Next Article in Journal
Multi-Target β-Protease Inhibitors from Andrographis paniculata: In Silico and In Vitro Studies
Previous Article in Journal
Diversion of Carbon Flux from Sugars to Lipids Improves the Growth of an Arabidopsis Starchless Mutant
Open AccessArticle

Developing an Accurate and Fast Non-Destructive Single Leaf Area Model for Loquat (Eriobotrya japonica Lindl) Cultivars

1
Department of Agricultural Sciences, University of Naples Federico II, 80055 Naples, Italy
2
CREA Research Centre for Plant Protection and Certification, 90011 Bagheria (Palermo), Italy
3
Department of Agriculture and Forest Sciences, Tuscia University, 01100 Viterbo, Italy
*
Author to whom correspondence should be addressed.
Plants 2019, 8(7), 230; https://doi.org/10.3390/plants8070230
Received: 22 June 2019 / Revised: 9 July 2019 / Accepted: 16 July 2019 / Published: 17 July 2019
(This article belongs to the Section Plant Modeling)
In this research, seven different models to predict leaf area (LA) of loquat (Eriobotrya japonica Lindl) were tested and evaluated. This species was chosen due to the relevant importance of its fruit as an appreciated early summer product and of its leaves and flower as a source of additional income within the nutraceutical and functional food markets. The analysis (calibration and validation) was made using a large dataset (2190) of leaf width (W), leaf length (L), and single LA collected in ten common loquat cultivars. During the analysis, the results obtained using one- and two-regressor models were also evaluated to assess the need for fast measurements against different levels of accuracy achieved during the final estimate. The analysis permitted to finally select two different models: 1) a model based on a single measurement and quadratic relationship between the single LA and W (R2 = 0.894; root mean squared error [RMSE] = 12.98) and another model 2) based, instead, on two measurements (L and W), and on the linear relationship between single LA and the product of L × W (R2 = 0.980; RMSE = 5.61). Both models were finally validated with an independent dataset (cultivar ‘Tanaka’) confirming the quality of fitting and accuracy already observed during the calibration phase. The analysis permitted to select two different models to be used according to the aims and accuracy required by the analysis. One, based on a single-regressor quadratic model and W (rather than L) as a proxy variable, is capable of obtaining a good quality of fitting of the single LA of loquat cultivars (R2 = 0.894; RMSE = 12.98), whereas, the other, a linear two-regressor (i.e., W and L) model, permitted to achieve the highest prediction (R2 = 0.980; RMSE = 5.61) of the observed variable, but double the time required for leaf measurement. View Full-Text
Keywords: Indirect measurement; plant phenotyping; leaf shape; model calibration; bootstrap; validation Indirect measurement; plant phenotyping; leaf shape; model calibration; bootstrap; validation
Show Figures

Figure 1

MDPI and ACS Style

Teobaldelli, M.; Rouphael, Y.; Fascella, G.; Cristofori, V.; Rivera, C.M.; Basile, B. Developing an Accurate and Fast Non-Destructive Single Leaf Area Model for Loquat (Eriobotrya japonica Lindl) Cultivars. Plants 2019, 8, 230. https://doi.org/10.3390/plants8070230

AMA Style

Teobaldelli M, Rouphael Y, Fascella G, Cristofori V, Rivera CM, Basile B. Developing an Accurate and Fast Non-Destructive Single Leaf Area Model for Loquat (Eriobotrya japonica Lindl) Cultivars. Plants. 2019; 8(7):230. https://doi.org/10.3390/plants8070230

Chicago/Turabian Style

Teobaldelli, Maurizio; Rouphael, Youssef; Fascella, Giancarlo; Cristofori, Valerio; Rivera, Carlos M.; Basile, Boris. 2019. "Developing an Accurate and Fast Non-Destructive Single Leaf Area Model for Loquat (Eriobotrya japonica Lindl) Cultivars" Plants 8, no. 7: 230. https://doi.org/10.3390/plants8070230

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Search more from Scilit
 
Search
Back to TopTop