Wheat is a fundamental crop that contributes about 20% of the total dietary calories and proteins worldwide . It is one of the key staple crops for global food security, providing more than 35% of the cereal calorie intake in the developing world, 74% in the developed world, and 41% globally from direct consumption .
Wheat as a crop is facing its challenges though. In the US, the maximum reported winter wheat grain yields in the southern Great Plains (that encompasses parts of Texas, New Mexico and Oklahoma) remain well below the theoretical potential both at plot and farm level. In 2023 the provisional estimate of the English wheat harvest is 12.8 million tonnes, a decrease of 10% on 2022 due to decreases in both yield and area in almost all regions. Conversely the global production of wheat is expected to increase over the next decade, reflecting gains made primarily in major grain-producing countries.
However there are several barriers to producing higher volumes including disease control, over farming, herbicides, black grass, not to mention climate change . AI and machine learning can assist with production by enabling farmers to monitor crop moisture, soil composition, and temperature in growing areas. This allows an increase in yields through better care of the crops and determining the ideal amount of water or fertilizer to use. AI algorithms also enable autonomous crop management and can detect leaks or damage to irrigation systems.
AI and machine learning technologies like those being developed by AgriSynth will help shape the future of farming and help farmers optimise their yields while minimizing environmental impact. By using these technologies farmers can reduce inputs, improve yields, and protect their crops from pests and diseases.