Sensors and Portable Instruments for Postharvest Agriculture

Lerud, Ryan

doi:10.15760/etd.6870

Cited by 1 publication

(2 citation statements)

References 30 publications

(34 reference statements)

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“…43 For a single instrument calibration, DQM outperformed PLS regression on calibration statistics (SEC) for mango DM estimation. 44…”

Section: Model Typesmentioning

confidence: 99%

“…43 For a single instrument calibration, DQM outperformed PLS regression on calibration statistics (SEC) for mango DM estimation. 44 The CovSel method 45 is a wavelength selection method relevant to MLR. It is based on selection of the most important variable as estimated by highest covariance to y, followed by an orthogonal projection of the remaining variable matrix (X) to eliminate collinear variables.…”

Section: Multiple Linear Regressionmentioning

confidence: 99%

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Review: The evolution of chemometrics coupled with near infrared spectroscopy for fruit quality evaluation

Anderson

Walsh

2022

Journal of Near Infrared Spectroscopy

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Short wave near infrared (NIR) spectroscopy operated in a partial or full transmission geometry and a point spectroscopy mode has been increasingly adopted for evaluation of quality of intact fruit, both on-tree and on-packing lines. The evolution in hardware has been paralleled by an evolution in the modelling techniques employed. This review documents the range of spectral pre-treatments and modelling techniques employed for this application. Over the last three decades, there has been a shift from use of multiple linear regression to partial least squares regression. Attention to model robustness across seasons and instruments has driven a shift to machine learning methods such as artificial neural networks and deep learning in recent years, with this shift enabled by the availability of large and diverse training and test sets.

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“…43 For a single instrument calibration, DQM outperformed PLS regression on calibration statistics (SEC) for mango DM estimation. 44…”

Section: Model Typesmentioning

confidence: 99%