The Application of Deep Learning in the Whole Potato Production Chain: A Comprehensive Review

Agriculture, Год журнала: 2024, Номер 14(8), С. 1225 - 1225

Опубликована: Июль 25, 2024

The potato is a key crop in addressing global hunger, and deep learning at the core of smart agriculture. Applying (e.g., YOLO series, ResNet, CNN, LSTM, etc.) production can enhance both yield economic efficiency. Therefore, researching efficient models for great importance. Common application areas chain, aimed improving yield, include pest disease detection diagnosis, plant health status monitoring, prediction product quality detection, irrigation strategies, fertilization management, price forecasting. main objective this review to compile research progress various processes provide direction future research. Specifically, paper categorizes applications into four types, thereby discussing introducing advantages disadvantages aforementioned fields, it discusses directions. This provides an overview describes its current stages chain.

Язык: Английский

Organic substitution enhances soil quality, soil microbial community stability, foxtail millet productivity, and grain quality in North China

Journal of Environmental Management, Год журнала: 2025, Номер 384, С. 125613 - 125613

Опубликована: Май 2, 2025

Язык: Английский