Non-Destructive Detection of Pesticide-Treated Baby Leaf Lettuce During Production and Post-Harvest Storage Using Visible and Near-Infrared Spectroscopy
The market demand for baby leaf lettuce is constantly increasing, while safety has become one of the most important traits in determining consumer preference driven by human health hazards concerns. In this study, the performance of visible and near-infrared (vis/NIR) spectroscopy was tested in disc...
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MDPI AG
2024-11-01
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| author | Dimitrios S. Kasampalis Pavlos I. Tsouvaltzis Anastasios S. Siomos |
| author_facet | Dimitrios S. Kasampalis Pavlos I. Tsouvaltzis Anastasios S. Siomos |
| author_sort | Dimitrios S. Kasampalis |
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| description | The market demand for baby leaf lettuce is constantly increasing, while safety has become one of the most important traits in determining consumer preference driven by human health hazards concerns. In this study, the performance of visible and near-infrared (vis/NIR) spectroscopy was tested in discriminating pesticide-free against pesticide-treated lettuce plants. Two commercial fungicides (mancozeb and fosetyl-al) and two insecticides (deltamethrin and imidacloprid) were applied as spray solutions at the recommended rates on baby leaf lettuce plants. Untreated-control plants were sprayed with water. Reflectance data in the wavelength range 400–2500 nm were captured on leaf samples until harvest on the 10th day upon pesticide application, as well as after 4 and 8 days during post-harvest storage at 5 °C. In addition, biochemical components in leaf tissue were also determined during storage, such as antioxidant enzymes’ activities (peroxidase [POD], catalase [CAT], and ascorbate peroxidase [APX]), along with malondialdehyde [MDA] and hydrogen peroxide [H<sub>2</sub>O<sub>2</sub>] content. Partial least square discriminant analysis (PLSDA) combined with feature-selection techniques was implemented, in order to classify baby lettuce tissue into pesticide-free or pesticide-treated ones. The genetic algorithm (GA) and the variable importance in projection (VIP) scores identified eleven distinct regions and nine specific wavelengths that exhibited the most significant effect in the detection models, with most of them in the near-infrared region of the electromagnetic spectrum. According to the results, the classification accuracy of discriminating pesticide-treated against non-treated lettuce leaves ranged from 94% to 99% in both pre-harvest and post-harvest periods. Although there were no significant differences in enzyme activities or H<sub>2</sub>O<sub>2</sub>, the MDA content in pesticide-treated tissue was greater than in untreated ones, implying that the chemical spray application probably induced a stress response in the plant that was disclosed with the reflected energy. In conclusion, vis/NIR spectroscopy appears as a promising, reliable, rapid, and non-destructive tool in distinguishing pesticide-free from pesticide-treated lettuce products. |
| format | Article |
| id | doaj-art-a428f17f2b744bcdaa7c6830237cf0e6 |
| institution | Kabale University |
| issn | 1424-8220 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | MDPI AG |
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| series | Sensors |
| spelling | doaj-art-a428f17f2b744bcdaa7c6830237cf0e62024-12-13T16:31:53ZengMDPI AGSensors1424-82202024-11-012423754710.3390/s24237547Non-Destructive Detection of Pesticide-Treated Baby Leaf Lettuce During Production and Post-Harvest Storage Using Visible and Near-Infrared SpectroscopyDimitrios S. Kasampalis0Pavlos I. Tsouvaltzis1Anastasios S. Siomos2Department of Horticulture, Aristotle University, 54124 Thessaloniki, GreeceHorticultural Sciences Department, Southwest Florida Research and Education Center, University of Florida, Immokalee, FL 34142, USADepartment of Horticulture, Aristotle University, 54124 Thessaloniki, GreeceThe market demand for baby leaf lettuce is constantly increasing, while safety has become one of the most important traits in determining consumer preference driven by human health hazards concerns. In this study, the performance of visible and near-infrared (vis/NIR) spectroscopy was tested in discriminating pesticide-free against pesticide-treated lettuce plants. Two commercial fungicides (mancozeb and fosetyl-al) and two insecticides (deltamethrin and imidacloprid) were applied as spray solutions at the recommended rates on baby leaf lettuce plants. Untreated-control plants were sprayed with water. Reflectance data in the wavelength range 400–2500 nm were captured on leaf samples until harvest on the 10th day upon pesticide application, as well as after 4 and 8 days during post-harvest storage at 5 °C. In addition, biochemical components in leaf tissue were also determined during storage, such as antioxidant enzymes’ activities (peroxidase [POD], catalase [CAT], and ascorbate peroxidase [APX]), along with malondialdehyde [MDA] and hydrogen peroxide [H<sub>2</sub>O<sub>2</sub>] content. Partial least square discriminant analysis (PLSDA) combined with feature-selection techniques was implemented, in order to classify baby lettuce tissue into pesticide-free or pesticide-treated ones. The genetic algorithm (GA) and the variable importance in projection (VIP) scores identified eleven distinct regions and nine specific wavelengths that exhibited the most significant effect in the detection models, with most of them in the near-infrared region of the electromagnetic spectrum. According to the results, the classification accuracy of discriminating pesticide-treated against non-treated lettuce leaves ranged from 94% to 99% in both pre-harvest and post-harvest periods. Although there were no significant differences in enzyme activities or H<sub>2</sub>O<sub>2</sub>, the MDA content in pesticide-treated tissue was greater than in untreated ones, implying that the chemical spray application probably induced a stress response in the plant that was disclosed with the reflected energy. In conclusion, vis/NIR spectroscopy appears as a promising, reliable, rapid, and non-destructive tool in distinguishing pesticide-free from pesticide-treated lettuce products.https://www.mdpi.com/1424-8220/24/23/7547chemometricsantioxidant enzymesdiscriminationfeature extractionpartial least squares |
| spellingShingle | Dimitrios S. Kasampalis Pavlos I. Tsouvaltzis Anastasios S. Siomos Non-Destructive Detection of Pesticide-Treated Baby Leaf Lettuce During Production and Post-Harvest Storage Using Visible and Near-Infrared Spectroscopy Sensors chemometrics antioxidant enzymes discrimination feature extraction partial least squares |
| title | Non-Destructive Detection of Pesticide-Treated Baby Leaf Lettuce During Production and Post-Harvest Storage Using Visible and Near-Infrared Spectroscopy |
| title_full | Non-Destructive Detection of Pesticide-Treated Baby Leaf Lettuce During Production and Post-Harvest Storage Using Visible and Near-Infrared Spectroscopy |
| title_fullStr | Non-Destructive Detection of Pesticide-Treated Baby Leaf Lettuce During Production and Post-Harvest Storage Using Visible and Near-Infrared Spectroscopy |
| title_full_unstemmed | Non-Destructive Detection of Pesticide-Treated Baby Leaf Lettuce During Production and Post-Harvest Storage Using Visible and Near-Infrared Spectroscopy |
| title_short | Non-Destructive Detection of Pesticide-Treated Baby Leaf Lettuce During Production and Post-Harvest Storage Using Visible and Near-Infrared Spectroscopy |
| title_sort | non destructive detection of pesticide treated baby leaf lettuce during production and post harvest storage using visible and near infrared spectroscopy |
| topic | chemometrics antioxidant enzymes discrimination feature extraction partial least squares |
| url | https://www.mdpi.com/1424-8220/24/23/7547 |
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