Canadian potato growers are embracing artificial intelligence (AI) to monitor and predict the nutritional needs of their crops in real time.
This innovative approach, spearheaded by researchers from Dalhousie University, is poised to revolutionize the cultivation of potatoes in Canada.
Traditionally, potato growers grapple with challenges in nutrient management, a pivotal aspect directly impacting crop yields. Conventional methods such as soil treatments and foliar feeding, while somewhat effective, face limitations, especially concerning nutrients required during later stages of potato growth.
Rising fuel and fertilizer costs further emphasize the need for more precise and efficient nutrient application.
The team from Dalhousie University, led by Ph.D. candidate Reem Abukmeil and Associate Professor Ahmad Al-Mallahi, utilizes a portable spectrophotometer—an optical sensor—to rapidly determine petiole nutrient values in potato fields.
This technological advancement, coupled with machine learning algorithms trained on historical data, enables near real-time assessment of the plant’s nutritional needs.
The AI-driven approach presents numerous advantages. It empowers farmers to apply fertilizers with greater efficiency and timeliness, ensuring that plants receive the right nutrients at the right stages of growth. This optimization not only enhances crop quality and yields but also strikes a balance between production goals and environmental protection.
As the Canadian potato landscape undergoes this transformative integration of AI technology, it signifies a significant leap forward. Beyond optimizing efficiency and sustainability in potato farming, this approach sets a precedent for other crops.
The newfound ability to efficiently apply necessary fertilizers in a timely manner represents a valuable tool for farmers, promising to strike a harmonious balance between production goals and environmental stewardship.
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