Artificial intelligence in food quality assessments
The agricultural and food industries have witnessed significant transformation in recent decades due to the rapid growth of science and technology. Technological innovations have improved and increased the efficiency of food production to meet the continuously growing demand due to the increasing...
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2023
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my.upm.eprints.1114822024-07-03T08:03:56Z http://psasir.upm.edu.my/id/eprint/111482/ Artificial intelligence in food quality assessments Hashim, Norhashila The agricultural and food industries have witnessed significant transformation in recent decades due to the rapid growth of science and technology. Technological innovations have improved and increased the efficiency of food production to meet the continuously growing demand due to the increasing population. Food loss and spoilage, low-quality food items supply, manufacturing contamination, unauthorized addition of preservatives and additives, food fraud and adulteration are just a few of the threats faced by food security (Hu et al., 2019; Tan & Xu, 2020). Poor monitoring techniques of food quality contribute to the threat received by food safety which leads to high spoilage and wastage. Food deterioration is detrimental to people’s health and the nation’s economy (Arshad et al., 2023). To abate the health complications and hazards due to food quality deterioration, the rapid assessment of food quality is brought into the limelight and developed into a major area of interest for researchers and industrial food producers. This sets Artificial intelligence (AI) on the right track in promoting rapid food quality assessment by integrating it with high-capacity sensors, vast databases, and computing techniques such as soft computing, internet computing and the Internet of Things (IoT). AI is essential to expedite the advancement of reliable and improved food quality assessment with hastened response capability and delivers results with high precision and repeatability during the process (Addanki et al., 2022). AI does not only improve time efficiency but also serves as the benchmark for state-of-art non-invasive food quality assessment techniques. 2023-09 Conference or Workshop Item PeerReviewed text en http://psasir.upm.edu.my/id/eprint/111482/1/Short%20communication%20note%202023.pdf Hashim, Norhashila (2023) Artificial intelligence in food quality assessments. In: Tsubuka Conference 2023, 25-29 September 2023, Jepun. (pp. 1-3). |
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The agricultural and food industries have witnessed significant transformation in recent
decades due to the rapid growth of science and technology. Technological innovations have
improved and increased the efficiency of food production to meet the continuously growing
demand due to the increasing population. Food loss and spoilage, low-quality food items
supply, manufacturing contamination, unauthorized addition of preservatives and additives,
food fraud and adulteration are just a few of the threats faced by food security (Hu et al., 2019;
Tan & Xu, 2020). Poor monitoring techniques of food quality contribute to the threat received
by food safety which leads to high spoilage and wastage. Food deterioration is detrimental to
people’s health and the nation’s economy (Arshad et al., 2023). To abate the health
complications and hazards due to food quality deterioration, the rapid assessment of food
quality is brought into the limelight and developed into a major area of interest for researchers
and industrial food producers. This sets Artificial intelligence (AI) on the right track in
promoting rapid food quality assessment by integrating it with high-capacity sensors, vast
databases, and computing techniques such as soft computing, internet computing and the
Internet of Things (IoT). AI is essential to expedite the advancement of reliable and improved
food quality assessment with hastened response capability and delivers results with high
precision and repeatability during the process (Addanki et al., 2022). AI does not only improve
time efficiency but also serves as the benchmark for state-of-art non-invasive food quality
assessment techniques. |
| format |
Conference or Workshop Item |
| author |
Hashim, Norhashila |
| spellingShingle |
Hashim, Norhashila Artificial intelligence in food quality assessments |
| author_facet |
Hashim, Norhashila |
| author_sort |
Hashim, Norhashila |
| title |
Artificial intelligence in food quality assessments |
| title_short |
Artificial intelligence in food quality assessments |
| title_full |
Artificial intelligence in food quality assessments |
| title_fullStr |
Artificial intelligence in food quality assessments |
| title_full_unstemmed |
Artificial intelligence in food quality assessments |
| title_sort |
artificial intelligence in food quality assessments |
| publishDate |
2023 |
| url |
http://psasir.upm.edu.my/id/eprint/111482/1/Short%20communication%20note%202023.pdf http://psasir.upm.edu.my/id/eprint/111482/ |
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1804067042010071040 |
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13.211869 |