Author: New Jersey Agricultural Experiment StationPublisher:
ISBN:
Category : Agriculture
Languages : en
Pages : 1112
Book Description
Bulletin
Author: New Jersey Agricultural Experiment StationPublisher:
ISBN:
Category : Agriculture
Languages : en
Pages : 1112
Book Description
The Victory Garden Cookbook
Author: Marian MorashPublisher: Alfred A. Knopf
ISBN: 039470780X
Category : Cookbooks
Languages : en
Pages : 386
Book Description
Includes over 800 recipes for using fresh vegetables, plus essential gardening information and ideas on how to use your harvest.
Bulletin
Author: Recent Investigations on the Control of Three Important Field Diseases of Sweet Potatoes
Author: Robert Frank PoolePublisher:
ISBN:
Category : Fungal diseases of plants
Languages : en
Pages : 48
Book Description
Research Bulletin
Author: Bulletin
Author: Idaho Agricultural Experiment StationPublisher:
ISBN:
Category : Agriculture
Languages : en
Pages : 798
Book Description
DEPTH IMAGING AND APPLICATION IN POTATO QUALITY GRADING
Author: Qinghua SuPublisher: CAYLEY NIELSON PRESS, INC.
ISBN: 1957274158
Category : Computers
Languages : en
Pages : 249
Book Description
As one of the world's most important crops, potatoes play an important role in maintaining the stability of the global food supply. Many countries, including China, believe that food supply security is a basic condition for maintaining national stability and development. Therefore, potatoes can not only solve the problem of international food shortage, but also promote the development of international trade. In recent years, with the continuous improvement of planting technology, the global production and trade volume of potatoes have also been continuously increasing. However, the development of traditional potato quality grading technology is relatively slow. Currently, it still relies on manual sorting in many countries and regions. Because workers can not keep their attention for a long time under huge work pressure and their understanding of grading standards is inconsistent, large amount of wrong potato grading often occurs. This result not only affects farmers' income, but also causes serious waste in the potato processing due to unqualified raw potatoes. In addition, with the continuous increase of manual wages, the cost of manual grading of potatoes has under challenge. Therefore, achieving automation of potato quality grading is imperative. Traditional grading system mainly uses cameras to capture potato color images, and achieves potato quality grading through color information analysis. This method can reach high success rate for certain defects detection, such as green skin, surface rot and mechanical damage. Due to the variety of shapes of potatoes growing underground, the appearance defects, such as bending, bump and hollow, are widely existing. These abnormal samples may fail to be detected and grade to wrong quality groups, the 3D appearance information cannot be fully perceived in 2D color images. In response to such issues, we have decided to build a machine vision system based on depth cameras, which can obtain depth images of potatoes with 3D shape information. Unlike each pixel in a color image that stores color information, each pixel in a depth image stores the distance from the target to the camera. Therefore, the potato 3D surface features can be sensed and used for bump and hollow defects detection. To capture high-quality depth images, we have constructed a specialized depth imaging system, and developed the image acquisition software based on OpenCV and OpenNI framework. Then, each potato surface features are analyzed and extracted for shape analysis, defect detection, and overall quality grading. In recent years, machine learning technology has developed rapidly and has been widely applied in fields such as object recognition and feature detection. Hence, we also apply machine learning technology to the field of potato quality grading. By developing a machine learning model based on convolutional neural networks, we can directly input potato depth images and get the corresponding quality level of the samples. The experiment achieved good grading results. Since color and depth images of potatoes are actually collected simultaneously in data collection step, a novel algorithm is developed for potato 3D model rebuilding. The method is based on Point Cloud Library and OpenGL technology, and it shows the advantage in solving the problem of data traceability, especially when users have objections to automatic quality classification results. This model not only displays 3D potato shape model, but also supports scaling and 360-degree rotation operations. Overall, we believe that with the development of machine learning and depth sensing, potato quality grading systems will become more intelligent, efficient and low-cost.
New Jersey Agriculture
Author: Potato Production Systems
Author: Jeffrey C. StarkPublisher: Springer Nature
ISBN: 3030391574
Category : Science
Languages : en
Pages : 633
Book Description
This comprehensive guide to potato production systems management contains 20 chapters and more than 350 color photographs. Beginning with the history of potato culture, it spans all aspects of potato production, pest and planting management, storage, and marketing. Written by a team of over 35 scientists from North America, this book offers updated research-based information and serves as a unique, valuable tool for researchers, extension specialists, students, and farm managers. More than a description of principles, it contains practical analytical tools, charts, and methods to create guidelines for best production practices and cost estimates. Some key areas include: Potato Growth and Development, Potato Variety Selection and Management, Seed and Planting Management, Seed Production and Certification, Field Selection, Crop Rotation, and Soil Management, Integrated Pest Management for Potatoes, Potato Nutrient Management, Irrigation Management, Tuber Quality, Economics and Marketing, Production Costs, among others. Potato Production Systems should be a valuable reference for successful culture of the "noble tuber."
Author: