In Vitro; Logístico bicompartimental; Modelos não lineares.; Análisis multivariado; In Vitro; Logística bicompartimental; Modelos no lineales.; Multivariate analysis; In Vitro; Bicompartmental logistics; Non-linear models.

In order to evaluate if the period (rainy season) interferes in the nutritional value and select the best model that describes the accumulated gas values in ten genotypes of fodder peanuts (Arachis pintoi): 13251, 15121, 15598, 30333, 31135, 31496, 31534, 31828, cv. Itabela and cv. RIO in two seasons (dry season and rainy season). The experimental design used was that of random blocks, with ten treatments (genotypes) and three repetitions. It was evaluated: the production of dry matter kg ha-1; the contents of crude protein, fiber in neutral detergent, fiber in acid detergent, insoluble protein in acid detergent and accumulated production of gases adjusted to the models: Gompertz, Logístico, Brody, Von Bertalanffy and Logístico Bicompartimental. The fitting quality of the models was measured by means of the mean square of the residue (QMR), Akaike information criterion (AIC), Bayesian information criterion (BIC) and adjusted determination coefficient . The multivariate analysis used was the analysis of groupings with cofenetic correlation coefficient and the Rand index to check the quality of the fit and the quantity of groups. In the period of greater rainfall the genotypes 15121, 15598, 30333 and 31496 were considered those of better productivity and nutritional value. In the period of lower rainfall, genotypes 31828 and Itabela stood out as the best genotypes. The best adjusted model for both genotypes was the Logistic Bicomportamental model, for presenting lower AIC and BIC.