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| Filter results8 paper(s) found. |
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1. Inversion of Potato Chlorophyll Content Based on Radiation Transfer Model and Machine Learning AlgorithmLeaf chlorophyll content (LCC) significantly correlates with crop growth conditions, nitrogen content, yield, etc. It is a crucial indicator for elucidating the senescence process of plants and can reflect their growth and nutrition status. However, the performance of traditional LCC inversion models is limited by the quality and scale of training data. It is difficult to satisfy the needs of precision agriculture. 【Objective】Therefore, this study proposes a hybrid modeling framework based... Y. Ma, J. Zhang, D. Pan, Q. Wu, S. Xiaoyu, X. Xu |
2. Development of a Label-free Electrochemical Biosensor for Detection of Infectious Hepatitis a VirusOne of the leading causes of foodborne viral illnesses in the world is Hepatitis A Virus, which is frequently involved in causing outbreaks linked to contaminated produce and shellfish (e.g., green onions and berries) due to contamination during cultivation, processing, or handling. HAV is highly stable in environment capable of remaining infectious on food matrices and in water for extended periods. Humans get infected primarily via the fecal-oral route... D. Kaur, R.P. Ramasamy, M. Esseili |
3. Precision Tillage Operations: Analyzing the Efficiency of Conventional and Robotic SystemsABSTRACT. The crop production sector is labor- and energy-intensive, significantly impacting the environment. Soil tillage is one of the most expensive and polluting technological operations; therefore, modern automated and precision technologies applied according to soil variability can help change economic costs and environmental pollution. This study evaluated the effects of site-specific variable depth tillage using two combinations of a conventional tractor and a multifunctional cultivator,... E. Šarauskis, S. Sokas, I. Bručienė, S. Buragienė, M. Kazlauskas, V. Naujokienė |
4. The Agronomic and Bioeconomic Aspects of Site-Specific Seeding Rates and Depths for Winter Wheat in LithuaniaPrecision seeding is one of the most important agrotechnological solutions for smart agriculture. It exploits the variability of soil properties in the field to increase the agronomic and economic efficiency of crops. This study investigated the impact of site-specific seeding (SSS) on the yield and productivity parameters of winter wheat in Lithuania, as well as its economic benefits, compared with conventional uniform rate seeding (URS). Experiments were conducted in a field divided into five... Z. Kriauciuniene, M. Kazlauskas, K. Romaneckas, S. Buragiene, I. Bručienė, E. Šarauskis |
5. A Machine Learning Framework for Crop Productivity Classification and Risk AssessmentThe integration of Artificial Intelligence and Remote Sensing is essential for the early identification of agricultural fields with suboptimal growing conditions. Such capabilities are vital for targeted interventions, supply chain logistics, and agricultural risk management. This study developed and validated a machine learning framework designed to classify the productivity conditions of corn, soybean, and wheat into ‘Low’, ‘Medium’, and ‘High’ tiers, utilizing... J.D. Xavier, K. Schenatto, G.V. Miranda, C.L. Bazzi, R. Sobjak |
6. Study on the Phenological Zoning Method for Winter Wheat in the Huang-Huai-Hai Region of ChinaThe impact of global climate change on agricultural phenology is becoming increasingly significant. As a major producer of winter wheat, China's cultivation areas span multiple climate zones. Against the backdrop of climate change, the spatiotemporal differentiation of crop phenology has raised new scientific demands for agricultural zoning. Phenological zoning has guiding significance for variety selection, irrigation management, and pest prediction. However, existing research often relies... S. Xiaoyu, Q. Wu, Y. Ma, J. Zhang, P. Dong, X. Xu |
7. Who is the Agricultural Practitioner of the Future?An agricultural industry that continues to adopt new technologies and rely on data-driven decisions demands a unique skillset from its practitioners that goes beyond traditional agricultural training. Despite this demand, relatively few technology-focused agriculture programs are available at the post-secondary level worldwide. In 2020, Olds College of Agriculture & Technology (Alberta, Canada) created a 2-year diploma in Precision Agriculture (launched in 2020) and a 4-year Bachelor of Digital... D. Karran, B. Hoffos, F.H. Karp |
8. Estimation of Sugarcane Yield Based on Phenological Feature Extraction from Time-Series Sentinel-1 Images and Machine LearningDue to frequently rainy and cloudy weather in the main sugarcane production areas, optical remote sensing data are often missing, and the conventional yield estimation models based on radar remote sensing data lack the support of crop growth mechanisms. This study aims to explore a new yield estimation method for capturing the key dynamic growth features of sugarcane under all-weather conditions. This study takes the sugarcane yield in the dominant area of sugarcane production, Guangxi Zhuang... H. Xue, X. Xu, G. Yang, Z. Xu, S. Xiaoyu, L. Chen |