Sweet pepper yield modeling via deep learning and selection of superior genotypes using GBLUP and MGIDI.

ABSTRACT: Intelligent knowledge about Capsicum annuum L. germplasm could lead to effective management of germplasm. Here, 29 accessions of sweet pepper were investigated in two separate randomized complete block design with three replications in the field condition. Fruit yield accompanied by 13 agro-morphological traits were recorded in two experiments. Genomic fingerprinting of accessions was done by using 10 ISSR primers. The convolutional neural network (CNN) models via outputs of both correlation coefficients and stepwise regression showed the high accuracy of CNN model through correlation coefficients (R² = 0.879) in predicting fruit yield of sweet pepper. Fruit thickness and fruit width were identified simultaneously as significant components in both models. Genomic best linear unb

SUBMITTER: Maleki HH 

PROVIDER: S-EPMC12034786 | biostudies-literature | 2025 Apr

REPOSITORIES: biostudies-literature