Alcinei Mistico Azevedo

Fenotipagem de alta eficiência para vitamina A em banana utilizando redes neurais artificiais e dados colorimétricos

Banana is one of the most consumed fruits in Brazil and an important source of minerals, vitamins and carbohydrates for human diet. The characterization of banana superior genotypes allows identifying those with nutritional quality for cultivation and to integrate genetic improvement programs. However, identification and quantification of the provitamin carotenoids are hampered by the instruments and reagents cost for chemical analyzes, and it may become unworkable if the number of samples to be analyzed is high. Thus, the objective was to verify the potential of indirect phenotyping of the vitamin A content in banana through artificial neural networks (ANNs) using colorimetric data. Fifteen banana cultivars with four replications were evaluated, totaling 60 samples. BASIC AREA Article High-efficiency phenotyping for vitamin A in banana using artificial neural networks and colorimetric data César Fernandes Aquino1*, Luiz Carlos Chamhum Salomão1, Alcinei Mistico Azevedo2 1. Universidade Federal de Viçosa Departamento de Fitotecnia Viçosa (MG), Brazil. 2. Universidade Federal de Minas Gerais Instituto de Ciências Agrárias Montes Claros (MG), Brazil. *Corresponding author: cesarfernandesaquino@yahoo.com.br Received: Oct. 2, 2015 – Accepted: Dec. 17, 2015 For each sample, colorimetric data were obtained and the vitamin A content was estimated in the ripe banana pulp. For the prediction of the vitamin A content by colorimetric data, multilayer perceptron ANNs were used. Ten network architectures were tested with a single hidden layer. The network selected by the best fit (least mean square error) had four neurons in the hidden layer, enabling high efficiency in prediction of vitamin A (r2 = 0.98). The colorimetric parameters a* and Hue angle were the most important in this study. High-scale indirect phenotyping of vitamin A by ANNs on banana pulp is possible and feasible.Banana is one of the most consumed fruits in Brazil and an important source of minerals, vitamins and carbohydrates for human diet. The characterization of banana superior genotypes allows identifying those with nutritional quality for cultivation and to integrate genetic improvement programs. However, identification and quantification of the provitamin carotenoids are hampered by the instruments and reagents cost for chemical analyzes, and it may become unworkable if the number of samples to be analyzed is high. Thus, the objective was to verify the potential of indirect phenotyping of the vitamin A content in banana through artificial neural networks (ANNs) using colorimetric data. Fifteen banana cultivars with four replications were evaluated, totaling 60 samples. For each sample, colorimetric data were obtained and the vitamin A content was estimated in the ripe banana pulp. For the prediction of the vitamin A content by colorimetric data, multilayer perceptron ANNs were used. Ten network architectures were tested with a single hidden layer. The network selected by the best fit (least mean square error) had four neurons in the hidden layer, enabling high efficiency in prediction of vitamin A (r2 = 0.98). The colorimetric parameters a* and Hue angle were the most important in this study. High-scale indirect phenotyping of vitamin A by ANNs on banana pulp is possible and feasible.

Agrupamento multivariado de curvas na desidratação em raízes de batata-doce

Minimizing post-harvest losses during sweet potato storage is imperative for the producer and consumer. Therefore, the use of statistical tools to select the superior genotypes that have good post-harvest characteristics will contribute to breeding programs. The aim of this study was to demonstrate the applicability of the multivariate clustering technique as an alternative in the post-harvest study on root dehydration among sweet potato accessions. A total of 74 accessions of sweet potatoes were evaluated in a randomized complete block design in four replicates. The roots were stored in plastic boxes at room temperature and the loss of fresh matter was measured on times 0, 4, 8, 12 and 16 days after harvest. The multivariate clustering was based on the Euclidean distance and the Tocher optimization method on adjusted curves using linear and nonlinear models. The nonlinear best fit model was Brody, which allowed the discrimination of accesses with higher and lower dehydration. The multivariate grouping of curves was efficient in the post-harvest study on sweet potato access roots.

Biometric evaluation of morpho-agronomic traits in pepper lines and hybrids

Hortic. bras., Brasília, v.36, n.3, July September 2018 P of the genus Capsicum are known worldwide for its pungency, with a great variety of color and shape, being consumed in several ways. The genus also has important characteristics to produce condiments, such as flavor and aroma (Alves, 2015). The species C. annuum presents a great deal of genetic variation, including sweet and spicy varieties, the species C. chinense is of great economic importance. Its diversity center is the Amazon basin region. Despite of the importance of these species, little information on morphological and productive traits, which meet industry needs, is available. As consequence, it is difficult to develop the industrial market, which is important for the national agriculture (Jarret & Berket, 2012). Some breeding programs have devoted efforts to obtain hybrids with resistance to diseases and superior agronomic traits (Fonseca, 2008), aiming to meet demands for fresh and processing consumption. Characterization of Capsicum species is of great interest for germplasm banks, since the great variability is not completely described yet (Sudré, 2010). Thus, we conclude that characterizing Capsicum genotypes, in order to enhance genetic improvement and release new cultivar of the genus, is necessary. The aim of this study was to evaluate lines and hybrids of pepper (C. chinense and C. annuum) aiming to obtain information on agronomic performance, heterosis, heterobeltiosis, phenotypic ANDRADE JÚNIOR, VC; PEDROSA, CE; MIRANDA, TG; VALADARES, NR; PEREIRA, SL; AZEVEDO, AM. 2018. Biometric evaluation of morphoagronomic traits in pepper lines and hybrids. Horticultura Brasileira 36: 357-361. DOI http://dx.doi.org/10.1590/S0102-053620180312

Architectural diversity and galling insects on Caryocar brasiliense trees

Galling insects are a highly sophisticated herbivore group on Caryocar brasiliense, a tree that represents the main income source for many communities. The effect of architectural diversity of C. brasiliense trees on galling insect community diversity and abundance was studied. The abundance of adult insects and galled leaves were seven and 1.6 times higher in trees with a greater height/width of canopy (RHW) ratio, respectively. Gall parasitoid richness was 1.8 times greater on trees with higher RHW. Zelus armillatus (Lepeletier & Serville) (Hemiptera: Reduviidae) and ant numbers were 5.8 and 2.7 higher on trees with the largest and smallest RHW, respectively. More complex plant architectures favored species diversity for galling insects and their natural enemies. The competition among four galling insect species for space and feeding and the evidence of “prudence strategy” were, for the first time, observed for galling insects in the Brazilian Cerrado biome.