five

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

收藏
DataCite Commons2022-06-07 更新2024-07-29 收录
下载链接:
https://scielo.figshare.com/articles/dataset/Conilon_coffee_outturn_index_a_precise_alternative_for_estimating_grain_yield/20012812/1
下载链接
链接失效反馈
官方服务:
资源简介:
ABSTRACT. 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.
提供机构:
SciELO journals
创建时间:
2022-06-07
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作