Estimation of common bean (Phaseolus vulgaris) leaf area by a non-destructive method

Abstract

The aim of this study was to develop mathematical models to estimate the leaf area of common bean (Phaseolus vulgaris) in irrigated and non-irrigated water regimes from linear dimensions. An experiment was carried out in a completely randomized design with a 3×2 factorial arrangement (three cultivars: Triunfo, Garapiá and FC 104; two water regimes: irrigated and non-irrigated) with 25 replicates each. A total of 523 trifoliates were collected throughout the crop cycle. The length (L, cm) and width (W, cm) of the central leaflet of the trifoliate were measured and their product (LW) (cm²) calculated. Then, the leaf area of these trifoliates was determined by digital photography methods using ImageJ® software, and using leaf discs. The number of samples required to estimate the leaf area of a trifoliate was determined to define which method is the most accurate to be used as the real leaf area in generating equations to estimate the leaf area in common bean. The relationship between area by digital photographs and the dimensions of the central leaflet of the trifoliate (L, W and LW) was fitted by linear, quadratic and power models. Subsequently, the predictive capacity of the equations was assessed by the root mean square error (cm2 trifoliate-1), mean absolute error (cm2 trifoliate-1), index of agreement and Pearson’s correlation coefficient. Sample size varied between cultivars, water regimes and evaluation methods. It is more appropriate to use the leaf area provided by ImageJ® as real for comparison purposes in generating models to estimate leaf area from linear measurements, in common bean. The general equation LA = 1.092L1.945 can be used in the tested regimes without accuracy losses.

Dissecting the genetic architecture of leaf morphology traits in mungbean (Vigna radiata (L.) Wizcek) using genome‐wide association study

“…Simple or multiple linear and quadratic regression equations have been developed for use nondestructively in other crops such as sunflower ( Helianthus annuus L., cv. Melody) (Rouphael et al., 2007), black gram ( V. mungo L. Hepper) (Mishra et al., 2000), soybean (Pandey & Singh, 2011; Wiersma & Bailey, 1975), common bean (Pohlmann et al., 2021), horticultural crops (Khan et al., 2016), 15 vines (X. Yu et al., 2020), and maize (Stewart & Dwyer, 1999). Using 3125 leaves from 780 taxa, Schrader et al.…”

“…Indirect measurements, such as the nondestructive use of mathematical relationships, and the use of point cloud technology (Y. between leaf area and other leaf dimensions would be more advantageous (Bakhshandeh et al, 2010(Bakhshandeh et al, , 2011. Researchers have developed nondestructive predictive models for leaf area in various crops such as soybean (Bakhshandeh et al, 2010(Bakhshandeh et al, , 2011Wiersma & Bailey, 1975), common bean (Phaseolus vulgaris) (Pohlmann et al, 2021), maize (Zea mays) (Raj et al, 2021;Stewart & Dwyer, 1999), vines (Vitis spp.) (X.…”

“…Indirect measurements, such as the nondestructive use of mathematical relationships, and the use of point cloud technology (Y. Wang et al., 2021) between leaf area and other leaf dimensions would be more advantageous (Bakhshandeh et al., 2010, 2011). Researchers have developed nondestructive predictive models for leaf area in various crops such as soybean (Bakhshandeh et al., 2010, 2011; Wiersma & Bailey, 1975), common bean ( Phaseolus vulgaris ) (Pohlmann et al., 2021), maize ( Zea mays ) (Raj et al., 2021; Stewart & Dwyer, 1999), vines ( Vitis spp.) (X. Yu et al., 2020), trees (Y. Wang, Jin, et al., 2019), urdbean ( Vigna mungo ) (Mishra et al., 2000), peach ( Prunus persica ) (Demirsoy et al., 2004), horticultural crops (Khan et al., 2016), tomato ( Lycopersicon spp.)…”

Dimensionamento amostral de caracteres de feijão em condição hídrica irrigada e não irrigada

“…Londrina, v. 43, n. 5, p. 2323-2338, set./out. 2022 diameter of the main stem (SD, cm), measured between the cotyledonary node and the node of unifoliate leaves, with a caliper; root length (RL, cm), measured with a millimeter ruler; fresh and dry weights of shoots (SFW and SDW) and roots (RFW and RDW) (g), by weighing immediately after collection and drying at 65 ºC until constant weight and weighing again; number of nodules (NDL) with a diameter greater than 2 mm and their respective fresh and dry weights (NFW and NDW), which were weighed immediately after counting and dried at 65 ºC until constant weight and weighed again; leaf area (LA, cm plant -1 ) determined by the equation LA = 1.092C1.945 (Pohlmann et al, 2021) during stages V4 to R8 (Fernández et al, 1986); leaf temperature (LT, ºC), measured daily at 15h00 during the water deficit in the central leaflet of the trefoil located in the upper third, using an infrared thermometer. The following data referring to yield components were collected at the end of the crop cycle at R9: number of pods (NP); number of grains per plant (GPl) and per pod (GPo), by counting; pod length (PL), measured as the distance between the ends of the pod with a millimeter ruler; and dry weight of grains at 13% moisture (GDW), which were weighed after drying in the sun.…”