Wheat is a major source of food and energy in the major parts of the world. In many developing world post harvest losses in the cereals of 10-15 is quite common. (Lucia & Assennato,1994).
Grains are stored for many reasons like time utility, place utility and to harvest better price. The stored grain losses include both in quantity and quality. These losses occur when the grains are attacked by insects, mite rodents and microorganisms. Besides consuming grains, insects also contaminate the grains by their by-products and making them unfit for consumption.
Monitoring the stored grain pest is as important as monitoring the field problems. Monitoring of stored grain pest is finding out the trends in insect numbers or infestation levels in a period of time. It helps to understand the population behaviour of insects with respect to environmental conditions; to know the time for pesticide application and to determine the effectiveness of pest management actions.
Tools and techniques used for sampling stored grain pests
1. Grain probe traps: Grain probe traps are mostly used to detect the presence of insects in stored grains. The traps are inserted into the grain mass and left for a period of time. This allows insects to crawl into the probe for counting and identification at a later time. Populations of insects should be monitored periodically to see whether there is any increase or not. These traps are good for monitoring beetle-like insects. Consistent trapping intervals are important in providing accurate counts, and in determining whether or not population increases are occurring.
2. Sticky traps: To monitor flying insects (moths), sticky traps baited with pheromone attractants are useful. These traps are placed in grain bins at the top of the bin, and attract male species of moth which become trapped to the sticky cardboard structure. High populations of moths indicate whether there is likely to be a problem.
3. UV – LIGHT TRAP FOR GRAIN STORAGE GODOWNS: The UV light trap can be placed in food grain storage godowns at 1.5 m above ground level, preferably in places around warehouse corners, as it has been observed that the insect tends to move towards these places during the evening hours. The trap can be operated during the night hours. The light trap attracts stored product insects of paddy like lesser grain borer, Rhyzopertha dominica, red flour beetle, Tribolium castaneum and saw toothed beetle, Oryzaephilus surnamensis in large numbers. Psocids which are of great nuisance in godowns are also attracted in large numbers. Normally 2 numbers of UV light trap per 60 x 20 m (L x B) godown with 5 m height is suggested. The trap is ideal for use in godowns meant for long term storage of grains, whenever infested stocks arrive in godowns and during post fumigation periods to trap the resistant strains and left over insects to prevent build up of the pest populations. In godowns of frequent transactions the trap can be used for monitoring.
4. Grain triers and bullet probes: Grain triers and bullet probes are also useful for monitoring stored grains for insects. However, they are only useful when the sampler is present. Trier samples should be taken from the top centre area of the grain mass. South to southwest quadrants of the bin, where temperature increases are more likely, are areas where insect activity might also be increased. Check areas where moisture might have contaminated the grain, especially around doors and aeration fans. Deeper regions of the grain mass should be checked using bullet probes.
5. Pelican samplers: Pelican samplers and similar devices are used to gather samples of grain while it is flowing. The composition of samples is used to determine presence and quantity of insects in the grain.
6. A simple way to check for heating is to insert a metal rod into the bulk of the grain for one hour, making note of an increase in temperature. This will indicate whether heating is occurring or not.
7. Mechanical device: Ludhiana based Central Institute of Post Harvest Engineering and Technology (CIPHET) under Indian Council of Agricultural Research has developed a mechanical device for detection of insects in stored grains. The device is capable of instant detection, and a fair quantification, of insect infestation in stored food grains. The device facilitate the detection of the presence or absence of live or dead insects in stored grain and it also allows to visualize the egg infestation in the grain sample; that further provide a fair quantification of insect infestation level.
Modern Insect detection Techniques
1. Acoustical methods: These methods use insect feeding sounds to automatically monitor both internal and external feeding insects. Insects hidden inside kernels of grain can be can be detected acoustically by amplification and filtering of their movement and feeding sounds. The disadvantage with this method is that it cannot detect dead insects in grain and infestation by early larval stages of insects. (Neethirajan et al. 2007)
2. Electrical conductance: Pearson, Brabec, and Schwartz (2003) detected hidden internal insect infestations in wheat kernels using electrical conductance. Their studies showed that the identification accuracies for all wheat samples were 88% for large sized larvae, and 87% for pupae, and there was no sound kernel misclassified as infested.
3. Near Infrared Reflectance (NIR) spectroscopy: The NIR spectroscopy has evolved as a fast, reliable, accurate and economical technique available for compositional analysis of grains (Kim, Phyu, Kim, & Lee, 2003). This technique can be used for both qualitative and quantitative analysis. The NIR technique provides information based on the reflectance properties of different substances present in a product.
4. X-ray imaging: Soft X ray is the only non-destructive direct method that can detect insect infestation in grain kernels. Karunakaran (2003) correctly identified wheat kernels infested with Sitophilus oryzae larvae and pupae adults with more than 97% accuracy from the soft X-ray images.
These modern techniques are yet to be popularized in India
During monitoring of stored grain pest following points should be taken care of
1. Odours that are not usually found in stored grain — musty or mint-like odours indicate potential mould problems.
2. Temperature variations in the same body of grain that exceed 10° C. Variations in temperature or moisture lend themselves to development of potential danger zones.
3. The appearance of water vapour or mist during cold weather. This is an indicator that warm moisture is emanating from the grain mass and is a symptom that some part of the grain is out of condition.
4. During the winter months, look for melting snow on the granary roof. This is a good indicator that excessive heat is present within the grain mass, which requires immediate attention.
5. The presence of insects found by chance, or with the use of grain probes.
6. Increases in insect populations over time in traps set for specific time periods.
7. Changes in temperature over periodic measurements using thermometers with accompanying electronic monitors.
Time of monitoring: When grain is first placed into storage bins, it will probably require more vigilant monitoring. Twice weekly or more frequent examinations may be necessary. Once the grain has stabilized, the grain can be monitored once a month, if the temperature of the grain mass remains above 10° C. When the grain mass is cooled to less than 10° C, monitoring efforts can be reduced significantly. Remember, small problems are indicators that potential larger problems may be just ahead. Watch for signs such as: unnatural musty odours; visible vapour mists; significant differences in temperature within the grain mass; and snow melting off the bin roof faster than other unheated bins. Keep in mind that the longer the grain is in storage, there is a greater chance for infestations to develop
Lucia, M. D., & Assennato, D. (1994). Agricultural engineering in development—post-harvest operations and management of foodgrains. InFAO Agricultural Services Bulletin. Food and Agricultural Organization of the United Nations
Kim, S. S., Phyu, M. R., Kim, J. M., & Lee, S. H. (2003). Authentication of rice using near infrared reXectance spectroscopy. Cereal Chemistry, 80(3), 346–349.
Pearson, T. C., Brabec, D. L., & Schwartz, C. R. (2003). Automated detection of internal insect infestations in whole wheat kernels using a PERTEN SKCS 4100. Applied Engineering in Agriculture, 19(6), 727– 733.
S. Neethirajan, C. Karunakaran D.S. Jayas and N.D.G. White (2007) Detection techniques for stored-product insects in grain,. Food Control, 18, 157–162.
CN Mishra, R P Meena and Satish Kumar