Nanodiamond quantum sensors in microdroplets could enable non-invasive monitoring of nutrient and water flow in plants, potentially revealing early stress signals and supporting more precise irrigation and fertilization decisions.
Quantum and quantum-inspired network design could explore complex warehouse placement and capacity scenarios, potentially reducing spoilage, emissions, and costs while improving food access and supply chain resilience.
Quantum gravimetry could enable high-resolution subsurface imaging of soil properties such as water content, compaction, and density, potentially supporting more informed decisions on sustainable land and water use.
Quantum LiDAR could enhance crop imaging by improving sensitivity and resolution in noisy environments, potentially enabling more precise monitoring of plant structure, early stress detection, and better-informed management decisions.
Quantum NMR using NV-centre diamond sensors could enable highly sensitive detection of molecular signatures in agricultural samples, potentially improving monitoring of nutrients in feed, water, and biological materials.
Quantum or quantum-enhanced simulations could model cell behavior and bioprocesses in cultured meat production, potentially accelerating optimization of media, scaffolds, and growth conditions while reducing cost and experimentation.
Quantum computing could enhance analysis of satellite data and mission planning, potentially improving early detection of subtle forest-cover changes and enabling more timely monitoring of illegal deforestation.
Quantum computing could enable more accurate simulation of mineral surfaces and reagents, potentially improving understanding of phosphate extraction processes and supporting the design of more efficient fertiliser component recovery methods.
Quantum-enhanced simulation and machine learning could improve regional climate modelling, potentially enabling more accurate predictions that support crop selection, irrigation planning, and resilience to climate-related agricultural risks.
Quantum algorithms could model complex photosynthetic processes, including energy transfer and environmental effects, potentially improving understanding of efficiency and supporting development of higher-yield crops or advanced light-harvesting technologies.
Quantum magnetometers combined with inertial systems could enable GPS-independent navigation by mapping local magnetic variations, potentially improving reliability of autonomous agricultural machines in signal-denied or obstructed environments.
Quantum nano-NMR using NV-centre sensors could enable highly sensitive detection of contaminants in food, potentially improving identification of trace pathogens, chemicals, and molecular-level safety risks.
Quantum nano-NMR with NV-centre sensors could enable detailed detection of soil molecular composition, potentially improving analysis of nutrients and organic matter to support more precise and efficient agricultural practices.
Quantum annealing could solve maximum-flow problems in ecological and agrifood networks, potentially enabling more efficient planning of water, nutrients, and logistics by identifying optimal resource throughput under constraints.
Quantum-enhanced Gaussian process models could improve predictions of species distribution and abundance, potentially supporting more accurate biodiversity management and conservation decisions within agricultural and changing environmental conditions.
Hybrid quantum-classical models could improve predictions of evapotranspiration and soil moisture, potentially enabling more accurate irrigation scheduling and supporting efficient use of freshwater in agriculture.
Quantum computing could improve modelling of saltwater intrusion in coastal aquifers, potentially supporting better prediction and management strategies to protect freshwater resources, crop productivity, and soil health.
Quantum computing could improve spatial planning by tackling complex, multi-objective optimisation problems, potentially supporting more efficient land allocation, sustainable resource use, and improved agricultural productivity.
Quantum computing could enhance computer vision for livestock tracking, potentially improving identification and monitoring of individual animals over time and supporting earlier detection of health issues and more efficient farm management.
Quantum computing could improve simulation of protein–immune interactions, potentially enabling more accurate prediction of allergenicity and supporting the design of safer food ingredients with reduced reliance on extensive testing.
Quantum-enhanced simulations could model interactions between antimicrobial candidates and microbial targets, potentially accelerating discovery of targeted preservatives or coatings and reducing reliance on broad-spectrum chemicals and trial-and-error approaches.
Quantum chemistry could improve modelling of molecular interactions in food systems, potentially supporting design of plant-based and low-fat products with better texture, stability, and reduced reliance on additives.
Quantum chemistry could improve modelling of molecular changes during food processing, potentially supporting optimisation of conditions to achieve desired texture, safety, and nutrient retention while reducing energy use.
Water Sector: Use CasesMeerte van Duuren
