Classification of wheat kernels with near-infrared hyperspectral imaging

Alexia Naudé; Paul J. Williams

doi:10.1117/12.2585562

12 April 2021 Classification of wheat kernels with near-infrared hyperspectral imaging

Alexia Naudé, Paul J. Williams

Proceedings Volume 11754, Sensing for Agriculture and Food Quality and Safety XIII; 117540A (2021) https://doi.org/10.1117/12.2585562
Event: SPIE Defense + Commercial Sensing, 2021, Online Only

Abstract

Wheat (Triticum spp.) is a widely grown cereal crop and is one of the most important staple foods internationally. Grading is an imperative step in wheat production to ensure that the grains are of acceptable quality and safety for food processing and consumption. Current wheat grading practices are performed manually which is tedious, time-consuming, and subjective. This study aimed to investigate the feasibility of NIR hyperspectral imaging (HSI) and chemometrics to discriminate sound wheat from four common defects. Defective wheat included heat-damaged, Fusarium-damaged, sprout-damaged, and immature kernels. A wide variety of pre-processing techniques and classification algorithms (logistic regression, partial least squares-discriminant analysis, linear discriminant analysis, k-nearest neighbours, decision trees, random forests and support vector machines) were evaluated for both two-way and multiclass analyses. For the two-way classifications, accuracies between 98.6% and 100% were achieved for each defective category. The multiclass analyses had a decreased performance, where the best model attained an accuracy of 84.6%. Given that agricultural products vary significantly in inherent characteristics due to genetics, cultivation practices, handling and storage, the overall results achieved are highly successful. This study shows that HSI is capable of effectively discriminating sound wheat from common occurring defects, offering a promising alternative grading technique to the cereal industry.

Conference Presentation

Citation Download Citation

Alexia Naudé and Paul J. Williams "Classification of wheat kernels with near-infrared hyperspectral imaging", Proc. SPIE 11754, Sensing for Agriculture and Food Quality and Safety XIII, 117540A (12 April 2021); https://doi.org/10.1117/12.2585562

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members: $17.00

Non-members: $21.00 ADD TO CART

PROCEEDINGS
PRESENTATION

WATCH
PRESENTATION SAVE TO MY LIBRARY

GET CITATION

KEYWORDS

Hyperspectral imaging

Agriculture

Chemometrics

Genetics

Near infrared

Performance modeling

Safety

Keywords/Phrases

Search In:

Publication Years