Caracterização fisiológica, morfológica e determinação do índice de área foliar em linhagens de trigo

Abstract

Wheat (triticum aestivum L.) is one of the most important crops in the world. Thus, understanding the importance of culture and the growing demand to accelerate the progress of cultivar development, studies of agronomic, morphological and physiological parameters have become fundamental. The use of electromagnetic radiation by plants depends on the interception capacity of the canopy, thus varying according to morphological characteristics. Among them, leaf area is a critical variable for productivity. The ability of plants to intercept solar radiation is measured using the Leaf Area Index (LAI), defined as the ratio between leaf area and soil area occupied by the crop. Currently, methods to assess IAF are laborious and often destructive. Given the above, techniques for large-scale LAI determination are necessary to satisfy the demands. Among them, the use of remote sensing to estimate LAI is a promising method. The objective of the present study is to determine the LAI in wheat lines by destructive and non-destructive methods, and to correlate it with different agronomic and morphophysiological parameters. The study was carried out in the 2020 agricultural season, in Campo Erê – SC, Renascença –PR and Pato Branco – PR. Twelve wheat genotypes developed by the Genetic Improvement Program of UTFPR – Pato Branco were evaluated. The design was randomized blocks, with three replications. Among the physiological parameters, photosynthetic rate, transpiration and leaf nitrogen content were evaluated. The LAI was determined by destructive and non-destructive methods. The morphological parameters evaluated were: flag leaf angle, width and length of the flag leaf blade, sheath length, peduncle length, plant height and dry mass. Grain yield, thousand seed weight and hectoliter weight were determined at harvest. Data were subjected to joint analysis of variance, comparison of means and correlation analysis. The LAI was determined by the destructive method, ranging from 2.13 to 4.86. It was not possible to estimate the LAI by non-destructive method through machine learning. The LAI showed no correlation with the morphophysiological parameters. Therefore, it is not feasible to use these methods to estimate this parameter in the wheat crop at the phenological stage of grain filling. The lines UTFT170013, UTFT170500, UTFT170074, UTFT170242 and UTFT170588 showed good performance for most of the evaluated parameters and high yield, being promising for varietal development.