agriculture
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YOLOv8 Tutorial: Classify Agricultural Pests
Read Full Article: YOLOv8 Tutorial: Classify Agricultural Pests
This tutorial provides a comprehensive guide for using the YOLOv8 model to classify agricultural pests through image classification. It covers the entire process from setting up the necessary Conda environment and Python libraries, to downloading and preparing the dataset, training the model, and testing it with new images. The tutorial is designed to be practical, offering both video and written explanations to help users understand how to effectively run inference and interpret model outputs. Understanding how to classify agricultural pests using machine learning can significantly enhance pest management strategies in agriculture, leading to more efficient and sustainable farming practices.
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Arizona Water Usage: Golf vs Data Centers
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In Maricopa County, Arizona, golf courses consume significantly more water than data centers, using approximately 29 billion gallons annually compared to the 905 million gallons used by data centers. Despite this disparity, data centers generate more tax revenue, contributing $863 million statewide in 2023, compared to $518 million from the golf industry in 2021. When evaluating tax revenue per gallon of water used, data centers are about 50 times more efficient. The broader context reveals that agriculture accounts for 70% of Arizona's water usage, while data centers use less than 0.1%. Understanding these figures can help reframe discussions around water usage priorities and economic contributions in Arizona.
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Engineering Resilient Crops for Climate Change
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As global warming leads to more frequent droughts and heatwaves, the internal processes of staple crops are being disrupted, particularly photosynthesis, which is crucial for plant growth. Berkley Walker and his team at Michigan State University are exploring ways to engineer crops to withstand higher temperatures by focusing on the enzyme glycerate kinase (GLYK), which plays a key role in photosynthesis. Using AlphaFold to predict the 3D structure of GLYK, they discovered that high temperatures cause certain flexible loops in the enzyme to destabilize. By replacing these unstable loops with more rigid ones from heat-tolerant algae, they created hybrid enzymes that remain stable at temperatures up to 65°C, potentially leading to more resilient crops. This matters because enhancing crop resilience is essential for maintaining food security in the face of climate change.
