Energy Cane x Sugarcane Microregion Interaction in the State of Pernambuco: Sugarcane for Production of Bioenergy and Renewable Fuels
João de Andrade Dutra Filho,
Frank Gomes-Silva,
Lauter Silva Souto,
Anielson dos Santos Souza,
Rômulo Gil de Luna,
Guilherme Rocha Moreira,
Moacyr Cunha Filho,
Marcelo Cleon de Castro Silva,
Andréa Chaves Fiuza Porto,
Cícero Carlos Ramos de Brito,
Mária Lindomárcia Leonardo da Costa,
Odair Honorato de Oliveira,
Amaro Epifânio Pereira Silva,
Fabiana Aparecida Cavalcante Silva,
André Luiz Pinto dos Santos,
Tercilio Calsa Júnior
Affiliations
João de Andrade Dutra Filho
Biological Science Nucleus, Vitoria Academic Center, Federal University of Pernambuco, Rua Alto do Reservatório, s/n-Bela Vista, Vitória de Santo Antão 55608-680, Pernambuco, Brazil
Frank Gomes-Silva
Department of Statistics and Informatics, Federal Rural University of Pernambuco, Rua Dom Manuel de Medeiros, s/n-Dois Irmãos, Recife 52171-900, Pernambuco, Brazil
Lauter Silva Souto
Agri-Food Science and Technology Center, Federal University of Campina Grande, Rua Jairo Vieira Feitosa, 1770-Pereiros, Pombal 58840-000, Paraiba, Brazil
Anielson dos Santos Souza
Agri-Food Science and Technology Center, Federal University of Campina Grande, Rua Jairo Vieira Feitosa, 1770-Pereiros, Pombal 58840-000, Paraiba, Brazil
Rômulo Gil de Luna
Agri-Food Science and Technology Center, Federal University of Campina Grande, Rua Jairo Vieira Feitosa, 1770-Pereiros, Pombal 58840-000, Paraiba, Brazil
Guilherme Rocha Moreira
Department of Statistics and Informatics, Federal Rural University of Pernambuco, Rua Dom Manuel de Medeiros, s/n-Dois Irmãos, Recife 52171-900, Pernambuco, Brazil
Moacyr Cunha Filho
Department of Statistics and Informatics, Federal Rural University of Pernambuco, Rua Dom Manuel de Medeiros, s/n-Dois Irmãos, Recife 52171-900, Pernambuco, Brazil
Marcelo Cleon de Castro Silva
Agri-Food Science and Technology Center, Federal University of Campina Grande, Rua Jairo Vieira Feitosa, 1770-Pereiros, Pombal 58840-000, Paraiba, Brazil
Andréa Chaves Fiuza Porto
Dom Agostinho Ikas Agricultural College, Federal Rural University of Pernambuco, Avenida Dr. Francisco Corrêa, 643–Centro, São Lourenço da Mat 54735-000, Pernambuco, Brazil
Cícero Carlos Ramos de Brito
Federal Institute of Pernambuco, Avenida Professor Luiz Freire, 500, Cidade Universitária, Recife 50740-545, Pernambuco, Brazil
Mária Lindomárcia Leonardo da Costa
Animal Science Department, Federal University of Paraiba, 12 Rodovia, PB-079, Areia 58397-000, Paraiba, Brazil
Odair Honorato de Oliveira
Department of Agrarian Science, Federal University of Grande Dourados, R. João Rosa Góes, 1761-Vila Progresso, Dourados 79825-070, Mato Grosso, Brazil
Amaro Epifânio Pereira Silva
Carpina Sugarcane Experimental Station, Federal Rural University of Permambuco, Rua Ângela Cristina Canto Pessoa de Luna, s/n, Carpina 55810-700, Pernambuco, Brazil
Fabiana Aparecida Cavalcante Silva
Phytosanitary Diagnosis Laboratory, Northeast Strategic Technologies Center, Avenida Professor Luís Freire, 1, Cidade Universitária, Recife 50740-545, Pernambuco, Brazil
André Luiz Pinto dos Santos
Department of Statistics and Informatics, Federal Rural University of Pernambuco, Rua Dom Manuel de Medeiros, s/n-Dois Irmãos, Recife 52171-900, Pernambuco, Brazil
Tercilio Calsa Júnior
Department of Genetics, Biosciences Center, Federal University of Pernambuco, Avenida Professor Moraes Rego, 1235, Cidade Universitária, Recife 50670-901, Pernambuco, Brazil
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.
