Thank you for raising this issue, I believe AI can support and help in preventing environmental issues related to global warming and potential for shortage in many directions starting from adopting AI applications for crop monitoring, which can detect pest infestations, monitor crop, plants, and trees health or event to detect water stress at early stages to allow farmers or the representative stakeholders to take the corrective actions of decisions at the right time. Moreover, there might be a need for applications that is able to analyze weather patterns and soil conditions and historical data to predict or forecast the yield to better plan resources by optimizing the use of water, fertilizer and pesticides to minimize the food waste at farming stage and reduce the associated environmental impacts.

When it comes to the supply chains, AI can support in demand forecasting based on the different factors such as population growth, climate conditions, dynamic prices, market trends and conditions to prevent overproduction or shortages (this paper might be interesting in this domain https://doi.org/10.1016/j.clpl.2023.100034). Furthermore, AI can support in optimizing the logistics and distribution operations and activities. Such as route optimization, supply chain network design (refer to this paper: https://doi.org/10.3390/su142114463). This can lead to prevent waste generation due to the long transportation time. Adding to it, the factors that might increase the waste while transporting food from one stage to another in the supply chain such as the packaging material as highlighted here: https://doi.org/10.3390/su141912644. Innovation in food supply chains is a plus such as transforming from linear supply chains to circular supply chains to adopt applicable and suitable circular economy strategies as included here: doi.org/10.1016/j.rcradv.2023.200199.

AI can also support in adopting alternative farming strategies such as controlling vertical farms to maximize yield and reduce the yield gap. From another point of view, the adaptive farming practices so that farmers can adapt to changing climate conditions by for example recommending crops varieties, planting and irrigation times and optimizing the irrigation water. Additionally, digitalizing food supply chain by implementing decision support tool can help in analyzing huge amounts of data to provide insight for policy and decision making process and simulating the different scenarios including climate change, conflicts to support the decisionmakers to plan for potential food crisis. Also, providing training for the different stakeholders can provide with personalized advice and training to improve their ability to adapt to changing conditions and adopt sustainability practices. and finally, consumer awareness is an important factor here, where AI can help to raise awareness about sustainability issues of the different food products to encourage consumers to shift toward more sustainable options.

Thanks for identifying such a critical matter. From my view, AI has the potential to help mitigate food shortages exacerbated by global crises such as climate change, wars, and economic disruptions. By optimizing agricultural practices, AI can enhance crop productivity, reduce resource waste, and improve food distribution. For instance, AI-powered remote sensing can monitor crop health and predict yields more accurately, helping farmers make timely interventions to prevent crop losses. Additionally, AI can optimize food supply chains by predicting demand and reducing food waste through better management of production and storage processes (Jung et al., 2020).

Moreover, AI can play a significant role in creating sustainable food systems by reducing greenhouse gas emissions and enhancing resilience to climate change. For example, AI is being integrated into smart farming systems to optimize water usage and reduce methane emissions from livestock. These AI-driven innovations can contribute to more efficient and sustainable food production while reducing the environmental footprint of agriculture (Camaréna, 2020). Ultimately, AI's potential lies in its ability to address both short-term food crises and long-term sustainability goals in agriculture.

In addition to improving agricultural productivity, AI can significantly contribute to addressing food security by tackling inefficiencies in global supply chains. By employing machine learning and advanced algorithms, AI can predict market trends, optimize logistics, and enhance decision-making in real-time, reducing food waste and improving distribution. This is particularly important in areas hit hardest by climate change or geopolitical crises, where timely food distribution can save lives. AI can also enhance food safety by ensuring that supply chains are well-regulated, tracking food quality and safety from production to consumption, and ensuring minimal spoilage during transportation and storage (Kollia et al., 2021).

• S. Camaréna, "Artificial intelligence in the design of the transitions to sustainable food systems," Journal of Cleaner Production, vol. 271, 2020.
• J. Jung, M. Maeda, A. Chang, M. Bhandari, A. Ashapure, and J. Landivar-Bowles, "The potential of remote sensing and artificial intelligence as tools to improve the resilience of agriculture production systems," Current Opinion in Biotechnology, vol. 70, pp. 15-22, 2020.
• I. Kollia, J. Stevenson, and S. Kollias, "AI-enabled efficient and safe food supply chain," ArXiv, 2021.