Author
Listed:
- Giuseppe Bonifazi
(Department of Chemical Engineering, Materials and Environment, Sapienza University of Rome, Via Eudossiana 18, 00184 Rome, Italy)
- Riccardo Gasbarrone
(Research and Service Center for Sustainable Technological Innovation (Ce.R.S.I.Te.S.), Sapienza University of Rome, 04100 Latina, Italy)
- Davide Gattabria
(Department of Chemical Engineering, Materials and Environment, Sapienza University of Rome, Via Eudossiana 18, 00184 Rome, Italy)
- Eugenio Lendaro
(Pathology Unit (I.C.O.T.), Department of Medical-Surgical Sciences and Bio-Technologies, Sapienza University of Rome, 04100 Latina, Italy)
- Luciana Mosca
(Department of Biochemical Sciences, Faculty of Pharmacy and Medicine, Sapienza University of Rome, p.le Aldo Moro 5, 00185 Rome, Italy)
- Roberto Mattioli
(Department of Biochemical Sciences, Faculty of Pharmacy and Medicine, Sapienza University of Rome, p.le Aldo Moro 5, 00185 Rome, Italy)
- Silvia Serranti
(Department of Chemical Engineering, Materials and Environment, Sapienza University of Rome, Via Eudossiana 18, 00184 Rome, Italy)
Abstract
Accurate and rapid assessment of the water content in olive fruits is critical for enhancing the efficiency and sustainability of olive oil production. This study investigates the application of visible and short-wave infrared (Vis-SWIR) spectroscopy as a non-invasive method to directly measure the water content in intact olive fruits before milling, also affecting eco-friendly farming practices. Partial least squares (PLS) regression models for the olive fruit weight, weight loss, and water content were developed while using the dehydration process in a drying oven as the reference analysis. The models demonstrated strong predictive performance, with the PLS model for the olive fruit weight achieving a coefficient of determination in cross-validation (R 2 CV ) of 0.78 and a root mean squared error (RMSECV) of 0.6 g. Additionally, for olive fruit weight loss, a R 2 CV of 0.96 with an RMSECV of 4.5% was achieved. Meanwhile, for the olive fruit water content, an R 2 CV of 0.94 with an RMSECV of 0.245 mL was obtained. The PLS regression model set up to predict the water content for intact olive fruits showed promise, as evidenced by its fit, RMSE in prediction, and residual prediction deviation (RPD) values (R 2 P = 0.80, RMSEP = 0.556 mL, and RPD = 2.247). The obtained results indicate that portable Vis-SWIR spectrophotometers provide a rapid and efficient alternative to conventional drying and weighing methods, facilitating early detection of olive fruit quality. This technological approach not only enhances the financial returns for producers but also supports sustainable agricultural practices. The use of Vis-SWIR spectroscopy has broader potential applications in the olive industry, including quality control, monitoring the water status of olive orchards, and optimizing irrigation management, contributing to the sustainable management of land and agricultural resources.
Suggested Citation
Giuseppe Bonifazi & Riccardo Gasbarrone & Davide Gattabria & Eugenio Lendaro & Luciana Mosca & Roberto Mattioli & Silvia Serranti, 2024.
"Early Study on Visible (Vis) and Short-Wave Infrared (SWIR) Spectroscopy for Assessing Water Content in Olive Fruits: Towards Sustainable Land and Agricultural Practices,"
Land, MDPI, vol. 13(12), pages 1-16, December.
Handle:
RePEc:gam:jlands:v:13:y:2024:i:12:p:2231-:d:1548109
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