Papers
1
Total Citations
48
H-Index
1
About
Xi Tian is a leading researcher in agricultural engineering and nondestructive food quality assessment, with a focus on visible and near-infrared (Vis/NIR) spectroscopy. His most-cited work, published in 2020, has garnered 48 citations and introduces an innovative online Vis/NIR transmission system combined with a diameter correction method to predict soluble solids content in apples. This contribution significantly advances real-time fruit quality monitoring, offering a practical solution for the agricultural industry to enhance postharvest sorting and reduce food waste. Tian’s research bridges precision agriculture and optical sensing, demonstrating how machine learning models can be optimized for accurate, noninvasive analysis of internal fruit properties. His work is highly regarded for its methodological rigor and direct applicability to smart farming technologies. By refining prediction models and correcting for physical variations like fruit size, Tian has set a benchmark for online quality assessment, influencing subsequent studies in horticulture and food engineering. His achievements underscore a commitment to developing scalable, cost-effective tools that support sustainable agriculture and improve supply chain efficiency.
Research Focus
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Top Papers
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