Allometric models to estimate peanuts leaflets area by non-destructive method

Abstract

The determination of leaf area is fundamental for studies related to plant growth and physiology. Thus, non-destructive methods allow an accurate estimate of the leaf area through linear dimensions of the leaves. The research objective was to construct allometric equations to estimate the leaflet area of peanut cultivars. Then, 2,605 leaflets were collected from six peanut cultivars (IAC Caiapó, IAC 8112, Runner IAC 886, BRS Havana, BRS 151 L7, and IAC Tatuí), with more than 400 leaflets sampled for each cultivar. We measured the length, width, product between length and width, and leaflet area. Linear and non-linear models (linear, linear without intercept, power, and exponential) were built, and the best equation was chosen using the statistical criteria: highest coefficient of determination (R 2 ), Pearson's linear correlation coefficient (r), Willmott's agreement index (d), lowest Akaike information criterion (AIC), and root mean square of the error (RMSE). It was found that the models that used the product between length and width were the most suitable for estimating the leaflet area of peanut cultivars. Given the little intraspecific morphological variability, it was possible to group the cultivars, and model ̂= 0.875 * LW 0.929 was indicated to estimate the peanut leaflet area accurately, regardless of the cultivar.

Artificial neural network approach for predicting the sesame (Sesamum indicum L.) leaf area: A non-destructive and accurate method

“…Thus, the proposed regression model can be used to estimate the leaf area of the sesame using the product between leaf length and width (LW). For other species, models were also proposed to estimate leaf area using leaf product (LW) as an independent variable [ 20 , 21 , [68] , [69] , [70] ].

Fig.

…”

“…Regression models using length and width were proposed to estimate the leaf area of many oilseed species such as macaúba palm [ 11 ], sunflower [ 14 ], walnut [ 4 ], canola [ 15 , 16 ], chia [ 17 ], cocoa [ 18 ], brazil chestnut [ 19 ], moringa [ 20 ], peanut [ 21 ] and basil [ 22 ]. In addition to linear dimensions, such as length and width, other studies have proposed a correction coefficient to correct a systematic bias in estimation and increase the accuracy of leaf area measurements in plants [ [23] , [24] , [25] ].…”

Non-destructive method for estimating chrysanthemum leaf area

“…This model had the highest coefficient of determination (R 2 ) (0.9937), Pearson's correlation coefficient (r = 0.9847) and Willmott index (d = 0.9922) and the lowest Akaike's information criterion (AIC = 3032.5) and root mean square error (RMSE) values (1.601) (Table 2). The power models were also the best fit for estimating the LA of Tectona grandis (Tondjo et al, 2015), Manihot esculenta (Trachta et al, 2020) and Arachis hypogaea (Ribeiro et al, 2022c). In their study on chrysanthemum varieties, Fanourakis et al (2021) emphasized the importance of considering both leaf length (L) and width (W) when estimating leaf area (LA).…”

Non-destructive method for estimating leaf area of Ocimum gratissimum L. using leaf dimensions

“…Arachis hypogaea (Ribeiro et al, 2022a), Ocimum basilicum (Ribeiro et al, 2022b), Erythrina velutina (Ribeiro et al, 2022c), and Manilkara zapota (Ribeiro et al, 2023b).…”