Non‐destructive prediction of pigment content in lettuce based on visible–NIR spectroscopy

BACKGROUND Lettuce (Lactuca sativa L.) is one of the most important salad vegetables in the world, with a number of head shapes, leaf types and colors. The lettuce pigments play important physiological functions, such as photosynthetic processes and light stress defense, but they also benefit human...

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Bibliographic Details
Published in:Journal of the science of food and agriculture 2017-05, Vol.97 (7), p.2015-2022
Main Authors: Steidle Neto, Antonio José, Moura, Lorena de Oliveira, Lopes, Daniela de Carvalho, Carlos, Lanamar de Almeida, Martins, Luma Moreira, Ferraz, Leila de Castro Louback
Format: Article
Language:English
Subjects:
Agronomy
anthocyanin
Anthocyanins
Anthocyanins - chemistry
Antioxidants
Carotenoids
Carotenoids - chemistry
chlorophyll
Chlorophyll - chemistry
Chlorophylls
Estimating
Farming
Lactuca - chemistry
Lactuca - growth & development
Lactuca sativa
Lettuce
Lettuces
Mathematical models
partial least squares regression
Pigments
Plant Leaves - chemistry
spectral reflectance
Spectroscopy, Near-Infrared - methods
Spectrum analysis
Vegetables - chemistry
Vegetables - growth & development
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Summary:BACKGROUND Lettuce (Lactuca sativa L.) is one of the most important salad vegetables in the world, with a number of head shapes, leaf types and colors. The lettuce pigments play important physiological functions, such as photosynthetic processes and light stress defense, but they also benefit human health because of their antioxidant action and anticarcinogenic properties. In this study three lettuce cultivars were grown under different farming systems, and partial least squares models were built to predict the leaf chlorophyll, carotenoid and anthocyanin content. RESULTS The three proposed models resulted in high coefficients of determination and variable importance for the projection values, as well as low estimative errors for calibration and external validation datasets. These results confirmed that it is possible to accurately predict chlorophyll, carotenoid and anthocyanin content of green and red lettuces, grown in different farming systems, based on the spectral reflectance from 500 to 1000 nm. CONCLUSION The proposed models were adequate for estimating lettuce pigments in a quick and non‐destructive way, representing an alternative to conventional measurement methods. Prediction accuracies were improved by using the detrending, smoothing and first derivative pretreatments to the original spectral signatures prior to estimating lettuce chlorophyll, carotenoid and anthocyanin content, respectively. © 2016 Society of Chemical Industry
ISSN:0022-5142
1097-0010
DOI:10.1002/jsfa.8002