Abstract Machine learning (ML) has proven to be a useful technology for data analysis and
modeling in a wide variety of domains, including food science and engineering. The use of …

With shrinking natural resources and the climate challenges, it is foreseen that there will be
an imminent stress in agricultural outputs. Deep learning provides immense possibilities in …

Highlights•The concentration of pesticide residue in tea was evaluated non-destructively.•
Electronic nose and confocal Raman microspectroscopy were used for the …

Fungal contamination of maize during pre and post-harvest is rampant and omnipresent.
Hyperspectral imaging (HSI) is a popular non-invasive technique for detection of fungal …

Adulteration of desiccated coconut powder (DCP) with coconut milk residue (CMR) is an
emerging problem in the coconut processing industry. Consumers and industries are …

Abstract Aflatoxin B 1 (AFB 1) is an important cause of human liver cancer. This study
proposes a quantitative detection method for the AFB 1 in corn based on Fourier transform …

Maize mildew is a common phenomenon and it is essential to detect the mildew of a single
maize kernel and prevent mildew from spreading around. In this study, a line-scanning …

Traditional methods for detecting foodstuff hazards are time-consuming, inefficient, and
destructive. Spectral imaging techniques have been proven to overcome these …

Hyperspectral data in 900–1700 nm range was mined for rapid and non-destructive
determination of chicken chemical compositions. Hyperspectral images of chicken flesh …

Traditional Chinese herbal medicine (TCHM) plays an essential role in the international
pharmaceutical industry due to its rich resources and unique curative properties. The …