Towards Early Poultry Health Prediction through Non-Invasive and Computer Vision-Based Dropping Classification DOI Creative Commons

Arnas Nakrošis,

Agnė Paulauskaitė-Tarasevičienė, Vidas Raudonis

et al.

Animals, Journal Year: 2023, Volume and Issue: 13(19), P. 3041 - 3041

Published: Sept. 27, 2023

The use of artificial intelligence techniques with advanced computer vision offers great potential for non-invasive health assessments in the poultry industry. Evaluating condition by monitoring their droppings can be highly valuable as significant changes consistency and color indicators serious infectious diseases. While most studies have prioritized classification into two categories (normal abnormal), some relevant dealing up to five categories, this investigation goes a step further employing image processing algorithms categorize six classes, based on visual information indicating level abnormality. To ensure diverse dataset, data were collected three different farms Lithuania capturing types litter. With implementation deep learning, object detection rate reached 92.41% accuracy. A range machine learning algorithms, including architectures, has been explored and, obtained results, we proposed comprehensive solution combining models segmentation purposes. results revealed that task achieved highest accuracy 0.88 terms Dice coefficient K-means algorithm. Meanwhile, YOLOv5 demonstrated accuracy, achieving an ACC 91.78%.

Language: Английский

Recent advances in artificial intelligence towards the sustainable future of agri-food industry DOI
Pinku Chandra Nath, Awdhesh Kumar Mishra,

Ramesh Sharma

et al.

Food Chemistry, Journal Year: 2024, Volume and Issue: 447, P. 138945 - 138945

Published: March 5, 2024

Language: Английский

Citations

53
Towards sustainable agriculture: Harnessing AI for global food security DOI Creative Commons
Dhananjay K. Pandey, Richa Mishra

Artificial Intelligence in Agriculture, Journal Year: 2024, Volume and Issue: 12, P. 72 - 84

Published: April 30, 2024

The issue of food security continues to be a prominent global concern, affecting significant number individuals who experience the adverse effects hunger and malnutrition. finding solution this intricate necessitates implementation novel paradigm-shifting methodologies in agriculture sector. In recent times, domain artificial intelligence (AI) has emerged as potent tool capable instigating profound influence on sectors. AI technologies provide advantages by optimizing crop cultivation practices, enabling use predictive modelling precision techniques, aiding efficient monitoring disease identification. Additionally, potential optimize supply chain operations, storage management, transportation systems, quality assurance processes. It also tackles problem loss waste through post-harvest reduction, analytics, smart inventory management. This study highlights that how utilizing power AI, we could transform way produce, distribute, manage food, ultimately creating more secure sustainable future for all.

Language: Английский

Citations

49
Digital transformation in the agri-food industry: recent applications and the role of the COVID-19 pandemic DOI Creative Commons
Abdo Hassoun, H.J.P. Marvin, Yamine Bouzembrak

et al.

Frontiers in Sustainable Food Systems, Journal Year: 2023, Volume and Issue: 7

Published: July 18, 2023

Providing food has become more complex because of climate change and other environmental societal stressors, such as political instability, the growth in world population, outbreaks new diseases, especially COVID-19 pandemic. In response to these challenges, agri-food industry increased its efforts shift using digital tools advanced technologies. The transition toward been part fourth industrial revolution (called Industry 4.0) innovations that have are reshaping most industries. This literature review discusses potential implementing technologies industry, focusing heavily on role pandemic fostering adoption greater digitalization supply chains. Examples use for various applications, barriers challenges will be highlighted. trend solutions gained momentum since advent 4.0 implementations accelerated by outbreak Important technology enablers high mitigating negative effects both current global health crisis systems include artificial intelligence, big data, Internet Things, blockchain, smart sensors, robotics, twins, virtual augmented reality. However, much remains done fully harness power achieve widespread implementation agriculture

Language: Английский

Citations

45
Leveraging artificial intelligence and advanced food processing techniques for enhanced food safety, quality, and security: a comprehensive review DOI Creative Commons
Sambandh Bhusan Dhal,

Debashish Kar

Deleted Journal, Journal Year: 2025, Volume and Issue: 7(1)

Published: Jan. 11, 2025

Abstract Artificial intelligence is emerging as a transformative force in addressing the multifaceted challenges of food safety, quality, and security. This review synthesizes advancements AI-driven technologies, such machine learning, deep natural language processing, computer vision, their applications across supply chain, based on comprehensive analysis literature published from 1990 to 2024. AI enhances safety through real-time contamination detection, predictive risk modeling, compliance monitoring, reducing public health risks. It improves quality by automating defect optimizing shelf-life predictions, ensuring consistency taste, texture, appearance. Furthermore, addresses security enabling resource-efficient agriculture, yield forecasting, chain optimization ensure availability accessibility nutritious resources. also highlights integration with advanced processing techniques high-pressure ultraviolet treatment, pulsed electric fields, cold plasma, irradiation, which microbial extend shelf life, enhance product quality. Additionally, technologies Internet Things, blockchain, AI-powered sensors enables proactive management, analytics, automated control. By examining these innovations' potential transparency, efficiency, decision-making within systems, this identifies current research gaps proposes strategies address barriers data limitations, model generalizability, ethical concerns. These insights underscore critical role advancing safer, higher-quality, more secure guiding future fostering sustainable systems that benefit consumer trust.

Language: Английский

Citations

14
Emerging Trends in Food Process Engineering: Integrating Sensing Technologies for Health, Sustainability, and Consumer Preferences DOI Creative Commons
Mir Waqas Alam, Jothi Vinoth Kumar, Mohammed Awad

et al.

Journal of Food Process Engineering, Journal Year: 2025, Volume and Issue: 48(1)

Published: Jan. 1, 2025

ABSTRACT The food processing industry, a significant global economic driver, encompasses diverse sectors ranging from agriculture to service and is currently undergoing transformative changes fueled by engineering innovations, evolving consumer preferences, regulatory demands. Cutting‐edge advancements in technology, such as precision agriculture, intelligent packaging, advanced methods like high‐pressure 3D printing, are revolutionizing efficiency sustainability. These innovations reducing waste, improving safety, enhancing traceability throughout the supply chain. Simultaneously, demands for healthier, sustainable, ethically produced reshaping product offerings. Emerging trends include functional foods, clean labels, plant‐based diets, personalized nutrition, allergen‐free products, all reflecting focus on health wellness. Sustainability remains critical priority, with emphasis eco‐friendly farming practices, waste reduction, biodegradable or recyclable packaging solutions. Digital technologies IoT, blockchain, artificial intelligence, robotics operational transparency. Intelligent featuring embedded sensors monitoring freshness quality further bolstering confidence chain efficiency. position industry address challenges, ensuring security, sustainability while adapting dynamic market

Language: Английский

Citations

7
Synergizing Artificial Intelligence and Probiotics: A Comprehensive Review of Emerging Applications in Health Promotion and Industrial Innovation DOI
Xin Han,

Q. D. Liu,

Yun Li

et al.

Trends in Food Science & Technology, Journal Year: 2025, Volume and Issue: unknown, P. 104938 - 104938

Published: Feb. 1, 2025

Language: Английский

Citations

6
Harnessing artificial intelligence for advancements in Rice / wheat functional food Research and Development DOI

Fangye Zeng,

Min Zhang, Chung Lim Law

et al.

Food Research International, Journal Year: 2025, Volume and Issue: unknown, P. 116306 - 116306

Published: March 1, 2025

Language: Английский

Citations

6
Forecasting disruptions in global food value chains to tackle food insecurity: The role of AI and big data analytics – A bibliometric and scientometric analysis DOI Creative Commons
Phemelo Tamasiga, El houssin Ouassou, Helen Onyeaka

et al.

Journal of Agriculture and Food Research, Journal Year: 2023, Volume and Issue: 14, P. 100819 - 100819

Published: Oct. 12, 2023

Globalization and interconnected supply chains have led to complex disruptions in global value chains, caused by various factors such as natural disasters, climate events, geopolitical conflicts, economic crises. Recent breakthroughs AI, machine learning, blockchain, big data analytics offer new possibilities for forecasting managing these effectively. This study examines the role of AI within chain tackle food insecurity. We conducted a bibliometric scientometric analysis using comprehensive from Scopus Web Science explore emerging research trends, influential publications, leading institutions, collaborations, themes, policy implications, future avenues. The revealed an average yearly growth rate 13.78 % publications 1973 2022. China, United Kingdom, States lead applications address disruptions, particularly concerning Frequently used keywords include "food security," "supply management," "agriculture," "modelling," "climate change," "COVID-19." Themes identified focus on impact COVID-19 achieving security amidst change, leveraging predictive models agriculture, assessing price volatility risk assessment approaches. insights gained this valuable guidance policymakers researchers enhance security. themes provide direction efforts advancing uncertainties chains.

Language: Английский

Citations

44
Effects of storage conditions and packaging materials on the postharvest quality of fresh Chinese tomatoes and the optimization of the tomatoes' physiochemical properties using machine learning techniques DOI Creative Commons

Hany S. El‐Mesery,

Oluwasola Abayomi Adelusi,

Sefater Ghashi

et al.

LWT, Journal Year: 2024, Volume and Issue: 201, P. 116280 - 116280

Published: May 30, 2024

This study evaluated the impacts of varying storage temperatures and packaging materials on colour, enzymatic activity, phytochemical content, antioxidant properties Chinese tomatoes during storage. More so, machine learning (ML) optimization models were employed to predict optimize effects period, temperatures, tomatoes' physicochemical properties. According two-way ANOVA analysis, temperature impacted all parameters except L anthocyanin. Furthermore, demonstrated a substantial effect factors. The combined also measurements for ΔE. It was possible obtain optimized conditions storing using four constructed two different algorithms. findings from ML models, product at 4 °C with 85 % relative humidity (RH) results in higher-quality end than 25 °C. Additionally, majority that NPHDP packing material will typically produce are higher quality. is vital maintaining quality nutritional value throughout their postharvest.

Language: Английский

Citations

14
Applications of artificial intelligence (AI) in managing food quality and ensuring global food security DOI Creative Commons
Ali Ikram, Hassan Mehmood,

Muhammad Tayyab Arshad

et al.

CyTA - Journal of Food, Journal Year: 2024, Volume and Issue: 22(1)

Published: Sept. 9, 2024

Language: Английский

Citations

14