Feed Analysis

The production of efficient, high-quality animal products relies heavily on the precise supply of nutrition in the ration. Good animal feeding plays a key role in safeguarding animal hygiene and health as well as producing safe and high-quality products of animal origin. The demand for animal-derived protein has led to the intensification of livestock production and the predominant use of industrial compound feeds, which leads livestock producers to feed their livestock with better quality feeds, which drives the demand for feed analysis, which is important in ensuring feed quality and animal quality aspects.

Our Solution

Lifeasible provides solutions for feed analysis, including inspection of physical properties of feed, analysis of conventional ingredients in feed, detection of feed energy, amino acids, minerals, toxic and harmful substances, vitamin additives, feed processing quality, detection of enzyme activity in enzyme preparations, and data processing and quality control of NIR spectral analysis results.

Feed quality monitoring platform

Under the premise of ensuring the quality of feed materials, scientific and reasonable feed formulation and the realization of feed formulation in feed processing are important in guaranteeing feed's biological efficiency. Traditional feed quality monitoring adopts manual sampling and off-line analysis, which takes a long time and many steps, and there are unqualified products that are missed, which has a lag in guiding and adjusting feed formulations. We use online NIR monitoring technology to detect the nutrient content of feed ingredients and products in real-time and quickly, and dynamically adjust the formulation of feed ingredients to achieve accurate nutrition and fidelity processing of established formulations.

Optimization of feed protein, fat, and vitamin ratios

Protein is the costliest part of the feed, and the appropriate level of protein is essential for designing the optimal cost formulation. In addition to providing essential fatty acids for animals, fat is also an important energy supplier. Vitamins are also one of the most important nutrients in the feed and play an important role in maintaining the normal metabolism and physiological functions of the body. Therefore, we offer optimized solutions for the composition of feed rations to save costs and get the best output ratio.

Feed nutritional value assessment

Assessment techniques and methods

• Chemical composition assessment
• Approximate nutrient analysis method
• Fan's fiber analysis method
• CNCPS system
• Near-Infrared Spectroscopy

Analysis of nutritional components of fodder crops

Evaluation of effective energy

A regression model between net energy and digestive or metabolic energy is derived from the measured net energy data of a certain number of representative feeds, and thus, the net energy value of the feed is calculated.

Determination of crude fat and crude fiber content in the feed

Accurate formulation of feed nutrition can not only improve the quality of feed but also save costs. Crude fat and crude fiber are the main components of feed, and their content detection is an important part of feed formulation. The traditional method of feed composition is a wet chemical detection method with high sensitivity and accuracy, but the operation is complicated, the detection time is long and the cost is high.

Therefore, we introduced NIR spectroscopy to achieve the content detection of crude fat and crude fiber in feeds. And before establishing a regression model for content analysis using NIR spectroscopy, spectral pre-processing methods and variable selection methods were used to simplify the model to improve its analytical accuracy.

Applications

• Monogastric animal nutrition and feed
• Ruminant nutrition and feed
• Animal molecular nutrition and feed biotechnology
• Feed absorbable nutrient release dynamics and feed nutrient utilization
• Physicochemical properties and molecular structure of feeds
• Feed safety and quality of livestock products

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For research or industrial use.

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