Wheat Detection and Counting Solutions in Global Wheat Head Detection Dataset with Performance-Oriented Strategies

As one of the three major grain crops, wheat is widely planted all over the world. Its planting and production have a direct relationship with people’s food security and health safety. However, after increasing rapidly for decades, the rate of increment in wheat yields has slowed down since the early 1990s [3, 5]. According to the Food and Agriculture Organization of United Nations, the whole world’s demand for wheat is expected to reach 850 million tons by 2050 [1], which means the supply may fall short of demand in the future. Wheat production has become ever more challenging worldwide. Recently, precision agriculture is one of the many strategies designed to improve crop management and maximize crop yields. Precision agriculture relies on monitoring and measuring the growth of crops in real-time [2], which means a huge amount of crop data collected to explore the growing status needs well organization and analysis. However, analyzing such a sheer amount of crop data is overly time-consuming and labor-intensive. Yield estimation is one of the most important tasks in precision agriculture. However, traditional wheat yield estimation requires agricultural experts to manually count the heads of wheat, which is extremely challenging, error-prone, and obviously not cost-effective at all.