Open AccessShort Communication: Allometric model to estimate bifoliate leaf area and weight of kaffir lime (Citrus hystrix)
Author(s) -
Rahmat Budiarto,
Roedhy Poerwanto,
Edi Santosa,
Darda Efendi,
Andria Agusta
Publication year - 2021
Publication title -
biodiversitas
Language(s) - English
Resource type - Journals
eISSN - 2085-4722
pISSN - 1412-033X
DOI - 10.13057/biodiv/d220545
Subject(s) - mathematics , allometry , hystrix , stepwise regression , lime , horticulture , botany , frenet–serret formulas , linear regression , biology , statistics , ecology , geometry , paleontology , curvature
. Budiarto R, Poerwanto R, Santosa E, Efendi D, Agusta A. 2021. Short Communication: Allometric model to estimate bifoliate leaf area and weight of kaffir lime (Citrus hystrix). Biodiversitas 22: 2815-2820. Leaf is an economically important plant organ harvested from kaffir lime (Citrus hystrix DC.) for flavor and fragrance. This study aimed to formulate and validate regression models to estimate the leaf area (LA) and leaf weight (LW) of bifoliate kaffir lime leaf. There were 220 bifoliate leaves collected from 22 individual plants planted on Bogor. Bifoliate C. hystrix leaf consisted of upper main leaflets and winged petiole as lower secondary leaflet. All leaves were pooled and then grouped randomly into two subgroups for model formulation and validation, respectively. Linear, zero intercepts linear, exponential, logarithmic, polynomial, zero intercept polynomial and power regressions were used to properly estimate LA and LW. There was 63 formula obtained from nine predictors following seven regression models. Selected nine formulas with the highest R2 plus a stepwise formula were further tested for validation. Stepwise always showed the highest R2 followed by total of leaf ,length (TL) both on LA and LW estimation. However, the stepwise seemed to be more complicated and time wasted than TL regression model. Thus, our recommendation models for non-destructive and simple estimation in C. hystrix bifoliate leaf were LA = 0.1997 (TL)2 + 0.4571 (TL) and LW = 0.0067 (TL)2 + 0.0065 (TL), respectively.