Monitoring grain moisture is essential for the food industry, ensuring food quality and security. This article will explore how using sensors to monitor grain moisture can benefit the industry.
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Why is Monitoring Grain Moisture Important?
Feeding the growing global population requires constant food quality and safety monitoring to ensure food security. Grain is the most commonly consumed food product, feeding both humans and livestock.
Moisture can ruin entire stocks of grain if not monitored correctly. Even if it appears dry on the surface, moisture can exist deep within the grain. If left unchecked, moisture can lead to mold development, insect infestation, fermentation, loss of freshness, germination, odor development, and discoloration. It can also lead to problems with reduced yields.
Grain is of critical importance to the world’s food supply, so research into improving grain moisture monitoring is a key area of study in the agriculture and food industries. Monitoring moisture improves quality control and processing efficiency. It also ensures food safety, prevents undue economic loss, and reduces waste.
Grain should be dried as soon as possible post-harvest and kept under low moisture conditions to ensure safe storage and the quality of food products and animal feed. Technology plays a key role in ensuring that grain is stored in environments with optimal moisture conditions.
Traditional Grain Moisture Monitoring
Prior to the invention of modern moisture monitoring technologies, farmers had to visually inspect their products to determine if they were dry enough to use. Another traditional approach is using an oven dry test.
Both of these approaches are inefficient, costly, and time-consuming. With visual inspections, there is an unacceptable margin of error, and despite the best efforts of individuals inspecting the grain, problems could persist downstream of quality control measures.
Modern Approaches to Grain Monitoring
Modern agricultural and food industries exploit several technologies to ensure the quality of food and animal feed. Direct methods such as distillation and gravimetric techniques are available for farmers and agro-industrial companies, but these can be less accessible, time-consuming, and require specialist equipment and facilities.
Indirect approaches such as magnetic measurement, microwave, magnetic resonance, infrared tomography, dielectric constant change, and electrical resistance/impedance methods provide faster response times than direct analysis. The use of indirect approaches should take into account test conditions and margins of error, and these methods must be calibrated periodically.
The various techniques employed by agro-industrial companies are governed by international standards such as USDA and ISO. Some analytical methods which are commonly employed for monitoring grain moisture levels include infrared radiation, gravimetric analysis, and Karl Fischer titration. These methods offer the benefits of repeatability, reliability, and accuracy.
Portable rapid measuring equipment is widely used in the agricultural and food industries, which are employed for rapid monitoring and detection on production lines.
The Benefits of Sensor Technologies in Agriculture
Industry 4.0 is a conceptual term that includes technologies such as machine learning, neural networks, Big Data, the Internet of Things, and smart sensors. These technologies have been widely applied in multiple industries, providing rapid advances in accuracy and predictive methods of operation.
Sensors are a central technology in many industrial processes in the 21st century, providing accurate real-time data which can be fed into central hubs for analysis by dedicated software and trained professionals. New, innovative grain moisture monitoring methods vastly improve the accuracy and efficiency of quality control, ensuring that grain is usable.
A distinct advantage of using sensors and machine learning techniques is their non-destructive nature compared to traditional grain moisture analysis and monitoring methods. This benefit is shared by several indirect methods which have been developed over the past few decades.
On-line near infrared moisture sensors are one such technology that is used to monitor grain moisture. These sensors are non-contact and provide non-destructive testing capabilities. They provide rapid and real-time analysis of grains and can be mounted above belts and conveyors or installed in silos and storage hoppers. The timely nature of results leads to greater profitability and uptime.
Other sensor-based approaches make use of methods such as near-infrared spectroscopy and radio frequency technologies. The various sensors employed for monitoring this crucial food safety and security issue are suitable for on-line, off-line, and laboratory instrumentation. These technologies save time and money by rapidly detecting variables and improving real-time correction.
Novel Approaches in Grain Moisture Monitoring
Although sensors have been utilized in the agricultural industry for several decades for purposes such as grain moisture monitoring, the rise of technologies such as machine learning, neural networks, and cloud computing has seen their integration into novel and innovative approaches for this crucial food security purpose. Wireless sensor networks are seeing growing use in the agricultural and food industries.
Rapid advances have been made in recent years in visible spectrum imaging, which uses integrated smart sensor systems. Unparalleled accuracy in determining factors such as grain surface morphology and characteristics has been made possible through recent innovative advances.
In visible spectrum analysis, for instance, relative changes in RGB and HIS color values and correlation between morphological characteristics, geometric characteristics, and moisture content provide pertinent information which improves grain quality control.
Innovative approaches developed in recent years for determining grain moisture content include predictive ANN and SVR modeling techniques, RF-based moisture content analysis in combination with artificial neural networks, microwave attenuation methods, and on-line measurement by resistance sensors.
Other approaches include inspection cards for rice moisture content measurement, analyzing the mechanical properties of grains to provide moisture content information, using a biospeckle technique to indirectly determine moisture content, and using dielcometric methods to evaluate gain moisture content. Sensors have a key role in each of these novel and innovative monitoring techniques.
Ensuring that grain is dry enough to use is a key concern in the agricultural and food industries. Incorrectly monitored grain stores can lead to food insecurity for populations, economic loss for producers, and can have a knock-on effect on food prices, leading to further social issues. Due to the critical nature of this issue, innovative technologies are being increasingly employed in the sector.
Sensors can help monitor grain moisture, improve food quality and security, and provide benefits such as real-time analysis and data, non-destructive testing capabilities, and improved grain storage and monitoring efficiency. Advances in technologies such as artificial intelligence are also improving the quality of the stored grain, and sensors can be incorporated into emerging technologies.
References and Further Reading
Flor, O et al. (2022) New Sensing Technologies for Grain Moisture Agriculture 12(3) 386 [online] mdpi.com. Available at: https://www.mdpi.com/2077-0472/12/3/386
Rice Knowledge Bank (2022) Grain moisture content and grain quality [on-line] knowledgebank.irri.og. Available at: http://www.knowledgebank.irri.org/step-by-step-production/postharvest/drying/drying-basics/grain-moisture-content-and-grain-quality
Finna Sensors (2022) Grain Moisture Sensor [online] finnasensors.com. Available at: https://finnasensors.com/grain-moisture-sensor/