Worldwide aflatoxin contamination of agricultural products and foods: From occurrence to control

A Jallow, H Xie, X Tang, Z Qi, P Li - Comprehensive reviews in …, 2021 - Wiley Online Library
Aflatoxins represent a global public health and economic concern as they are responsible
for significant adverse health and economic issues affecting consumers and farmers …

Machine learning for smart agriculture and precision farming: towards making the fields talk

TA Shaikh, WA Mir, T Rasool, S Sofi - Archives of Computational Methods …, 2022 - Springer
In almost every sector, data-driven business, the digitization of the data has generated a
data tsunami. In addition, man-to-machine digital data handling has magnified the …

Machine learning for high-throughput stress phenotyping in plants

A Singh, B Ganapathysubramanian, AK Singh… - Trends in plant …, 2016 - cell.com
Advances in automated and high-throughput imaging technologies have resulted in a
deluge of high-resolution images and sensor data of plants. However, extracting patterns …

A comprehensive review of high throughput phenotyping and machine learning for plant stress phenotyping

T Gill, SK Gill, DK Saini, Y Chopra, JP de Koff… - Phenomics, 2022 - Springer
During the last decade, there has been rapid adoption of ground and aerial platforms with
multiple sensors for phenotyping various biotic and abiotic stresses throughout the …

Artificial intelligence in food safety: A decade review and bibliometric analysis

Z Liu, S Wang, Y Zhang, Y Feng, J Liu, H Zhu - Foods, 2023 - mdpi.com
Artificial Intelligence (AI) technologies have been powerful solutions used to improve food
yield, quality, and nutrition, increase safety and traceability while decreasing resource …

[HTML][HTML] Artificial cognition for applications in smart agriculture: A comprehensive review

M Pathan, N Patel, H Yagnik, M Shah - Artificial Intelligence in Agriculture, 2020 - Elsevier
Abstract Agriculture contributes to 6.4% of the entire world's economic production. In at least
nine countries of the world, agriculture is the dominant sector of the economy. Agriculture not …

[HTML][HTML] Integrating artificial intelligence and high-throughput phenotyping for crop improvement

M Sheikh, F Iqra, H Ambreen, KA Pravin, M Ikra… - Journal of Integrative …, 2024 - Elsevier
Crop improvement is crucial for addressing the global challenges of food security and
sustainable agriculture. Recent advancements in high-throughput phenotyping (HTP) …

Mycotoxin contamination in food: An exposition on spices

MP Thanushree, D Sailendri, KS Yoha… - Trends in Food Science …, 2019 - Elsevier
Background Among several food and agricultural commodities, spices are valued for their
characteristic flavor. They may also impart color and improve the overall keeping quality of …

Machine learning in agriculture: a review of crop management applications

I Attri, LK Awasthi, TP Sharma - Multimedia Tools and Applications, 2024 - Springer
Abstract Machine learning has created new opportunities for data-intensive study in
interdisciplinary domains as a result of the advancement of big data technologies and high …

Analytical techniques combined with chemometrics for authentication and determination of contaminants in condiments: A review

I Reinholds, V Bartkevics, ICJ Silvis… - Journal of Food …, 2015 - Elsevier
Spices and herbs play an important role as flavorings, colorants, and also as bioactive
compounds used in medicine and cosmetics. The presence of common contaminants, eg …