Canola meal is derived from the crushing of canola seed for oil extraction. Although it has been used in swine diets for a long time, its inclusion levels have been limited due to concerns regarding its nutritive value primarily arising from results of early studies showing negative effects of dietary canola meal inclusion in swine diets. Such effects were attributable to the presence of anti-nutritional factors (ANF; notably glucosinolates) in canola meal. However, due to advances in genetic improvements of canola that have led to production of cultivars with significantly lower ANF content and improved processing procedures, canola meal with a superior nutritive value for non-ruminant animals is now available. Therefore, the aim of this paper is to review the recent studies in the use of canola meal as feedstuff for swine, the factors influencing its use and the strategies to overcome them. First a historical overview of the development of canola is provided.

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Recent advances in canola meal utilization in swine nutrition.

We developed an expert system for detection of rapeseed variety using computer vision and machine learning.Scanner images can be used to discriminate rapeseed variety.Developed algorithm determines successfully variety of rapeseed with an accuracy rate of 99.24%. Rapeseed is widely cultivated throughout the world for the production of animal feed, vegetable fat for human consumption, and biodiesel. Since the seeds are evaluated in many areas for sowing and oilseed processing, they must be identified quickly and accurately for selection of a correct variety. An affordable method based on computer vision and machine learning was proposed to classify the seven rapeseed varieties. Different types of feature sets, feature models, and machine learning classifiers were investigated to obtain the best predictive model for rapeseed classification. The training and test sets were used to tune the model parameters during the training epochs by varying the complexity of the predictive models with grid-search and K-fold cross validation. After obtaining optimized models for each level of complexity, a dedicated validation set was used to validate predictive models. The developed computer vision system provided an overall accuracy rate of 99.24% for the best predictive model in discriminating rapeseed variety.

Discriminating rapeseed varieties using computer vision and machine learning

/pdf/review-recent-advances-in-canola-meal-utilization-in-swine-4fvmj4f8l3.pdf

REVIEW : Recent advances in canola meal utilization in swine nutrition

The purpose of this chapter is to describe the pulse milling technologies. Milling is the process by which materials are reduced from a larger size to a smaller size. In the case of pulses dehulling or decortication, splitting, and flour milling or grinding, there are several processes that are used for the pulse milling. Milling is the most important process for human consumption of pulses, followed by various methods of cooking and food preparation. The chapter also illustrates the modern industrial methods of milling pulse flours. The production of pulse flours involves grinding whole or dehulled seeds into small particles. To obtain a flour of more uniform particle size, ground particles are passed through one or more screens. The grinding and screening are done as separate processes, or may be simultaneously performed in an automated mill, such as an impact mill or roller mill.

Pulse milling technologies

Effect of enzyme pre-dehulling treatments on dehulling and cooking properties of legumes

IAgricultural and Bioresource Engineering, University ofSaskatchewan, Saskatoon, SK, Canada S7N 5A9; 2Applied Microbiology and Food Science, University of Saskatchewan, Saskatoon, SK, Canada S7N 5AB; JDepartment of Chemical and Petroleum Engineering, University ofCalgary, Calgary, AB, Canada 12N 1N4; and Plasticulture Development Center, National Agricultural Research Project, Ganeshkund, Pune 7, India. Received 12 June 1997; accepted 15 December 1999.

J.A. Ikebudu

Papers

Grain conditioning for dehulling of canola