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The agricultural industry plays an influential role in meeting the food productions demands of an ever increasing population. In many parts of the world today, maximizing production while simultaneously protecting the environment is considered to be a serious issue.
Current food production is progressively turning to the science of spectroscopy to monitor crop health and improve production yields.
Agricultural equipment manufacturers and researchers in the biological sciences trust Avantes spectrometers to offer accurate spectral data at a reasonable cost. Avantes has more than 20 years of experience in developing spectrology solutions for a number of applications, and hence has the expertise to help with designing an optical spectroscopy system for any application.
Applications in Crop Production
Nitrogen Concentration in Rice
Improving crop conditions and monitoring plant health characteristics are major factors of importance in maximizing production yield. A series of indices for the measurement of chlorophyll in the leaves of rice plants1 were developed by Researchers from the Institute of Digital Agriculture at the Zhejiang Academy of Agricultural Sciences in Zhejiang, Hangzhou, China.
Chlorophyll has a strong, well documented correlation to nitrogen content, a prime indicator of plant health.
Using an older version of the AvaSpec-ULS2048CL-EVO, the Researchers investigated the use of the Red Edge Reflectance Index (RERI) and Yellow Edge Reflectance Index (YERI) for calibrating chlorophyll and nitrogen values to reference spectra at each stage of plant development and differing states of plant health2. Once the reference spectra are correlated, the theoretical work behind this study can be applied to other crops.3, 4
Fertilizer Automation Application
The commercial applications which are in use today follow the principles used by the Zhejiang Researchers. The UK agricultural giant, Yara was established in 1905 and committed to technological advancement in the agricultural industry, and has exclusively designed the N-sensor.
This variable-rate, real-time nitrogen sensor works in concert with fertilizer spreaders for monitoring plant conditions and for adjusting fertilizer application accordingly at the point of application. This indicates that the optimal amount of fertilizer is always used, reducing environmental impact and waste from over application of fertilizer and maximizing crop yield.
Wheat in the Pacific Northwest
The protein content in wheat actually influences its price and the declining wheat prices have affected Farmers especially in this region. The soft white winter wheat is well adapted to the PNW climate, and has a lower protein yield when compared to other varieties. Additional nitrogen fertilizer is needed by even other varieties that have a higher protein yield and that are well suited for the region.
Spectroscopy instruments were employed to define a standard for measuring protein levels as well as the equivalent nitrogen values. For Wheat Farmers, this is the first crucial step to developing variable-rate fertilizer technology for commercial application in the Pacific Northwest5.
Food of the Future
Mars colonization projects and long term space missions will demand that humans make food in environments that are less than optimal for plant growth. This has major ramifications for planning to meet the dietary requirements of these future colonies. The effects of low-intensity light on growth, yield of wheat and photosynthesis6 are extensively studied by Researchers of the Laboratory of Environmental Biology and Life Support Technology, in collaboration with the International Joint Research Center of Aerospace Biotechnology & Medical Engineering at Beihang University, Beijing, China.
The Researchers employed an AvaSpec-ULS2048 spectrometer to control the light intensity of various test groups at different growth stages. They found that low light at initial growth stages had little effect in the final yield, as long as sufficient light was available during the later grain filling stages.
Applications during Harvest
An important piece of the puzzle is maximizing harvest and monitoring produce quality on the way to market in order to ensure the future food supply. At this stage of the food stream, spectroscopy is employed as a non-destructive method to assess the quality and ripeness of produce.
Researchers around the world are working in the NIR range to develop indices for standard qualitative assessment of a variety of produce. These indices can be employed in-line to automate grading and sorting at the point of harvest and after.
Jonagold apples, sweet cherries in Hungary, peaches in Spain, and numerous types of grapes in Italy are some of the fruits that have been studied for this type of spectroscopy measurement.
Jonagold and Fuji Apples
Earlier, Avantes had already reported on Researchers trying to develop standards for evaluating the quality and ripeness of Fuji and Jonagold apple varieties. Working in near infrared and red range (600-1100 nm), these studies developed multiple objective indices for the qualification of apple quality and ripeness depending on color as well as water and soluble sugar content.
Hungary produces approximately 10-12 thousand tons of cherries per year. Researchers in this city explored the absorption characteristics of anthocyanin, a water soluble plant pigment that appears purple, blue or red based on small changes in the pH of the plant. The AvaSpec-ULS2048L proved to be an optimal instrument for working in the NIR (900-970 nm) and red spectra (570-730 nm), and with samples at several stages of the life cycle and changing health status. Eventually, this project developed four spectra indices to objectively qualify cherry fruit. Besides anthocyanin, water content and color indices were essential factors7.
Perceived ripeness is the main consideration after harvest as it is the most vital quality indicator for customers. However, as objective tests were destructive in nature, the process of qualifying the ripeness indicator has mostly been subjective.
Avantes is of course aware of the fact that water content (which affects firmness) and soluble sugar content (SSC) are largely correlated with fruit quality. Thanks to their spectra absorption properties, NIR spectroscopy has been established as an effective method to measure water content and SSC.
Italian Researchers used an early model equivalent to the AvaSpec-NIR256-1.7 to study the development of an index standard and thus correlate the results of NIR spectroscopy to perceptions of ripeness. This allowed this technology to be employed in commercial applications, thus putting this technology to use in the field8.
Grapes and Wine Production
Wine production is a key industry in many regions around the world, especially in Italy. A team of Researchers from the Department of Agricultural Engineering at the University of Milan, Italy applied Vis/NIR spectroscopy to characterize grape composition at harvest. They sampled an astounding 156 grape varieties in 2005 and 2006 while working toward a rapid in-line means of predicting ripening factors identified to affect wine quality9.
Grape composition at harvest is the main determinant of future wine quality. A number of factors are taken into consideration in grape composition including familiar ripeness indicators such as acidity and soluble sugar content as well as polyphenols and phenolic compounds anthocyanins (as in the cherries study).
This research conducted with the help of the AvaSpec-ULS2048L displayed promise for the progress of a portable VIS/NIR optical measurement system working in the 450-980 nm wavelength range for fast, non-destructive grape quality measurements with a 95% validation rate at the time the research was completed in 2010.
Since that time, spectrometer technology has progressed to the point that these applications are a “ripe” prospect for the creation of commercial systems.
Food Product Applications
There are numerous uses for spectrology in the dairy sector. Fluorescence spectroscopy is used to test milk content for fat, proteins, carbohydrates, water content and minerals. The traditional chemical techniques of analysis require laboratory equipment, specialized personnel, and are mostly destructive in methodology. The constituents of milk products are usually studied in the NIR (800-2500 nm) and UV (185-210 nm) wavelength ranges.
Research conducted by a team at the University of Food Technologies in Plodiv, Bulgaria is aimed, in part, at giving inspectors a tool to control the proliferation of milk products adulterated with the inclusion of sugars, vegetable fats and foreign proteins10.
The French company Spectralys Innovation, along with Actalia, a center of expertise for the food industry, has designed the Amaltheys, a commercial fluorescence analyzer for evaluating denatured whey proteins in cheese milk. This system enables cheese producers to check curd coagulation and standardize cheese production yields11.
Egg and Beef Quality
Work is in progress in order to develop methods for quality assessment of a number of other food products. The uses of VIS/NIR spectroscopy to evaluate beef tenderness and egg freshness are considered to be one of the more interesting and current examples.
Researchers working with Beef from China Agricultural University, College of Engineering, Beijing, China are working with the AvaSpec-NIR256-2.5 spectrometer in order to measure characteristics of meat quality, among them: fat content, color, water content, tenderness and pH. Besides studying the constituent macronutrients, this team also took into account the use of NIR spectroscopy to identify common contaminants such as total volatile basic nitrogen12.
Eggs are considered to be another popular source of protein, and monitoring freshness from within the shell was challenging. However, Researchers from the Egg Quality and Incubation Research Group analyzed the NIR and visible light transmission spectra attained from eggs. Using the AvaSpec-ULS2048L, the EQIRG discovered a powerful connection between the transmission spectra collected and standard measurements of egg freshness, such as Haugh and pH Units, which are capable of measuring protein quality based on the height of the albumin, or egg white13.
Catching Food Counterfeits
There are numerous food products that, because of price or demand, are often counterfeited. Olive oil and honey are two examples of products that are often adulterated or “counterfeit.” Honey is one of the world’s most faked foods. Adulterated alcohol has also been a topic in the news lately with resort areas in Mexico trying to stop the sale of these potentially lethal counterfeits.
Wendy Meulebroeck and a team from the Vrije University Brussels, Belgium published a series of research papers on photonics enhanced sensors in food monitoring in IEEE Instrumentation and Measurement magazine. This research made use of the AvaSpec-ULS3648 spectrometer with resolution possible down to 0.1 nm, and made immense strides in showing the viability of NIR spectroscopy for identification and authentication of liquid and solid food products14.
The Royal Society of Chemistry has also investigated the issue of food scams and is working on the formulation of a point-and-shoot fast detection technique in the field analysis of the food chain15. They assessed the AvaSpec-NIR256-2.5-HSC for use in a system that takes fast food analysis out of the lab and places it on the forefront of stopping food scams.
Avantes in Agriculture and Food
Avantes is a global leader in the development of spectroscopy solutions for real world applications. Avantes is depended upon by Researchers to ensure the world’s food population for the future.
Hu, Hao. “Nitrogen Status Determination of Rice by Leaf Chlorophyll Fluorescence and Reflectance Properties,” Sensor Letters, Volume 9, Number 3, June 2011, pp. 1207-1211
Zhang, Jinheng et al. “New Reflectance Spectral Vegetation Indices for Estimating Rice Nitrogen Nutrition I: Selection of Optimum Vegetation Indices Using Leaf Spectral Reflectance and SPAD Values.” Sensor Letters, Sensor Letters, Volume 9, Number 3, June 2011, pp. 1190-1195(6)
Zhang, Jinheng et al. “New Reflectance Spectral Vegetation Indices for Estimating Rice Nitrogen Nutrition II: Optimum Reflectance Spectral Vegetation Indices for Estimating Rice Leaf Nitrogen Concentration.” Sensor Letters, Sensor Letters, Volume 9, Number 3, June 2011, pp. 1196-1200(5).
Zhang, Jinheng et al. “New Reflectance Spectral Vegetation Indices for Estimating Rice Nitrogen Nutrition III: Development of a New Vegetation Index Based on Canopy Red-Edge Reflectance Spectra to Monitor Rice Canopy Leaf Nitrogen Concentration.” Sensor Letters, Sensor Letters, Volume 9, Number 3, June 2011, pp. 1201-1206(6).
Zhou, Yi et al. “Strategic Nitrogen Supply Alters Canopy Development and Improves Nitrogen Use Efficiency in Dryland Wheat.” Agronomy journal 109(3) January 2017.
Dong, Chen et al. “Low light intensity effects on the growth, photosynthetic characteristics, antioxidant capacity, yield and quality of wheat (Triticum aestivum L.) at different growth stages in BLSS”. Advances in Space Research Volume 53, Issue 11, 1 June 2014, Pages 1557-1566
Attila, Nagy, and Tomas Janos. “Sweet Cherry Fruit Analysis with Reflectance Measurements.” University of Oradea, Department of Environmental Protection Vol. 17, 2011.
S. Capone, et al. “Analysis of Peaches Ripeness by an Electronic Nose and Near-Infrared Spectroscopy” Senors and Microsystems: Proceedings of the 7th Italian Conference. Bologna, Itally. 2002
Guidetti, R. et al. “Evaluation of grape quality parameters by a simple Vis/NIR system.” Transactions of the ASABE 2010 Vol.53 No.2 pp.477-484 ref.28
Dimitrova, T.L. et al. “Scattering and Fluorescence Spectra of Cow Milk.” Bulgarian Chemical Communications, Vol.46 iss. B (pp. 39-43). December 10, 2014.
P, Lacotte et al. “Amaltheys: A fluorescence-based analyzer to assess cheese milk denatured whey proteins.” Journal of Dairy Science. 2015 Oct;98(10):6668-77.
Peng, Yankun , and Wenxiu Wang. “Application of Near-infrared Spectroscopy for Assessing Meat Quality and Safety.” 1 Jan. 2015.
Kemps, Bart et al. “Visible transmission spectroscopy for the assessment of egg freshness.” Journal of the Science of Food and Agriculture, 2006.
Meulebroeck, Thienpont, and Ottevaere. “Photonics enhanced sensors for food monitoring: part 1.” IEEE Instrumentation Measurement Magazine. Volume: 19, Issue: 6, December 2016 .
Royston Goodacre et al. “Point-and-shoot: rapid quantitative detection methods for on-site food fraud analysis – moving out of the laboratory and into the food supply chain.” Analytical Methods, 1 Jan. 2015.
This information has been sourced, reviewed and adapted from materials provided by Avantes BV.
For more information on this source, please visit Avantes BV.