贝叶斯多性状模型在低氮营养条件下环境高效阿拉比卡咖啡中的应用

IF 1.2 4区 农林科学 Q2 AGRICULTURE, MULTIDISCIPLINARY
Antônio Carlos da Silva Júnior, W. M. Moura, L. Torres, I. G. Santos, Michele Jorge da Silva, C. F. Azevedo, C. Cruz
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引用次数: 0

摘要

在过度施氮对环境和经济造成影响的背景下,鉴定更有效利用氮的阿拉比卡咖啡品种是一项重要的战略,也是必要的。虽然阿拉比卡咖啡的育种数据具有多性状结构,但它们往往是在单一性状结构下进行分析的。因此,本研究的目的是利用贝叶斯多性状模型,从广义上估计遗传力,并在限氮栽培中选择具有较好遗传潜力(理想农艺性状)的阿拉比卡咖啡品种。试验在温室内进行,20个阿拉比卡咖啡品种生长在低氮含量(1.5 mM)的营养液中。试验设计采用随机分组,每组3个重复。利用阿拉比卡咖啡育种计划的6个农业形态性状和5个营养效率指标。采用马尔可夫链蒙特卡罗算法估计遗传参数和遗传值。土壤形态性状具有较高的可遗传性,可信区间(95%概率)为:〖h2 = 0.9538 ~ 5.89E-01。贝叶斯多性状模型为低氮环境下阿拉比卡咖啡的遗传改良提供了合适的策略。阿拉比卡咖啡品种Icatu Precoce 3282、Icatu Vermelho IAC 4045、acai Cerrado MG 1474、Tupi IAC 1669-33、Catucaí 785/15、Caturra Vermelho和Obatã IAC 1669/20在低氮浓度条件下表现出更大的种植潜力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Multiple-trait model by Bayesian inference applied to environment efficient Coffea arabica with low-nitrogen nutrient
: Identifying Coffea arabica cultivars that are more efficient in the use of nitrogen is an important strategy and a necessity in the context of environmental and economic impacts attributed to excessive nitrogen fertilization. Although Coffea arabica breeding data have a multi-trait structure, they are often analyzed under a single trait structure. Thus, the objectives of this study were to use a Bayesian multitrait model, to estimate heritability in the broad sense, and to select arabica coffee cultivars with better genetic potential (desirable agronomic traits) in nitrogen-restricted cultivation. The experiment was carried out in a greenhouse with 20 arabica coffee cultivars grown in a nutrient solution with low-nitrogen content (1.5 mM). The experimental design used was in randomized blocks with three replications. Six agromorphological traits of the arabica coffee breeding program and five nutritional efficiency indices were used. The Markov Chain Monte Carlo algorithm was used to estimate genetic parameters and genetic values. The agromorphological traits were considered highly heritable, with a credibility interval (95% probability):〖 H 2 = 0.9538 – 5.89E-01. The Bayesian multitrait model presents an adequate strategy for the genetic improvement of arabica coffee grown in low-nitrogen concentrations. Coffee arabica cultivars Icatu Precoce 3282, Icatu Vermelho IAC 4045, Acaiá Cerrado MG 1474, Tupi IAC 1669-33, Catucaí 785/15, Caturra Vermelho and Obatã IAC 1669/20 demonstrated greater potential for cultivation in low-nitrogen concentration.
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来源期刊
Bragantia
Bragantia AGRICULTURE, MULTIDISCIPLINARY-
CiteScore
2.40
自引率
8.30%
发文量
33
审稿时长
4 weeks
期刊介绍: Bragantia é uma revista de ciências agronômicas editada pelo Instituto Agronômico da Agência Paulista de Tecnologia dos Agronegócios, da Secretaria de Agricultura e Abastecimento do Estado de São Paulo, com o objetivo de publicar trabalhos científicos originais que contribuam para o desenvolvimento das ciências agronômicas. A revista é publicada desde 1941, tornando-se semestral em 1984, quadrimestral em 2001 e trimestral em 2005. É filiada à Associação Brasileira de Editores Científicos (ABEC).
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