Cupuaçu tree genotype selection for an agroforestry system environment in the Amazon

Author:

Alves Rafael Moysés1ORCID,Chaves Saulo Fabrício da Silva2ORCID,Alves Rodrigo Silva3ORCID,Santos Thalita Gomes dos4ORCID,Araújo Dênmora Gomes de5ORCID,Resende Marcos Deon Vilela6ORCID

Affiliation:

1. Embrapa Amazônia Oriental, Brazil

2. Universidade Federal de Viçosa, Brazil

3. Universidade Federal de Lavras, Brazil

4. Universidade Federal do Ceará, Brazil

5. Universidade Federal Rural da Amazônia, Brazil

6. Embrapa Café, Brazil

Abstract

Abstract: The objective of this work was to select cupuaçu (Theobroma grandiflorum) tree progenies and individuals based on their agronomic traits, and, indirectly, to identify those adapted to an agroforestry system (AFS) environment in the Brazilian Amazon. For this purpose, 25 full-sib progenies were planted and tested in consortium with black pepper (Piper nigrum), banana (Musa spp.), and bacuri (Platonia insignis) trees. The experiment was carried out in a randomized complete block design, with five replicates and three plants per plot, from 2005 to 2019. For the statistical analyses, the phenotypic averages for production and incidence of witches’ broom disease, evaluated during 11 harvests, were used. Superior progenies and individuals were identified using the mixed model methodology (REML/BLUP), which led to the selection of ten plants from five families with superior agronomic traits. Cupuaçu tree progenies 6, 36, 37, 49, and 52 are the ones that best adapt to the environment of a multispecies AFS in the Amazon region because of their agronomic traits under competitive conditions. Ten matrices show agronomic potential and indirect adaptation to the AFS and can be used as clonal cupuaçu cultivars in this environment.

Publisher

FapUNIFESP (SciELO)

Subject

Agronomy and Crop Science,Animal Science and Zoology

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3