Conilon coffee outturn index: a precise alternative for estimating grain yield.

• Autor(a) principal: FIALHO, G. S.
• Data de Publicação: 2022
• Outros Autores: FONSECA, A. F. A. da, FERRAO, M. A. G., FERRÃO, R. F., OLIVOTO, T., NARDINO, M., REIS, E. F. dos, SAKIYAMA, N. S.
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)
• Texto Completo: http://www.alice.cnptia.embrapa.br/alice/handle/doc/1140751
• topic: Produção Agrícola; Coffea Canephora; Produtividade; Grão; Biometry

Coffee outturn can be defined as the ratio between the harvested coffee and its respective processed grains. This character is greatly influenced by genotypic and environmental effects, and in breeding programs your analysis is costly and time-consuming. In this sense, the use of an outturn index to estimate coffee yield on experimental plots is a desirable measure aiming at reducing resources and time in postharvest evaluations. Thus, the present study aimed to evaluate the accuracy of the use of an outturn index equal to 4.0, in the estimation of Conilon coffee grains production. This index indicates that four kilograms of harvested fruit would be needed to obtain one kilogram of processed grains. Based on the average of 157 genotypes conducted in three trials and four harvests, we evaluated the relationship between harvested fruits and processed grains (FcBe), the observed (OGY), and the estimated grain yield per plant (EGY) based on FcBe equal to 4.0 (an outturn index). Descriptive statistics, adequation test for EGY, and the coincidence of occurrence of genotypes observations relating to the top 20% of all observations of OGY and EGY. In the estimation of grain yield in Conilon, the use of FcBe equal to 4.0 showed high precision in the average of the analyzed trials. However, further studies should be conducted to elucidate the effects of climate variables on the yield of Conilon coffee, especially in atypical crop years. Thus, the use of an outturn index becomes interesting in cases where the number of genotypes to be evaluated is very large and a screening of the promising ones is desirable