Wheat is one of the most important staple food that is consumed globally. It is widely cultivated in more than 30,000 varieties worldwide. Just like for every other food crop, quality plays a major role in wheat. Moisture content and protein content are the 2 important parameters that determine the quality of wheat. There are laboratory tests performed to determine these two parameters. Other laboratory tests usually performed on wheat to measure certain parameters include –
· Tests to measure Ash Content
· Falling Number Test: To measure the level of enzyme activity
· Flour Color Analysis
· Single Kernel Characterization System: To evaluate wheat kernel texture
· Glutomatic: To determine quality of gluten in wheat samples
However, these laboratory methods are difficult to perform and are also time consuming, thus making them less favorable to determine quality characteristics.
Overcoming These Challenges Using AI
Artificial Intelligence going parallel with technologies like Near-Infrared Spectroscopy has been widely used in different industry sectors like pharma and healthcare. The need for advancements has developed a realization within the agricultural sector to adopt these rapid, cost effective and very accurate techniques to measure the quality parameters of agricultural commodities like wheat. These technologies have wide range of applications in the wheat grain industry ranging from physical analysis to chemical composition analysis and identification of contaminants.
Important Quality Parameters for Wheat
This is just an indicative list that very clearly shows the importance of AI and other technological advancements viz., usage of spectroscopy, in the agricultural sector, particularly in analyzing grain quality.These advanced technologies accurately measure the physical and chemical properties of the grain in real time. These technologies have potential for many commercial applications and can thus transform the Agriculture Sector.
Market Research Associate at AgNext