Proceedings :: International Society of Precision Agriculture

Proceedings

Find matching any: Reset

Gardezi, M

Xu, J

» Add more authors

Add filter to result:

Authors

Xu, J

Lu, Y

Kumari, S

Rathore, J

Mitra, S

Gardezi, M

Walsh, O

Gardezi, M

Walsh, O

Joshi, D

Kumari, S

Clay, D.E

Rathore, J

Xu, J

Lu, Y

Topics

Robotics and Automation with Row and Horticultural Crops

Site-Specific Nutrient, Lime and Seed Management

Artificial Intelligence (AI) in Agriculture

International Symposium on Robotics and Automation

Type

Poster

Year

2024

Home » Authors » Results

Authors

Filter results4 paper(s) found.
1. Automated Detection and Length Estimation of Green Asparagus Towards Selective Harvesting Green asparagus is an important vegetable crop in the United States (U.S.). Harvesting the crop is notoriously labor-intensive, accounting for over 50% of production costs. There is an urgent need to develop harvesting automation technology for the U.S. asparagus industry to remain sustainable and competitive. Despite previous research and developments on mechanical asparagus harvesting, no practically viable products are available because of their low harvest selectivity and significant yield... J. Xu, Y. Lu
2. Predicting Soybean Yield Using Remote Sensing and a Machine Learning Model Soybean (Glycine max L.), a nutrient-rich legume crop, is an important resource for both livestock feed and human dietary needs. Accurate preharvest yield prediction of soybeans can help optimize harvesting strategies, enhance profitability, and improve sustainability. Soybean yield estimation is inherently complex because yield is influenced by many factors including growth patterns, varying crop physiological traits, soil properties, within-field variability, and weather conditions. The objective... M. Gardezi, O. Walsh, D. Joshi, S. Kumari, D.E. Clay, J. Rathore Download paper
3. Optimizing Soil Nutrient Management: Agricultural Policy/environmental Extender (APEX) Model Simulation for Field Scale Phosphorous Loss Reduction in Virginia Managing soil nutrients is crucial for enhancing crop productivity and meeting consumptions demands while minimizing environmental impacts. Sustainable agriculture relies on well-planned soil nutrient management strategies. Phosphorous (P) stands out among the 16 essential soil nutrients, particularly in Virginia, where natural P levels are typically low. Adequate amount of P is necessary for the early root formation and plant growth. However, excess amount of P in the soil leads to increase the... S. Kumari, J. Rathore, S. Mitra, M. Gardezi, O. Walsh Download paper
4. Development of a Multispectral Vision-based Automated Sweetpotato Grading System Quality evaluation and grading of sweetpotatoes is a manual operation that requires significant labor input. Machine vision technology offers a promising solution for automated sweetpotato grading and sorting. Although color imaging is widely used for quality evaluation of various horticultural commodities, a multispectral vision technique that acquires color and near-infrared (NIR) images simultaneously is a potentially more effective modality for fruit grading, especially for defects, while... J. Xu, Y. Lu

Filter results4 paper(s) found.

1. Automated Detection and Length Estimation of Green Asparagus Towards Selective Harvesting

Green asparagus is an important vegetable crop in the United States (U.S.). Harvesting the crop is notoriously labor-intensive, accounting for over 50% of production costs. There is an urgent need to develop harvesting automation technology for the U.S. asparagus industry to remain sustainable and competitive. Despite previous research and developments on mechanical asparagus harvesting, no practically viable products are available because of their low harvest selectivity and significant yield... J. Xu, Y. Lu

2. Predicting Soybean Yield Using Remote Sensing and a Machine Learning Model

Soybean (Glycine max L.), a nutrient-rich legume crop, is an important resource for both livestock feed and human dietary needs. Accurate preharvest yield prediction of soybeans can help optimize harvesting strategies, enhance profitability, and improve sustainability. Soybean yield estimation is inherently complex because yield is influenced by many factors including growth patterns, varying crop physiological traits, soil properties, within-field variability, and weather conditions. The objective... M. Gardezi, O. Walsh, D. Joshi, S. Kumari, D.E. Clay, J. Rathore

Download paper

3. Optimizing Soil Nutrient Management: Agricultural Policy/environmental Extender (APEX) Model Simulation for Field Scale Phosphorous Loss Reduction in Virginia

Managing soil nutrients is crucial for enhancing crop productivity and meeting consumptions demands while minimizing environmental impacts. Sustainable agriculture relies on well-planned soil nutrient management strategies. Phosphorous (P) stands out among the 16 essential soil nutrients, particularly in Virginia, where natural P levels are typically low. Adequate amount of P is necessary for the early root formation and plant growth. However, excess amount of P in the soil leads to increase the... S. Kumari, J. Rathore, S. Mitra, M. Gardezi, O. Walsh

Download paper

4. Development of a Multispectral Vision-based Automated Sweetpotato Grading System

Quality evaluation and grading of sweetpotatoes is a manual operation that requires significant labor input. Machine vision technology offers a promising solution for automated sweetpotato grading and sorting. Although color imaging is widely used for quality evaluation of various horticultural commodities, a multispectral vision technique that acquires color and near-infrared (NIR) images simultaneously is a potentially more effective modality for fruit grading, especially for defects, while... J. Xu, Y. Lu