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

Abstract

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.

Non-destructive in Situ Measurement of Aquaponic Lettuce Leaf Photosynthetic Pigments and Nutrient Concentration Using Hybrid Genetic Programming

“…The concentration (mg/g) of included leaf pigments namely chlorophyll a, chlorophyll b, β-carotene, anthocyanin, and lutein were spectrophotometrically determined using optical densities (OD) of 480 nm, 495 nm, 663 nm, 645 nm, and 700 nm according to the procedure described by Ben Ghnaya, Charles, Hourmant, Ben Hamida, & Branchard (2007) and Gholami, Rahemi, Kholdebarin, & Rastegar (2012) and the adapted pigment equations (1-4). Anthocyanin pigment concentration (mg/g) that is based on cyanidin-3-glucoside extraction was adapted from the procedure done by Lee, Durst, & Wrolstad (2005) and Steidle Neto et al (2016) which is the pH-differential method that dilutes 0.1% of hydrochloric acid (HCL) to every 1 ml of leaf extract. Potassium chloride (KCl) and sodium acetate (C 2 H 3 NaO 2 ) buffers for pH 1.0 and 4.5, respectively, were diluted to leaf extracts before 30 minutes of centrifugation, then, samples undergo spectrophotometric measurement in the 520 nm and 700 nm wavelengths (5).…”

“…The most related techniques in this study are partial least square regression and quadratic regression using RGB and HSI color spaces (Table 5). The developed DT-MSRGP model completely bested these techniques by Steidle Neto et al (2016) and Yang et al (2016) in predicting chlorophylls, beta-carotene, anthocyanin, lutein, and vitamin C concentrations. Though Steidle Neto et al (2016) has a 9% advantage in the prediction accuracy of anthocyanin, their laboratory technique used 99.5% acetone instead of 75%, and the concentration convention used is mg/kg instead of mg/g.…”

“…The developed DT-MSRGP model completely bested these techniques by Steidle Neto et al (2016) and Yang et al (2016) in predicting chlorophylls, beta-carotene, anthocyanin, lutein, and vitamin C concentrations. Though Steidle Neto et al (2016) has a 9% advantage in the prediction accuracy of anthocyanin, their laboratory technique used 99.5% acetone instead of 75%, and the concentration convention used is mg/kg instead of mg/g. Likewise, the partial least regression was applied to the derived color of leaf extract and not to the raw leaf itself.…”

“…There is a study that conducted the combined effect of adjusting red and blue light intensity and nutrient solution control to the growth and quality of lettuce confirming that intense illumination and low nitrate in hydroponic tank results in high vitamin C yield in lettuce leaves (Song et al, 2020). Customary effective techniques in measuring phytopigments are through colorimetry (Henderson, 2015;Song et al, 2020), hyperspectral reflectance imaging (Pacumbaba & Beyl, 2011;Steidle Neto et al, 2016), chlorophyll fluorescence imaging (Hägele et al, 2016), artificial neural network (ANN) with RGB inputs (Odabas, Simsek, Lee, & İseri, 2017), and hybrid computer vision and paper chromatography (Concepcion et al, 2020). Chlorophyll normalized vegetation index (CNDVI) through the Miniature Leaf Spectrometer CI-710 is a good metric to measure the total chlorophyll concentration (Alsiņa, Dūma, Dubova, Šenberga, & Daģis, 2016).…”

Comparison of the Potential Abilities of Three Spectroscopy Methods: Near-Infrared, Mid-Infrared, and Molecular Fluorescence, to Predict Carotenoid, Vitamin and Fatty Acid Contents in Cow Milk

“…To our knowledge, the other carotenoids considered in our study have never been predicted in milk samples using MIR-ATR and fluorescence spectroscopy. However, different studies showed that it is possible to predict concentrations of β-cryptoxanthin, lutein, zeaxanthin [36,37], the sum of carotenes [38] and the sum of carotenoids [37,39,40] in vegetables using NIR spectroscopy. The equations used to predict the concentrations of these different carotenoids in vegetable samples are more precise than those applied in the current study.…”