Energy Cane x Sugarcane Microregion Interaction in the State of Pernambuco: Sugarcane for Production of Bioenergy and Renewable Fuels
Autor: | Marcelo Cleon de Castro Silva, Cícero Carlos Ramos de Brito, Odair Honorato de Oliveira, Tercilio Calsa Junior, Anielson dos Santos Souza, Rômulo Gil de Luna, Moacyr Cunha Filho, Amaro Epifânio Pereira Silva, Andréa Chaves Fiuza Porto, Frank Gomes-Silva, André Luiz Pinto dos Santos, João de Andrade Dutra Filho, Fabiana Aparecida Cavalcante Silva, Lauter Silva Souto, Guilherme Rocha Moreira, Maria Lindomárcia Leonardo da Costa |
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Rok vydání: | 2021 |
Předmět: |
0106 biological sciences
genotype × environment interaction Breeding program media_common.quotation_subject Agricultural engineering statistical models 01 natural sciences Adaptability high yield potential Saccharum spp Bioenergy stability traits Gene–environment interaction Cane Sugar Productivity media_common Mathematics biology prediction models Agriculture 04 agricultural and veterinary sciences Renewable fuels biology.organism_classification local varieties 040103 agronomy & agriculture 0401 agriculture forestry and fisheries Agronomy and Crop Science 010606 plant biology & botany |
Zdroj: | Agronomy Volume 11 Issue 6 Agronomy, Vol 11, Iss 1046, p 1046 (2021) |
ISSN: | 2073-4395 |
Popis: | Assessing the differential behavior of a group of genotypes in various environments is fundamentally important in any breeding program. As sugarcane is the most important crop in the state of Pernambuco, it is of great relevance to study its performance in different cultivation sites to assist in the recommendation of new cultivars that increase the productivity of the cane fields. In view of the new demand from the sugar-energy sector for cultivars with high energy potential, this work aimed to select and recommend new genotypes with high fiber and sucrose percentage in the sugarcane microregions of the state of Pernambuco. The methodologies used to classify genotypes for adaptability and stability were as follows: simple linear regression, the modified centroid method, additive main effects, multiplicative interaction analysis, and linear mixed models. Genotypes with higher productivity and specific adaptability to the tested microregions were identified. The methodologies applied were efficient and complementary in recommending genotypes with favorable prospects for increasing sugar productivity, cogeneration of electric energy and the production of renewable fuels. Genotypes 6, 7, 9, 14, 16, and 18 stand out in terms of the productivity of sugar and fiber, with high potential to be released as commercial cultivars. |
Databáze: | OpenAIRE |
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