Machine learning applications to non-destructive defect detection in horticultural products

JFI Nturambirwe, UL Opara - Biosystems engineering, 2020 - Elsevier
Highlights•Defects affecting horticultural products and detection challenges are
summarised.•Machine learning's role in addressing issues of fruit defect detection is …

Potential of near-infrared (NIR) spectroscopy and hyperspectral imaging for quality and safety assessment of fruits: An overview

I Chandrasekaran, SS Panigrahi, L Ravikanth… - Food Analytical …, 2019 - Springer
Daily consumption of fruits has rendered sophisticated techniques for accurate evaluation of
its quality and how it can be initiated in a more rapid way has become a state-of-art for the …

Near infrared (NIR) spectroscopy-based classification for the authentication of Darjeeling black tea

P Firmani, S De Luca, R Bucci, F Marini, A Biancolillo - Food Control, 2019 - Elsevier
Darjeeling black tea is a worldwide known tea variety which is currently part of the register of
protected designations of origin (PDO) and protected geographical indications (PGI) as …

YOLO-based deep learning framework for olive fruit fly detection and counting

N Mamdouh, A Khattab - IEEE Access, 2021 - ieeexplore.ieee.org
The olive fruit fly can damage up to 100% of the harvested fruit and can cause up to 80%
reduction of the value of the resulting olive oil. Therefore, it is important to early detect its …

Discrimination and growth tracking of fungi contamination in peaches using electronic nose

Q Liu, N Zhao, D Zhou, Y Sun, K Sun, L Pan, K Tu - Food Chemistry, 2018 - Elsevier
A non-destructive method for detection of fungal contamination in peaches using an
electronic nose (E-nose) is presented. Peaches were inoculated with three common …

Non-destructive technologies for detecting insect infestation in fruits and vegetables under postharvest conditions: A critical review

AA Adedeji, N Ekramirad, A Rady, A Hamidisepehr… - Foods, 2020 - mdpi.com
In the last two decades, food scientists have attempted to develop new technologies that can
improve the detection of insect infestation in fruits and vegetables under postharvest …

Determination of insect infestation on stored rice by near infrared (NIR) spectroscopy

A Biancolillo, P Firmani, R Bucci, A Magrì, F Marini - Microchemical Journal, 2019 - Elsevier
Among grains, rice is one of the most widely consumed cereals in the world; it represents a
staple food in great part of Asia and Africa, and it is also broadly diffused in America and …

Combining Multi-Dimensional Convolutional Neural Network (CNN) With Visualization Method for Detection of Aphis gossypii Glover Infection in Cotton Leaves Using …

T Yan, W Xu, J Lin, L Duan, P Gao, C Zhang… - Frontiers in Plant …, 2021 - frontiersin.org
Cotton is a significant economic crop. It is vulnerable to aphids (Aphis gossypii Glovers)
during the growth period. Rapid and early detection has become an important means to deal …

Seeing red: A review of the use of near-infrared spectroscopy (NIRS) in entomology

JB Johnson, M Naiker - Applied spectroscopy reviews, 2020 - Taylor & Francis
Near-infrared spectroscopy (NIRS) is a rapid, noninvasive and cheap method of profiling the
chemical composition of a broad range of sample types. Over the past two decades, it has …

NIR Spectroscopy as a Suitable Tool for the Investigation of the Horticultural Field

TMP Cattaneo, A Stellari - Agronomy, 2019 - mdpi.com
The last 10 years of knowledge on near infrared (NIR) applications in the horticultural field
are summarized. NIR spectroscopy is considered one of the most suitable technologies of …