Food quality 4.0: From traditional approaches to digitalized automated analysis

A Hassoun, S Jagtap, G Garcia-Garcia… - Journal of Food …, 2023 - Elsevier
Food quality has recently received considerable attention from governments, researchers,
and consumers due to the increasing demand for healthier and more nutritious food …

Food processing 4.0: Current and future developments spurred by the fourth industrial revolution

A Hassoun, S Jagtap, H Trollman, G Garcia-Garcia… - Food Control, 2023 - Elsevier
Abstract “Food processing 4.0” concept denotes processing food in the current digital era by
harnessing fourth industrial revolution (called Industry 4.0) technologies to improve quality …

[HTML][HTML] Guava disease detection using deep convolutional neural networks: A case study of guava plants

AM Mostafa, SA Kumar, T Meraj, HT Rauf, AA Alnuaim… - Applied Sciences, 2021 - mdpi.com
Food production is a growing challenge with the increasing global population. To increase
the yield of food production, we need to adopt new biotechnology-based fertilization …

Systematic literature review: application of deep learning processing technique for fig fruit detection and counting

ASF Kamaruzaman, AIC Ani, MAHM Farid… - Bulletin of Electrical …, 2023 - beei.org
Deep learning has shown much promise in target identification in recent years, and it's
becoming more popular in agriculture, where fig fruit detection and counting have become …

Dynamic mode decomposition and deep learning for postharvest decay prediction in apples

N Stasenko, D Shadrin, A Katrutsa… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
The damages and diseases that may occur in apples during the storage and cannot be seen
visually at early stages is a significant problem in precision agriculture leading to the loss of …

An improved U-Net network-based quantitative analysis of melon fruit phenotypic characteristics

C Qian, H Liu, T Du, S Sun, W Liu, R Zhang - Journal of Food …, 2022 - Springer
Melon fruit phenotype has rich genetic variation and is an important target trait for breeding
and commerciality. Existing measurement techniques have problems such as low detection …

Deep learning for postharvest decay prediction in apples

N Stasenko, M Savinov, V Burlutskiy… - IECON 2021–47th …, 2021 - ieeexplore.ieee.org
Artificial Intelligence (AI) is a widely used tool in precision agriculture for estimating the
quality of food. It is especially relevant while assessing crops at various harvest and …

Quality Grading and Prediction of Frozen Zhoushan Hairtails in China Based on ETSFormer

K Hu, T Hu, W Yan, W Dong, M Zuo, Q Zhang - Sustainability, 2023 - mdpi.com
With the increasing demand for high-quality, healthy, and nutritious food, hairtails have good
potential for development in both domestic and international markets. In particular …

Grading of harvested'Mihwang'peach maturity with convolutional neural network

MH Shin, KE Jang, SK Lee, JG Cho… - Journal of Bio …, 2022 - koreascience.kr
This study was conducted using deep learning technology to classify for'Mihwang'peach
maturity with RGB images and fruit quality attributes during fruit development and maturation …

Segmentasi Berbasis Warna Untuk Pengelompokan Kualitas Cacing Anc Menggunakan Yolov8

F Nurdiyansyah, I Akbar… - JIKO (Jurnal Informatika …, 2025 - ejournal.akakom.ac.id
Mengembangkan metode otomatisasi dalam pengelompokan kualitas cacing African Night
Crawler (ANC) menggunakan model YOLOv8 yang didukung oleh segmentasi berbasis …