Modelagem e desenvolvimento de aplicação tecnológica Mobile para estimativa não-destrutiva de área foliar de feijão-caupi.

Abstract

Cowpea is a crop of global importance, which is why many landraces and improved cultivars are explored. The leaves of these genetic materials have intrinsic characteristics that distinguish them. Thus, the objective was to adjust linear regression models and implement them in mobile technological applications to assist in the non-destructive estimation of leaf area of landraces and improved cultivars of cowpea. The cultivation was carried out at the Semiarid Sustainable Development Center of the Federal University of Campina Grande. Cowpea leaflets were collected, on which leaf dimensions were measured and then regression models were adjusted for non-destructive estimation of leaf area. Performance evaluation and validation of the models were carried out. Based on the results, it is recommended to use models based on the product of length and width to estimate the leaf area of Paulistinha (y = 0.6926x + 1.8475 R² = 0.9527), BRS Novaera (y = 0 .6914x - 0.0977 R² = 0.9794), BRS Pajeú (y = 0.6752x - 0.0682 R² = 0.9852), BRS Miranda (y = 0.6688x - 0.2357 R² = 0.9622) , BRS Pujante (y = 0.6624x + 0.642 R² = 0.9846) and BRS Tapahium (y = 0.6738x + 0.8833 R² = 0.9922). Where x represents the product (C * L). Allometric models can be used with high performance for non-destructive estimation of leaf area of landraces and improved cowpea cultivars based on linear dimension measurements. The mobile technological application LAMA – Leaf Area Measurement Assistant is an efficient and applicable tool in the field for non-destructive estimation of cowpea leaf area and can be downloaded for free from the Play Store. Google (After registration).