Articles
Use of a hand-held NIR spectrometer for rapid and non-destructive determination of apricot internal fruit quality in orchards
Article number
1450_20
Pages
151 – 158
Language
English
Abstract
Near infrared spectroscopy (NIR), combined with chemometrics, is known as a fast and non-destructive method for assessing the composition of materials, in particular of fruit.
The aim of this work was to evaluate the use of a portable spectrometer in order to test its use to help growers to fine-tune fruit harvesting date.
Trials were carried out over 4 years (2019-2022), on 10-16 cultivars of apricot each year.
The spectra were acquired between 310 and 1100 nm, with four identical NIR instruments (F-750, Felix Instruments, USA), measured on 20-30 fruits per cultivar with 2 spectra per fruit, in orchards.
The quality traits of interest were soluble solids content (SSC) and titratable acidity (TA), which illustrated a great variability, ranging from 6.2 to 22.6 °Brix for SSC and from 4.5 to 46.8 meq. 100‑1 g for TA. The relationships between spectra wavelengths and quality attributes measured on 1280 fruit were assessed by applying partial least squares linear regression on data divided randomly into a set for calibration (854 fruit) and a set for validation (426 fruit), using ChemFlow software (https://www.chemproject.org/chemhouse_fre/ChemFlow). Multi-year and multi-instrument models have been calibrated.
Prediction results were given for the internal validation test with R2 of 0.89 and RMSEP of 0.90 °Brix for SSC (729-975 nm, 7 latent variables, second derivative and SNV pretreatments), and R2 of 0.75 and RMSEP of 4.43 meq. 100‑1 g for TA (711-1038 nm, 12 latent variables, second derivative pretreatment). Although spectra were acquired with four different identical instruments, the prediction results were very similar to those obtained with a benchtop spectrometer.
However, an organization still needs to be found to deploy this new fruit quality measurement protocol, including spectrometer metrology, model transfer between individual instruments, model updates over years and recalibration for new cultivars.
The ultimate goal is to improve fruit quality and meet consumer expectations.
The aim of this work was to evaluate the use of a portable spectrometer in order to test its use to help growers to fine-tune fruit harvesting date.
Trials were carried out over 4 years (2019-2022), on 10-16 cultivars of apricot each year.
The spectra were acquired between 310 and 1100 nm, with four identical NIR instruments (F-750, Felix Instruments, USA), measured on 20-30 fruits per cultivar with 2 spectra per fruit, in orchards.
The quality traits of interest were soluble solids content (SSC) and titratable acidity (TA), which illustrated a great variability, ranging from 6.2 to 22.6 °Brix for SSC and from 4.5 to 46.8 meq. 100‑1 g for TA. The relationships between spectra wavelengths and quality attributes measured on 1280 fruit were assessed by applying partial least squares linear regression on data divided randomly into a set for calibration (854 fruit) and a set for validation (426 fruit), using ChemFlow software (https://www.chemproject.org/chemhouse_fre/ChemFlow). Multi-year and multi-instrument models have been calibrated.
Prediction results were given for the internal validation test with R2 of 0.89 and RMSEP of 0.90 °Brix for SSC (729-975 nm, 7 latent variables, second derivative and SNV pretreatments), and R2 of 0.75 and RMSEP of 4.43 meq. 100‑1 g for TA (711-1038 nm, 12 latent variables, second derivative pretreatment). Although spectra were acquired with four different identical instruments, the prediction results were very similar to those obtained with a benchtop spectrometer.
However, an organization still needs to be found to deploy this new fruit quality measurement protocol, including spectrometer metrology, model transfer between individual instruments, model updates over years and recalibration for new cultivars.
The ultimate goal is to improve fruit quality and meet consumer expectations.
Publication
Authors
A. Ronjon, S. Lurol, M. Jost, B. Gouble, V. Gallia, S. Bureau
Keywords
near infrared spectroscopy, Prunus armeniaca, soluble solids content, acidity, PLS prediction models
Online Articles (59)