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How can you use AI to reduce crop waste?

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Crop waste is a major problem for agribusiness, affecting food security, sustainability, and profitability. It occurs at various stages of the food supply chain, from harvesting to processing to consumption. According to the Food and Agriculture Organization, about one-third of the food produced globally is lost or wasted every year. How can you use AI to reduce crop waste and improve your agribusiness performance? Here are some ways that AI can help you optimize your crop management, processing, and distribution.

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Ankit Laddha

Head .retail @UPL
Mehmood Yousaf

Operations Manager at Valley Irrigation Pakistan (Pvt.Ltd) || Managing the maintenance and repair of Irrigation System…
Umesh Yadav

Agripreneur | Crop Management || Animal Health and Nutrition |

1 Detect diseases and pests

One of the main causes of crop loss is the damage caused by diseases and pests. AI can help you identify and prevent these threats by using image recognition, sensors, and drones. You can use AI to analyze images of your crops and detect signs of infection, infestation, or stress. You can also use AI to monitor the environmental conditions and crop health using sensors and drones. This way, you can apply timely and targeted interventions, such as pesticides, fertilizers, or irrigation, to protect your crops and reduce waste.

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Mehmood Yousaf

Operations Manager at Valley Irrigation Pakistan (Pvt.Ltd) || Managing the maintenance and repair of Irrigation System || Collaborating with other departments to develop & implement strategies
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- Utilize AI-powered sensors and imaging for precise monitoring of crop health and conditions. - Implement predictive analytics to optimize irrigation, pest control, and harvesting schedules, minimizing waste through data-driven decision-making.

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Umesh Yadav

Agripreneur | Crop Management || Animal Health and Nutrition |
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Utilize AI with image recognition, sensors, and drones to detect and prevent crop loss from diseases and pests. Analyze crop images to identify signs of infection, infestation, or stress. Monitor environmental conditions and crop health with AI-driven sensors and drones. Take timely, targeted actions like applying pesticides, fertilizers, or irrigation to safeguard crops and minimize waste.

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Dr. Merve Kaya

Future-Driven AgriTech Transformation Leader
(已编辑)
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The cutting-edge technology, driven by artificial intelligence, has redefined the landscape of aquaculture with its innovative solutions and transformative impact. Feed Optimization: Smart feeding reduces waste, boosts fish growth. Environmental Impact: Tech-driven sustainability minimizes waste, ensures healthier fish.

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2 Optimize harvesting and storage

Another cause of crop waste is the inefficiency of harvesting and storage methods. AI can help you improve your harvesting and storage practices by using data analytics, robotics, and smart packaging. You can use AI to analyze data from your crops, such as yield, quality, and maturity, and determine the optimal time and method for harvesting. You can also use AI to automate your harvesting process using robots, such as self-driving tractors, harvesters, or pickers. Moreover, you can use AI to enhance your storage conditions using smart packaging, such as sensors, indicators, or coatings, that can extend the shelf life and freshness of your crops.

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Márcio Silva Oshiro

Gerente de Marketing na ICL Group | Agronegócio | MBA em Customer Experience
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Minha experiência pessoal com IA na agricultura foi transformadora para reduzir desperdícios de colheitas. Utilizando sensores e algoritmos, a IA monitorou condi??es climáticas, identificou pragas e avaliou a saúde das plantas em tempo real. Essa análise preditiva permitiu interven??es precisas, como irriga??o controlada e tratamentos direcionados, minimizando perdas. Além disso, a IA facilitou a previs?o precisa de épocas ideais de colheita, evitando a colheita prematura ou tardia. O resultado foi uma produ??o mais eficiente, menos desperdício e uma abordagem sustentável na agricultura, com benefícios econ?micos e ambientais significativos.

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3 Reduce post-harvest losses

Post-harvest losses occur when crops are damaged, spoiled, or discarded during transportation, processing, or retailing. AI can help you reduce post-harvest losses by using supply chain management, traceability, and demand forecasting. You can use AI to manage your supply chain more efficiently, by tracking your inventory, logistics, and quality control. You can also use AI to trace your crops from farm to fork, by using blockchain, RFID, or QR codes, that can provide information on the origin, condition, and safety of your crops. Furthermore, you can use AI to forecast your demand more accurately, by using machine learning, big data, or social media, that can predict the consumer preferences, trends, and behaviors.

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Ankit Laddha

Head .retail @UPL
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25% of the food is wasted at this point, which can be fed to population in some other geography.. AI/ML can help in managing the inventory by simply reading the data points and connect the larger dots between demand and supply ..

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4 Prevent food waste

Food waste occurs when crops are thrown away by consumers or retailers due to excess, expiration, or aesthetic reasons. AI can help you prevent food waste by using dynamic pricing, smart labeling, and consumer education. You can use AI to adjust your prices according to the supply and demand of your crops, by using algorithms, sensors, or cameras, that can lower the prices of surplus or near-expiry crops. You can also use AI to improve your labeling practices using smart labels, such as QR codes, NFC tags, or digital watermarks, that can provide more information on the quality, nutrition, and recipes of your crops. Additionally, you can use AI to educate your consumers on how to reduce food waste, by using apps, chatbots, or gamification, that can offer tips, reminders, or incentives to avoid wasting food.

AI is a powerful tool that can help you reduce crop waste and improve your agribusiness performance. By using AI, you can optimize your crop management, processing, and distribution, and prevent food waste. This way, you can enhance your food security, sustainability, and profitability, and contribute to the global goal of reducing food loss and waste by 50% by 2030.

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Oleksandr Alba

Co-Founder @ COMPLANT CONSULTING | MSc Organic Agriculture/Agroecology
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There are several robust cases that worth attention. Winnow's AI-powered tools have saved around 61,000 tons of CO2, equal to preventing 36.5 million meal wastes. Their system, used in commercial kitchens, reduces food waste by up to 50%, saving significant costs. The Winnow Vision system identifies wasted food types using AI and tracks waste with a digital scale and tablet. Hilton Hotels in the Middle East, Africa, and Turkey reduced waste by about 600,000 meals using Winnow's AI, demonstrating substantial waste and cost reductions in the industry.

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5 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?

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Beuuy Sanga

Agritech Entrepreneur | Agri journalist with over 5M+ Impression
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In Africa, we are still struggling to integrate AI technologies into our agriculture supply chain. Many regions in Africa lack basic infrastructure, such as reliable electricity and internet connectivity, which are essential for deploying and maintaining AI technologies. Another thing is low Adaptation to Local Contexts: Many AI solutions need to be adapted to the specific agricultural practices, crops, and climates of different regions in Africa to ensure relevance and effectiveness. Addressing these challenges requires a collaborative effort involving governments, NGOs, private sector stakeholders, and local communities

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How can you use AI to reduce crop waste?

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1 Detect diseases and pests

2 Optimize harvesting and storage

3 Reduce post-harvest losses

4 Prevent food waste

5 Here’s what else to consider

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