Non-destructive leaf area estimation in habanero chili (Capsicum chinense Jacq.)

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Published: Mar 15, 2022
Keywords:
Dimension-related trait Leaf shape Model validation Weight-based predictor Zero intercept regression

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Lakitan, B.
College of Agriculture, Universitas Sriwijaya, Inderalaya 30662, Indonesia; Research Center for Sub-optimal Lands, Universitas Sriwijaya, Palembang 30139, Indonesia
Susilawati, S.
College of Agriculture, Universitas Sriwijaya, Inderalaya 30662, Indonesia
Wijaya, A.
College of Agriculture, Universitas Sriwijaya, Inderalaya 30662, Indonesia
Ria, R. P.
College of Agriculture, Universitas Sriwijaya, Inderalaya 30662, Indonesia
Putri, H. H.
College of Agriculture, Universitas Sriwijaya, Inderalaya 30662, Indonesia

Abstract

The best fit models were polynomial (RL2=0.9731; Rw2=0.9620) and power (RL2=0.9692; Rw2=0.9592) regressions if single predictor of leaf length (L) or width (W) was used. Meanwhile, if LW was used, the best fit models were the zero-intercept linear (RLw2=0.9929) and power (RLw2=0.9962) regressions. Forcing the intercept to zero yielded better estimation for smaller leaves and did not significantly alter the coefficient of determination. Configuration of scattered data helped to recognize the curving trend and should be used as reference in selecting an appropriate regression type. The second-order polynomial regression curve has a single bend, therefore, far-end of the curve would either rise to infinity or curve down after a rising start. These both cases are an inherited weakness of the second-order polynomial regression beyond range of collected data. Both problems associated with the decrease of leaf area (LA) at higher predictor values and under-estimating of LA at lower predictor value were successfully eliminated by opting to use the power regression if L2W or LW2 as predictors. Accuracy and reliability of separated L (R2=0.9843) or W (R2=0.9899) was lower than combined LW (R2=0.9960) as predictor in case of habanero chili. Significant differences in specific leaf fresh weight (SLFW) and leaf water content (LWC) between young leaves and mature leaves should be recognized as a source of discrepancy before considering using weight-related traits in developing LA estimation model. Use of 120 to 160 regularly-shape leaves were sufficient for creating an accurate LA estimation if the selected leaves were evenly distributed and covering wide range of leaf size in habanero chili.

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How to Cite
Lakitan, B., Susilawati, S., Wijaya, A., Ria, R. P., & Putri, H. H. (2022). Non-destructive leaf area estimation in habanero chili (Capsicum chinense Jacq.). International Journal of Agricultural Technology, 18(2), 633–650. retrieved from https://li04.tci-thaijo.org/index.php/IJAT/article/view/6934
Issue
Vol. 18 No. 2 (2022): March
Section
Original Study
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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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