Search

The maintenance of the variability of plant genetic resources is important both for conservation purposes and for the expansion of the genetic bases of the species. Machine learning is an additional tool with great potential that has been used in the search for solving various agricultural challenges. In this article we study the genetic divergence between tobacco genotypes by multivariate methods and verify the efficiency of computational algorithms, aiming at the identification of promising genotypes. Through multivariate analyses, three divergent groups were formed. Both approaches had high accuracy in classification. An artificial neural network with a hidden layer containing three neurons obtained an accuracy of 0.98, while the Random Forest accuracy was 0.98 and the decision tree 0.96. These values demonstrate how powerful these tools are and reinforce their use in studies aimed at maintaining the germplasm bank and also in tobacco conservation and genetic improvement programs in the Recôncavo region of Bahia.

Abstract: The objective of this work was to determine the optimal size of experimental plots for the evaluation of agronomic characteristics and fruit quality of papaya, by the linear model of plateau response, under soil and climatic conditions of the Recôncavo Baiano region, in the state of Bahia, Brazil. The experiment consisted of a uniformity test, with the papaya lineage L78, at 3×2 m spacing, in 16 rows with 22 plants, totaling 352 plants and 2,112 m2 useful area. Each plant was considered as a basic unit, and 11 forms of pre-established plots, with rectangular and row formats, were obtained. The agronomic characteristics and fruit quality were evaluated in the plots. Optimal plot size varied greatly among the variables related to agronomic characteristics, with a greater participation of the variable number of marketable fruit per plant at 14 months (16 basic units). The optimal plot size for the evaluation of the agronomic characteristics and fruit quality in papaya is eight experimental units, with 48 m2 area, at a spacing of 3 m between rows and 2 m between papaya plants.

Crop production systems increasingly require sustainable practices such as organic fertilization. Crops like Physalis peruviana L., commonly known as Cape gooseberry, still lack information on the use of organic compost as an alternative to increase productivity. In this scenario, the aim of this study was to evaluate the effect of doses of organic compost on the growth and initial development of P. peruviana L. in a dystrocohesive Yellow Latosol. The experiment was carried out in a greenhouse in a completely randomized design, with six treatments of rates of the organic fertilizer (0, 15, 30, 45 and 60 t ha-1) and an additional control with chemical fertilization. Each treatment consisted of 15 replications. The variables evaluated were plant height, stem diameter, number of leaves, number of flowers, number of fruits, shoot dry mass, and root volume. Cape gooseberry cultivated with organic compost showed growth comparable to those cultivated in soil without fertilization. In this study, the organic fertilizer produced from tree pruning waste and animal manure compost promoted significant gains in height (27.83 cm plant-1), stem diameter (9.23 mm plant-1), number of leaves (51.12 plant-1), number of fruits (5.33 plant-1), shoot dry mass (2.04 g plant-1), and root volume (0.70 g plant-1). The organic compost at the rate 45 t ha-1 provided the largest number of fruits, and therefore, it is recommended for the production of Cape gooseberry in dystrocohese Yellow Latosol.

O alumínio tóxico em altas concentrações no solo interfere no crescimento e desenvolvimento da mamoneira (Ricinus communis L.), afetando principalmente seu sistema radicular e dessa forma, diminuindo a produtividade da cultura. Nesse sentido, uma população de 117 linhagens de mamona foram submetidas à dose de 30 mg L-1 de Al+3 em solução nutritiva, sob condição hidropônica com o objetivo de avaliar e selecionar linhagens tolerantes ao alumínio tóxico. O experimento foi realizado no Laboratório de Seleção Precoce do Núcleo de Melhoramento Genético e Biotecnologia (NBIO) pertencente ao Centro de Ciências Agrárias, Ambientais e Biológicas da Universidade Federal do Recôncavo da Bahia, Cruz das Almas – BA. O delineamento foi inteiramente casualizado, com quatro repetições de seis plântulas por parcela. A dose utilizada, 30 mg L-1,interferiu no desenvolvimento das linhagens, agrupando-as diferentemente em cada caráter avaliado. Pela análise conjunta dos dados, existe variabilidade genética para tolerância ao alumínio tóxico, distribuindo as linhagens em cinco grupos distintos, permitindo a seleção das linhagens por apresentarem as melhores características quanto à tolerância ao alumínio tóxico.