A non-destructive method for estimating onion leaf area

Abstract

Leaf area is one of the most important parameters for characterizing crop growth and development, and its measurement is useful for examining the effects of agronomic management on crop production. It is related to interception of radiation, photosynthesis, biomass accumulation, transpiration and gas exchange in crop canopies. Several direct and indirect methods have been developed for determining leaf area. The aim of this study is to develop an indirect method, based on the use of a mathematical model, to compute leaf area in an onion crop using non-destructive measurements with the condition that the model must be practical and useful as a Decision Support System tool to improve crop management. were used and the leaf area for individual leaves was computed using two indirect methods, one based on the use of an automated infrared imaging system, LI-COR-3100C, and the other using a digital scanner EPSON GT-8000, obtaining several images that were processed using Image J v 1.43 software. A total of 1146 leaves were used. Before measuring the leaf area, 25 parameters related to leaf length and width were determined for each leaf. The combined application of principal components analysis and cluster analysis for grouping leaf parameters was used to reduce the number of variables from 25 to 12. The parameter derived from the product of the total leaf length (L) and the leaf diameter at a distance of 25% of the total leaf length (A25) gave the best results for estimating leaf area using a simple linear regression model. The model obtained was useful for computing leaf area using a non-destructive method. Keywords leaf area • onion • non-destructive method • mathematical model.

Relative leaf expansion rate and other leaf-related indicators for detection of drought stress in chili pepper (Capsicum annuum L.).

“…Linear regression model is reliable for estimating LA of chili pepper if LW is used as predictor as shown in Figure 1. Similar results were reported by Serdar and Demirsoy (2006) in chestnut, Rouphael et al (2010) in watermelon, Gao et al (2012) in rose, Córcoles et al (2015) in onion, Aminifard et al (2016) in coneflower, Padrón et al (2016) in bell pepper, and Küçükönder et al (2016) in tomato.…”

Response of Onion Yield and Quality To Different Planting Date, Methods and Density

“…Leaf area (cm 2 /plant) = 0.000199 + (1.277 × leaf length ×leaf diameter at a distance of 25% of the total leaf length ) (Corcoles et al, 2015).…”

Automated Grapevine Cultivar Identification via Leaf Imaging and Deep Convolutional Neural Networks: A Proof-of-Concept Study Employing Primary Iranian Varieties

“…Indeed, indirect, nondestructive methods using regression models for estimating leaves' dimensions (width and/or length) have recently resolved agronomic and physiologic dilemmas. Such procedures have increasingly found implementation on leaf analysis across several plants such as cacao [10], chestnut [11], fava bean [12], hazelnut [13], ginger [14], maize [15], onion [16] and pepper [17].…”