Explore recent research papers collected from PubMed.
This study develops an intelligent sorting system using a modified YOLOv10n deep learning model to distinguish potato tubers from mineral impurities like soil and stones. The system achieves high sorting accuracy and efficiency, optimizing postharvest processing through automated identification and pneumatic rejection.
This study evaluates various YOLO deep learning architectures for automated potato quality detection and sorting into edible, feed, and rotten categories. Using a dataset from multiple locations, the research demonstrates that low-cost RGB-based systems can achieve high accuracy and transferability for post-harvest potato inspection.
This study investigates the impact of traditional Andean chuño processing on the structural and functional properties of starch from three potato cultivars. The research demonstrates that processing leads to reduced amylose content, increased thermal stability, and significant structural reorganization of starch granules while preserving their fundamental B-type crystalline polymorph.
This study investigates the effect of soluble arabinoxylan on the quality and starch retrogradation of mashed potatoes during cold storage. The results show that arabinoxylan improves water retention, inhibits starch recrystallization, and maintains the sensory appeal and soft texture of the product, suggesting its potential as a functional modifier for potato-based foods.
This study investigates how different culture conditions, including the selection of specific potato ecotypes like Leke Pek'e, influence the antifungal activity of Trichoderma harzianum against Botrytis cinerea. The research highlights that the chemical composition of potato-based media significantly affects the production of bioactive metabolites for biocontrol applications.
This study describes the development of a dual-emission carbon quantum dot composite film designed for greenhouse potato production. The film significantly enhances potato tuber yield and photosynthetic rates by optimizing light spectra and improving photosystem II efficiency.
This study identifies and characterizes the miR482 family in Solanum tuberosum, exploring its role in responding to alkaline salt stress and the stress-alleviating effects of 24-epibrassinolide. The research highlights tissue-specific expression patterns of various miR482 members and predicts target genes involved in stress signaling and disease resistance.
This study develops a regional critical nitrogen dilution curve for potatoes in northern China using a Bayesian hierarchical model to diagnose nitrogen status. It identifies specific growth stages as optimal windows for using canopy spectral sensors to predict the nitrogen nutrition index, providing a framework for precision nitrogen management across different cultivars and environments.
This study compares the physicochemical and functional properties of maltodextrins derived from starch of various Solanum tuberosum cultivars, including red-, purple-, and light-fleshed varieties. The research highlights that maltodextrins from colored potato varieties possess superior solubility, water absorption, and distinct gelling properties compared to yellow varieties due to differences in microstructure and molecular weight profiles.
This study investigates how nitrogen supply influences the physiological response of Solanum tuberosum to heat stress. It demonstrates that sufficient nitrogen mitigates yield loss by maintaining radiation use efficiency and improving dry matter partitioning to tubers under high-temperature conditions.