Non-Destructive Hyperspectral Imaging and Machine Learning-Based Predictive Models for Physicochemical Quality Attributes of Apples during Storage as Affected by Codling Moth Infestation †
Abstract
:1. Introduction
2. Materials and Methods
2.1. Sample Preparation
2.2. Hyperspectral Image Acquisition
2.3. Physicochemical Parameters Measurements
2.4. Data Processing
3. Results and Discussion
3.1. Quality Change of Apples during Storage
3.2. Reflectance Spectra of Control and Infested Apples during Storage
3.3. Predicting the Quality of Control and Infested Apples during Storage
4. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Samples Condition | Regression Model | Rc | RMSEC | Rp | RMSEP |
---|---|---|---|---|---|
Control | PLSR | 0.94 | 0.17 | 0.97 | 0.25 |
SVR | 0.93 | 0.19 | 0.93 | 0.30 | |
Infested | PLSR | 0.97 | 0.13 | 0.71 | 0.24 |
SVR | 0.65 | 0.24 | 0.44 | 0.24 | |
Combination | PLSR | 0.85 | 0.24 | 0.54 | 0.33 |
SVR | 0.89 | 0.22 | 0.49 | 0.34 |
Quality Parameter | Samples Condition | Regression Model | Rc | RMSEC | Rp | RMSEP |
---|---|---|---|---|---|---|
pH | Control, stored at 0 °C | PLSR | 0.94 | 0.17 | 0.97 | 0.25 |
SVR | 0.93 | 0.19 | 0.93 | 0.30 | ||
Firmness | Control, stored at 0 °C | PLSR | 0.95 | 1.26 | 0.93 | 1.62 |
SVR | 0.96 | 1.21 | 0.95 | 1.45 | ||
SSC | Control, stored at 0 °C | PLSR | 0.95 | 0.53 | 0.90 | 0.81 |
SVR | 0.95 | 0.56 | 0.92 | 0.89 | ||
MC | Control, stored at 0 °C | PLSR | 0.85 | 0.81 | 0.88 | 0.88 |
SVR | 0.84 | 0.82 | 0.91 | 0.82 |
Quality Parameter | Samples Condition | Regression Model | Rc | RMSEC | Rp | RMSEP |
---|---|---|---|---|---|---|
pH | Control, stored at 4 °C | PLSR | 0.92 | 0.29 | 0.89 | 0.51 |
SVR | 0.95 | 0.25 | 0.76 | 0.90 | ||
Firmness | Control, stored at 4 °C | PLSR | 0.95 | 1.37 | 0.74 | 3.19 |
SVR | 0.67 | 2.20 | 0.54 | 2.54 | ||
SSC | Control, stored at 4 °C | PLSR | 0.88 | 0.68 | 0.58 | 0.91 |
SVR | 0.99 | 0.36 | 0.77 | 0.80 | ||
MC | Control, stored at 4 °C | PLSR | 0.98 | 0.39 | 0.66 | 1.08 |
SVR | 0.96 | 0.58 | 0.95 | 0.87 |
Quality Parameter | Samples Condition | Regression Model | Rc | RMSEC | Rp | RMSEP |
---|---|---|---|---|---|---|
pH | Control, stored at 10 °C | PLSR | 0.97 | 0.18 | 0.94 | 0.40 |
SVR | 0.97 | 0.20 | 0.96 | 0.35 | ||
Firmness | Control, stored at 10 °C | PLSR | 0.98 | 0.98 | 0.95 | 0.97 |
SVR | 0.99 | 0.10 | 0.98 | 1.77 | ||
SSC | Control, stored at 10 °C | PLSR | 0.92 | 0.65 | 0.73 | 1.03 |
SVR | 0.71 | 0.92 | 0.56 | 1.19 | ||
MC | Control, stored at 10 °C | PLSR | 0.97 | 0.53 | 0.94 | 1.31 |
SVR | 0.99 | 0.10 | 0.80 | 1.16 |
Quality Parameter | Selected Wavelengths (nm) | Regression Model | Rc | RMSEC | Rp | RMSEP |
---|---|---|---|---|---|---|
pH | 950, 1161, 1221, 1224, 1271, 1274, 1334, 1378, 1381, 1471, 1474, 1477, 1481, 1584 | PLSR | 0.90 | 0.20 | 0.92 | 0.26 |
SVR | 0.98 | 0.12 | 0.92 | 0.29 | ||
SSC | 1081, 1117, 1157, 1161, 1164, 1167, 1238, 1241, 1244, 1248, 1251, 1254, 1258, 1301, 1354, 1358, 1368, 1477, 1481 | PLSR | 0.97 | 0.48 | 0.91 | 0.84 |
SVR | 0.94 | 0.57 | 0.92 | 0.85 | ||
Firmness | 957, 1164, 1184, 1248, 1321, 1324, 1477 | PLSR | 0.80 | 1.77 | 0.95 | 1.66 |
SVR | 0.87 | 1.68 | 0.94 | 1.84 | ||
MC | 953, 957, 1020, 1054, 1071, 1074, 1184, 1188, 1241, 1291, 1344, 1348 | PLSR | 0.83 | 0.83 | 0.89 | 0.80 |
SVR | 0.83 | 0.84 | 0.90 | 0.85 |
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Khaled, A.Y.; Ekramirad, N.; Donohue, K.D.; Villanueva, R.T.; Adedeji, A.A. Non-Destructive Hyperspectral Imaging and Machine Learning-Based Predictive Models for Physicochemical Quality Attributes of Apples during Storage as Affected by Codling Moth Infestation. Agriculture 2023, 13, 1086. https://doi.org/10.3390/agriculture13051086
Khaled AY, Ekramirad N, Donohue KD, Villanueva RT, Adedeji AA. Non-Destructive Hyperspectral Imaging and Machine Learning-Based Predictive Models for Physicochemical Quality Attributes of Apples during Storage as Affected by Codling Moth Infestation. Agriculture. 2023; 13(5):1086. https://doi.org/10.3390/agriculture13051086
Chicago/Turabian StyleKhaled, Alfadhl Y., Nader Ekramirad, Kevin D. Donohue, Raul T. Villanueva, and Akinbode A. Adedeji. 2023. "Non-Destructive Hyperspectral Imaging and Machine Learning-Based Predictive Models for Physicochemical Quality Attributes of Apples during Storage as Affected by Codling Moth Infestation" Agriculture 13, no. 5: 1086. https://doi.org/10.3390/agriculture13051086