Fields et al. (2020) provide photographs and illustrations many different types of insect monitoring equipment. Hagstrum and Subramanyam (2006) Fundamentals of Stored Product Entomology reviewed sampling plans developed between 1985 and 2004 for bulk storage, processing, transportation, and marketing facilities. They discuss the relationship between variance and mean insect density which is widely used to calculate the number of samples needed to estimate the mean with a given accuracy and to develop sequential sampling plans. Sequential sampling plans are cost effective, because sampling stops when the cumulative number of insects or number of samples or traps with insects exceed a control required economic threshold (ET), is less than a control is unnecessary threshold or exceeds 30 or more samples. If a decision is not reached with 30 or more samples, it is probably best to sample again later rather than to continue sampling. Sequential sampling plans have been developed for 12 species of stored product insects and one mite species, some in the field prior to harvest. Stop lines for sequential sampling plans can be derived from the parameters of Taylor’s power law (Green 1970), Taylor’s power law has been fit for many additional species of stored product insects and could be used to develop sequential sampling plans for many more species. Naranjo and Hutchison (1997) provide a resampling program to validate sequential sampling plans. Sequential sampling plans are well suited to sampling along a transect in a flat storage or taking samples from the grain stream as grain is moved. When sampling a grain bin, a representative sample can be taken and then the separation of insects from grain plus identifying and counting the insects (often the most costly part of sampling) can be stopped as soon as a decision is reached.
The relationship between variance and mean is curvilinear and consistent between insect species and commodities (Hagstrum et al. 1997). A linear approximation of the curve can be used when data are collected for insect densities ranging over five orders of magnitude (0.1 to 1,000) is used to fit the curve. Otherwise, the slope varies with the range of insect densities considered. The linear approximation of this generic variance-mean equation may provide a sequential sampling plan for many species of stored product insects including foreign grain beetle, rusty grain beetle, saw-toothed grain beetle on grain, lesser grain borer, red flour beetle and hairy fungus beetle.
The random distribution of insects among sampling units explains the probability of insect detection and the relationship between variance and mean insect density. As the first insects arrive, the number of sampling units with one insect increases logarithmically. The fraction of sampling units with one insect determines how fast the variance increases. At some insect densities, a sampling unit will eventually have more than one insect. At this point, the variance will begin to increase more rapidly as the number of sampling units with more than one insect begins to increase logarithmically. In many studies, as a result of these relationships, aggregation appears to increase as insect density increases.
Accurate estimation of insect density often requires more sampling than can be justified economically. However, determining whether a pest population is near the density at which economic losses are likely to occur generally is more practical using a sequential sampling plan. Economic thresholds have been determined for 14 stored product pest species that infest raw commodity storages, processing plants, or retail businesses. Most of the following cited papers were not included in Hagstrum and Subramanyam (2006) Fundamentals of Stored Product Entomology. Most were published more recently than this book.
Historically, cables with thermocouples have been used to monitor for hot spots produced by insects or microbial populations in grain bins and more recently CO2 detectors were shown to detect hot spots earlier (Ileleji 2006). Remote, automatic monitoring of stored product insect populations have been demonstrated with bioacoustics detection (Banga et al. 2020, Hagstrum et al. 1991, 1996, Han 2010), camera scanning surfaces (Adler et al. 2018, Štefcová et al. 2014, Wang et al. 2018), insect discharge recorder trap (Takikawa et al. 2015), electronic probe trap and variations (Bonjour and Phillips 2003, Eliopoulos et al. 2018, Flinn et al. 2009, Ho et al. 1997, Toews et al. 2003, Wang et al. 2018,Yao et al. 1999) and SightTraps and variations (Burks et al. 2022a,b, Cabacos and Crépon 2022, Estabrook, Ethan 2020, Feston et al. 2022, Feuerbach et al 2023, Mueller 2019, Saradopoulos et al. 2023, Wang et al. 2018). Kaushik and Singhai (2018) reviewed sensing technologies available for automating the monitoring of insect infestations in stored grain. Research on acoustic detection of insects was reviewed by Mankin et al. 2011 and Mankin et al. 2021 expanded this review through the next decade. Acarus siro (Ridgeway et al. 2002), Cryptolestes ferrugineus (Wu et al. 2013), Ephestia kuehniella (Nouri et al. 2019), Rhyzopertha dominica (Mishra et al. 2018) and Tribolium castaneum (Wu et al. 2013, Xu et al. 2017) have been detected using electronic nose.
Sampling Plans
Amoah, Barbara, M. W. Schilling and Thomas W. Phillips. 2016. Monitoring Tyrophagus putrescentiae (Acari: Acaridae) with Traps in Dry-Cured Ham Aging Rooms. Environmental entomology 45(4): 1029-1039.
Alyousuf, A., R. A. Abood, and M. M. Alderawii. 2021. Dispersion and Binomial Sequential Sampling Plan for Lesser Date Moth Batrachedra amydraula (Lepidoptera: Batrachedridae) Infesting Date Palm Plantations. In Proceedings of the 1st Inter-national Electronic Conference on Entomology, pp. 1-15. Action thresholds of 0.15, 0.25, and 0.35 proportions of spikelets with at least three infested fruit
Caliboso, F. M. 1990. Corn weevil, Sitophilus zeamais motsch (Coleoptera: Curculionidae): a population model. PhD diss., Faculty of the Graduate School, University of the Philippines at Los Baños, Los Baños
Carvalho, Maria Otília, Alexandra Faro, and Bhadriraju Subramanyam. 2013. Insect population distribution and density estimates in a large rice mill in Portugal–A pilot study. Journal of stored products research 52: 48-56.
Carvalho, Maria Otilia, Laura Monteiro Torres, and António Mexia. 2004. Sequential Sampling Plans for Making Management Decisions about Lasioderma serricorne (F.) in Stored Tobacco Using Pheromone Traps. IOBC/Wprs Bulletin 27(9): 77–84.
Carvalho, M., J. de Carvalho, L. Torres, and A. Mexia. 2006. Developing sequential sampling plans for classifying Lasioderma serricorne (F.) (Coleoptera, Anobiidae) status in a cigarette factory. J. Stored Prod. Res. 42: 42-50.
Carvalho, M. O., A. Mexia and L. M. Torres. 2007. Sequential sampling plans for classifying Lasioderma serricorne (F) (Coleoptera : Anobiidae) status in a cigarette factory on the Cape Verde islands. Journal African Entomology 15: 37-44.
Carvalho, M.O., Faro, A. and Subramanyam, B. 2013. Insect population distribution and density estimates in a large rice mill in Portugal – A pilot study. J. Stored Prod. Res. 52: 48–56.
Carvalho, Maria Otilia 2016. Developing and Validating Sequential Sampling Plans for Integrated Pest Management on Stored Products. Advanced Techniques in Biology & Medicine 4: 183. doi: 10.4172/2379-1764.1000183
Fields, Paul, Fuji Jian and Dianxuan Wang 2020. Advances in insect pest management in postharvest storage of cereals: detection and monitoring. p. 199-230. In Dirk E. Maier editor, Advances in postharvest management of cereals and grains. Burleigh Dodds Science Publishing Limited
Gilboa, S., and H. Podoler. 1995. Presence absence sequential sampling for potato tuberworm (Lepidoptera, Gelechiidae) on processing tomatoes – selection of sample sites according to predictable seasonal trends. Journal of Economic Entomology 88(5): 1332–1336.
Green, R. H. 1970. On fixed precision sequential sampling. Res. Population Ecolology (Kyoto) 12: 249–251.
Hagstrum, DW, B. Subramanyam, and PW Flinn. 1997. Nonlinearity of a Generic Variance-Mean Equation for Stored-Grain Insect Sampling Data. Environmental Entomology 26(6): 1213–1223.
Jansson, R. K. and R. McSorley. 1990. Sampling Plans for the Sweetpotato Weevil (Coleoptera: Curculionidae) on Sweet Potato in Southern Florida. J. Econ. Entomol. 83: 1901-1906.
Jian, F., R. Larson, D. S. Jayas and N. D. G. White. 2011. Evaluation of sampling units and sampling plans for adults of Cryptolestes ferrugineus (Coleoptea: Laemophloeidae) in stored wheat under different temperatures, moisture contents, and adult densities. Journal of Stored Products Research 47(4): 334-340.
Jian, F., D. S. Jayas, and N. D. G. White. 2014. How many kilograms of grain per sample unit is big enough? Part I – comparison of insect detection and density estimation between manual probe sampling and Insector® system. Journal of Stored Products Research 56: 60-66.
Jian, F., D. S. Jayas, and N. D. G. White. 2014. How many kilograms of grain per sample unit is big enough? Part II – simulation of sampling from grain mass with different insect densities and distribution patterns. Journal of Stored Products Research 56: 67-80.
Jung, Jae-Min, Dae-hyeon Byeon, Eunji Kim, Hye-Min Byun, Jaekook Park, Jihoon Kim, Jongmin Bae et al. 2020. Sequential sampling method for monitoring potato tuber moths (Phthorimaea operculella) in potato fields. Korean Journal of Agricultural Science 47(3): 615-624.
Latifian, Masoud, and Bahar Rad. 2022. Sequential sampling pattern of important date storage pests based on the spectroscopic method. International Journal of Tropical Insect Science 42(5): 3373-3384. sawtoothed weevil, Oryzaephilus surinamensis L., Indian moth, Plodia interpunctella Hübner and flour moth, Ephestia kuheniella Zeller
Meikle, W. G., Markham, R. H., Holst, N., Djomamou, B., Schneider, H., and Vowotor, K. A. 1998. Distribution and sampling of Prostephanus truncatus (Coleoptera: Bostrichidae) and Sitophilus zeamais (Coleoptera: Curculionidae) in maize stores in Benin. J. Econ. Entomol. 91: 1366-1374.
Meikle, WG, N. Holst, P. Degbey, and R. Oussou 2000. Evaluation of Sequential Sampling Plans for the Larger Grain Borer (Coleoptera : Bostrichidae) and the Maize Weevil (Coleoptera : Curculionidae) and of Visual Grain Assessment in West Africa. Journal of Economic Entomology 93(6): 1822–1831.
Nam, Y.W., Y.S. Chun, and M.I. Ryoo 2009. Developing Sequential Sampling Plans for Evaluating Maize Weevil and Indian Meal Moth Density in Rice Warehouse. Kor. J. Appl. Entomol. 48(1): 45–51.
Nansen, Christian, William G. Meikle, James Campbell, Thomas W. Phillips, and Bhadriraju Subramanyam. 2008. A binomial and species-independent approach to trap capture analysis of flying insects. Journal of economic entomology 101(6): 1719-1728. Plodia interpunctella
Naranjo, S.E. and Hutchison, W.D. 1997. Validation of arthropod sampling plans using a resampling approach: software and analysis. Amer. Entomol. 43: 48–57.
Opit, G.P., Throne, J.E. and Flinn, P.W. 2009. Sampling Plans for the Psocids Liposcelis entomophila and Liposcelis decolor (Psocoptera: Liposcelididae) in Steel Bins Containing Wheat. Journal of Economic Entomology 102: 1714-1722.
Park, J. J. and T. M. Perring. 2010. Development of a Binomial Sampling Plan for the Carob Moth (Lepidoptera: Pyralidae), a Pest of California Dates. J. Econ. Entomol. 103: 1474-1482.
Pulakkatu-Thodi, Ishakh, Rosemary Gutierrez-Coarite, and Mark G. Wright. 2018. Dispersion and optimization of sequential sampling plans for coffee berry borer (Coleoptera: Curculionidae) infestations in Hawaii. Environmental entomology 47(5): 1306-1313.
Subramanyam, B., DW Hagstrum, RL Meagher, EC Burkness, WD Hutchison, and SE Naranjo. 1997. Development and Evaluation of Sequential Sampling Plans for Cryptolestes ferrugineus (Stephens) (Coleoptera: Cucujidae) Infesting Farm-Stored Wheat. Journal of Stored Products Research 33 (4): 321–329.
Toews, M., B. Subramanyam, and R. Roesli. 2003. Development and Validation of Sequential Sampling Plans for Sitophilus Species Associated with Pet Specialty Stores. p. 115–120. Credland, P.F.; Armitage, D.M.; Bell, C.H.; Cogan, P.M.; Highley, E. (eds.), Proceedings of the 8th International Working Conference on Stored Product Protection, 22-26 July 2002, York, UK. CAB International,Wallingford, United Kingdom
Wakefield, M., Dunn, J. 2005. Effectiveness of the BT mite trap for detecting the storage mite pests, Acarus siro, Lepidoglyphus destructor and Tyrophagus longior. Experimental and Applied Acarology 35: 17-28.
Yaghobi, Saeed, Ali Rajabpour, and Nooshin Zandi-Sohani. 2020. Seasonal Population Dynamics, Sampling Distribution, and Fixed-Precision Sequential Sampling of Spectrobates ceratoniae (Lepidoptera: Pyralidae) in Pomegranate Orchards. Journal of Economic Entomology 113 (3): 1513–1518.
Remote, automatic monitoring for insects
Adler, C., Bottger, G., Hentschel, C., Hopfner, D., Große, K., Kern, P., and Zorn, J. 2018. Star Wars in food stores – automated detection, determination and laser elimination of insect pests. p. 973–975. In Proceedings of the 12th International Working Conference on Stored Product Protection, Berlin, Germany, October 7-11, 2018
Banga, K.S.; Kotwaliwale, N.; Mohapatra, D.; Giri, S.K.; Bargale, P.C. 2020. Assessment of bruchids density through bioacoustics detection and artificial neural network (ANN) in bulk stored chickpea and green gram. J. Stored Prod. Res. 88, 101667.
Bonjour, E. L. and Phillips, T. W. 2003.Comparing insect captures in the “StorMax Insector” and other probe traps. P. 238-240. Advances in stored product protection. Proceedings of the 8th International Working Conference on Stored Product Protection, York, UK, 22-26 July 2002
Burks, C.S., 2022a. Comparison of navel orangeworm adults detected with optical sensors and captured with conventional sticky traps. AgriEngineering, 4(2): 523-532.
Burks, Charles S., Foster S. Hengst, Houston Wilson, and Jacob A. Wenger. 2022b. Diel Periodicity in Males of the Navel Orangeworm (Lepidoptera: Pyralidae) as Revealed by Automated Camera Traps. Journal of Insect Science 22(5): 11.
Cabacos, Marine and Katell Crépon 2022. Connected monitoring of beetles during grain storage to prevent proliferation. 13th Conference of the IOBC-WPRS Working Group on the “Integrated Protection of Stored Products (IPSP)”, Barcelona, Spain, IOBC-WPRS Bulletin 159, 34-40.
Eliopoulos P, Tatlas NA, Rigakis I, Potamitis I 2018. A “smart” trap device for detection of crawling insects and other arthropods in urban environments. Electronics 7(9):161.
Estabrook, Ethan 2020. SightTraps – A year in review. Fumigants & Pheromones 163: 1-3.
Feston, James, Samantha Kiever, Pat Kelley, and Ethan Estabrook 2022. Advances in remote monitoring for stored product pests. 13th Conference of the IOBC-WPRS Working Group on the “Integrated Protection of Stored Products (IPSP)”, Barcelona, Spain, IOBC-WPRS Bulletin 159, 6-11.
Feuerbach, Nadine, Katja Börgermann, Dieter Heider, Frank Hertel, Mareike Polzer, and Bernd Hommel. 2023. Netzwerk für den Wissenstransfer und die Implementierung der Leitlinien Integrierter Pflanzenschutz im Sektor Vorratsschutz (Verbundvorhaben) (Network for the transfer of knowledge and the implementation of the guidelines for integrated plant protection in the sector of stored product protection). https://www.wains.info/en/products/traptice-insect/
Flinn, P. W.，Opit, G. P. and J. E. Throne, 2009. Predicting Stored Grain Insect Population Densities Using an Electronic Probe Trap. Journal of Economic Entomology 102:1696-1704.
Hagstrum, DW, KW Vick, and PW Flinn. 1991. Automated Acoustical Monitoring of Tribolium castaneum (Coleoptera, Tenebrionidae) Populations in Stored Wheat. Journal of Economic Entomology 84(5): 1604–1608.
Hagstrum, D.W.; Flinn, P.W.; Shuman, D. 1996. Automated monitoring using acoustical sensors for insects in farm-stored wheat. J. Econ. Entomol. 89: 211–217.
Han Antai, He Yong, Li Jianfeng, Chen Zhiqiang, Sun Yanwei. 2010. Design of acoustic signal acquisition system of stored grain pests based on wireless sensor networks. Transactions of the CSAE 26(6): 181-187. (Tribolium castaneum)
Ho, S. H., L. Fan, and K. S. Boon. 1997. Development of a PC-based automatic monitoring system for Tribolium castaneum (Herbst)(Coleoptera: Tenebrionidae) in a rice warehouse. Journal of Stored Products Research 33(4): 277-281.
Ileleji, K.E., Maier, D.E., Bhat, C., Woloshuk, C.P. 2006. Detection of a developing hot spot in stored corn with a CO2 sensor. Appl. Eng. Agric. 22: 275–289.
Kaushik, Rekha, and Jyoti Singhai. 2018. Sensing Technologies Used for Monitoring and Detecting Insect Infestation in Stored Grain. International Journal of Engineering and Technology (UAE) 7: 169–173.
Mankin, R. W., D. W. Hagstrum, M. T. Smith, A. L. Roda, and M. T. K. Kairo. 2011. Perspective and promise: a century of insect acoustic detection and monitoring. Amer. Entomol. 57: 30-44.
Mankin, Richard, David Hagstrum, Min Guo, Panagiotis Eliopoulos, and Anastasia Njoroge. 2021. Automated Applications of Acoustics for Stored Product Insect Detection, Monitoring, and Management. Insects 12(3), 259
Mishra, Gayatri, Shubhangi Srivastava, Brajesh K. Panda, and H. N. Mishra. 2018. Sensor Array Optimization and Determination of Rhyzopertha dominica Infestation in Wheat Using Hybrid Neuro-Fuzzy-Assisted Electronic Nose Analysis. Analytical Methods 10(47): 5687–5695.
Mueller, Tom 2019. Fighting an uphill battle with Indian Meal Moth. Fumigants & Pheromones 156: 1-2.
Nouri, Behzad, Kobra Fotouhi, Seyed Saeid Mohtasebi, Amin Nasiri, and Seyed Hosein Goldansaaz. 2019. Detection of Different Densities of Ephestia kuehniella Pest on White Flour at Different Larvae Instar by an Electronic Nose System. J. Stored Prod. Res. 84, 101522
Ridgway, Christopher, Chambers. John, and Elena Portero-Larragueta Olivia Prosser. 1999. Detection of Mite Infestation in Wheat by Electronic Nose with Transient Flow Sampling. Journal of the Science of Food and Agriculture 79(15): 2067–2074. Acarus siro
Saradopoulos, Ioannis, Ilyas Potamitis, Antonios I. Konstantaras, Panagiotis Eliopoulos, Stavros Ntalampiras, and Iraklis Rigakis. 2023. Image-Based Insect Counting Embedded in E-Traps That Learn without Manual Image Annotation and Self-Dispose Captured Insects. Information 14(5), 267. (Plodia interpunctella)
Štefcová, P., M. Pech, M. Kotyk, J. Valach, K. Juliš, and J. Frankl. 2014. Pest Management in Museum Collections and Storage Areas (New Approach—Online Sensors for Pest Detection). Journal of Environmental Science and Engineering A 3: 163–176.
Takikawa, Y., Y. Matsuda, T. Nonomura, K. Kakutani, S. Kusakari, and H. Toyoda. 2015. Development of an Electrostatic Trap with an Insect Discharge Recorder for Multiple Real-Time Monitoring of Pests Prowling in a Warehouse. Int. J. Adv. Agric. Res. 3: 55–63. Lasioderma serricorne, Sitophilus oryzae, Tribolium castaneum
Toews, MD, TW Phillips, and D. Shuman. 2003. Electronic and Manual Monitoring of Cryptolestes ferrugineus (Coleoptera : Laemophloeidae) in Stored Wheat. Journal of Stored Products Research 39(5): 541–54.
Wang, D., C. Bai, H. Li, X. Guo, and J. Wang. 2018. Remote Monitoring of Stored Grain Insect Pests. p. 239–245. In Proceedings of the12th International Working Conference on Stored Product Protection (IWCSPP), October 7-11, 2018, Berlin, Germany (Cryptolestes ferrugineus, Liposcelis bostrychophila, Plodia interpunctella, Sitophlius zeamais)
Wu, J., D. S. Jayas, Q. Zhang, N. D. G. White, and R. K. York. 2013. Feasibility of the Application of Electronic Nose Technology to Detect Insect Infestation in Wheat. Canadian Biosystems Engineering 55: 3.1-3.9. Cryptolestes ferrugineus, Tribolium castaneum
Xu, Sai, Zhiyan Zhou, Keliang Li, Sierra Jamir, and Xiwen Luo. 2017. Recognition of the Duration and Prediction of Insect Prevalence of Stored Rough Rice Infested by the Red Flour Beetle (Tribolium castaneum Herbst) Using an Electronic Nose. Sensors 17(4), 688
Yao, W., Fu, J. and Zhang, Y. 1999. The sensor-based probe traps for monitoring stored product insects. p. 1437–1445. In Proceedings of the 7th International Working Conference on Stored-Product Protection, 1998. Sichuan Publishing House of Science and Technology, Beijing, China. Chengdu, China Sitophilus zeamais, Sitophilus oryzae, 0ryzaephilus surinamensis, Rhyzopertha dominica, Tribolium castaneum, Lathehcus oryzae , Cryptolestes ferrugineus
Economic Thresholds
Abdullahi, G., Muhamad, R., Dzolkhifli, O. and Sinniah, U.R. 2018. Damage potential of Tribolium castaneum (Herbst) (Coleoptera: Tenebrionidae) on cocoa beans: effect of initial adult population density and post infestation storage time. J. Stored Prod. Res. 75:1-9. Malaysian cocoa board economic threshold of insect free and <2.5% insect damaged or beans not germinating per 100 g.
Amoah, Barbara Amoh. 2016. Monitoring populations of the ham mite, Tyrophagus putrescentiae (Schrank) (Acari: Acaridae): research on traps, orientation behavior, and sampling techniques. PhD dissertation, Department of Entomology, Kansas State University
Amoah, Barbara, David Hagstrum, Bhadriraju Subramanyam, James F. Campbell, M. Wes Schilling and Thomas W. Phillips. 2017. Sampling methods to detect and estimate populations of Tyrophagus putrescentiae (Schrank) (Sarcoptiformes: Acaridae) infesting dry-cured hams. J. Stored Prod. Res. 73: 98-108.
Arthur, F.H., Campbell, J.F. and Toews, M.D. 2013. Distribution, abundance, and seasonal patterns of Plodia interpunctella (Hübner) in a commercial food storage facility. J. Stored Prod. Res. 53: 7–14.
Baier, A.H., and Webster, B.D. 1992. Control of Acanthoscelides obtectus Say (Coleoptera: Bruchidae) in Phaseolus vulgaris L. seed stored on small farms. I. Evaluation of damage. J. Stored Prod. Res. 28(4): 289–293.
Caliboso, F. M. 1990. Corn weevil, Sitophilus zeamais Motsch (Coleoptera: Curculionidae): a population model. MS thesis, Faculty of the Graduate School, University of the Philippines at Los Baños, Los Baños. Control action should be initiated within 28 to 41 days of storage or when three to four insects per two kg of corn or 3.5 to 5.3% damaged kernels are encountered. devise a sequential sampling plan for quick assessment of damage level.
Campbell, J.F., Toews M.D., Arthur F.H., Arbogast R.T. 2010. Long-term monitoring of Tribolium castaneum populations in two flour mills: rebound after fumigation. J. Econ. Entomol. 103(3): 1002–1011.
Carvalho, M.O., Passos de Carvalho, J., Torres, L.M.and Mexia, A. 2006. Developing sequential sampling plans for classifying Lasioderma serricorne (F.) (Coleoptera: Anobiidae) status in a cigarette factory. J. Stored Prod. Res. 42 (1): 42–50.
Carvalho, M.O., Faro, A. and Subramanyam, B. 2013. Insect population distribution and density estimates in a large rice mill in Portugal – A pilot study. J. Stored Prod. Res. 52: 48–56.
Chen, P, Zhang, H, Lu, Q. and Zheng, L. 2008. Survey and analysis of economic thresholds for insect pest control in grain storage in the Fujian area of China. See Ref. 57, pp. 493–97 In Guo DL, Navarro S, Jian Y, Cheng T, Zuxun J, et al., eds. 2008. Proc. Int. Conf. Control. Atmos. Fumigation Stored Prod. 8th, Chengdu, Sept. 21–26. Chengdu, China: Sichuan Publ. Group
Chen, P., H. Zhang, Q. Lu and L. Zheng. 2010. Survey and analysis of economic thresholds for stored insect pest control in Fujian area of China. Grain Storage 39: 10-13.
Compton, J.A.F., Floyd, S., Magrath, P.A., Addo, S., Gbedevi, S.R., Agbo, B., Bokor, G., Amekupe, S., Motey, Z., Penni, H. and Kumi, S. 1998. Involving grain traders in determining the effect of postharvest insect damage on the price of maize in African markets. Crop Prot. 17(6): 483–489.
Espino, L.; Greer, C.A.; Mutters, R.; Thompson, J.F. 2014 Survey of rice storage facilities identifies research and education needs. Calif. Agric. 68: 38–46. ETs are used by most rice storage facilities in California.
Fernandes, F. L., M. C. Picanço, S. O. Campos, C. S. Bastos, M. Chediak, R.N. Guedes, and R. S. Silva. 2011. Economic injury level for the coffee berry borer (Coleoptera: Curculionidae: Scolytinae) using attractive traps in Brazilian coffee fields. J. Econ. Entomol. 104: 1909–1917.
Flinn, P.W., Hagstrum, D.W., Reed, C.R. and Phillips, T.W. 2007. Stored Grain Advisor Pro: Decision support system for insect management in commercial grain elevators. J. Stored Prod. Res. 43(4): 375–383.
Hagstrum DW, Flinn PW. 2014. Modern stored-product insect pest management. J. Plant Prot. Res. 54: 205–210. (Review of economic thresholds for nine species)
Haouel-Hamdi, Soumaya, Faten Titouhi, Emna Boushih, Mohamed Zied Dhraief, Moez Amri and Jouda Mediouni-Ben Jemâa. 2017. Population Demographic and Reproductive Parameters of the Cowpea Seed Beetle Callosobruchus maculatus Infesting Stored Lentil and Chickpea Commodities. Tunisian Journal of Plant Protection 12(1): 67-81.
Higbee, B. S., and J. P. Siegel. 2009. New Navel Orangeworm Sanitation Standards Could Reduce Almond Damage. California Agriculture 63: 24–28.
Hodges, R.J., Smith, M., Madden, A., Russell, D., Gudrups, I. and Halid, H. 1997. Development of a decision support system for the fumigation of milled-rice bag-stacks in the tropics. p. 425–434. In: Proc. Int. Conference on Controlled Atmosphere and Fumigation in Stored Products (E.J. Donahaye, S. Navarro, A. Varnava eds. Cyprus, April 1996. Printco Ltd., Nicosia, Cyprus.
Jung, Jae-Min, Dae-hyeon Byeon, Eunji Kim, Hye-Min Byun, Jaekook Park, Jihoon Kim, Jongmin Bae et al. 2020. Sequential sampling method for monitoring potato tuber moths (Phthorimaea operculella) in potato fields. Korean Journal of Agricultural Science 47(3): 615-624. (15 – 20 moths per trap per night is the recommended economic threshold)
Luo F, Li Z, Yu J, and Lu X. 2008. Application of economic threshold level in stored grain fumigation for controlling of pests. See Ref. 57, pp. 530–532. In Guo DL, Navarro S, Jian Y, Cheng T, Zuxun J, et al., eds. 2008. Proc. Int. Conf. Control. Atmos. Fumigation Stored Prod. 8th, Chengdu, Sept. 21–26. Chengdu, China: Sichuan Publ. Group
Meikle, W.G., Holst, N., Degbey, P. and Oussou, B. 2000. Evaluation of sequential sampling plans for the larger grain borer (Coleoptera: Bostrichidae) and the maize weevil (Coleoptera: Curculionidae) and of visual grain assessment in West Africa. J. Econ. Entomol. 93 (6): 1822–1831.
Nam, Y.W., Chun, Y.S. and Ryoo, M.I. 2009. Developing sequential sampling plans for evaluating maize weevil and Indian meal moth density in rice warehouse. Kor. J. Appl. Entomol. 48(1): 45-51. The action thresholds for both insect pests were estimated to be 5 insects per kg. Managers can make decisions using only 20 probe with a minimum risk of incorrect assessment.
Nansen, C., and W. G. Meikle. 2011. The economic injury level and action threshold in stored-product systems, doi: 10.2212/spr.2011.3.3 ed.
Sabio, G. C., F. M. Caliboso, R. L. Tiongson, and E. A. Benigno. 1984. Establishment of economic threshold levels in stored grains, and preliminary trial of methacrifos as a stack spray, pp. 65-93. In R. L. Semple and A. S. Frio (eds.), Health and Ecology in Grains Post Harvest Technology. Proceedings of the 7th ASEAN Technical Seminar on Grain Post-Harvest Technology, 21-24 August 1984, Kuala Lumpur. ASEAN Crops Post-Harvest Programme.
Santos AK, Faroni LRA, Guedes RN, dos Santos JP, Rozazdo AF. 2002. Nıvel de dano economico de Sitophilus zeamais (M.) em trigo armazenado. Rev. Bras. Eng. Agrıc. Ambient. 6(2): 273–279.
Subramanyam, B., Hagstrum, D.W., Meagher, R.L., Burkness, E.C., Hutchinson, W.D. and Naranjo, S.E. 1997. Development and evaluation of sequential sampling plans for Cryptolestes ferrugineus (Stephens) (Coleoptera: Cucujidae) infesting farm stored wheat. J. Stored Prod. Res. 33 (4): 321–329.
Toews, M., Subramanyam, Bh. and Roesli, R. 2003. Development and validation of sequential sampling plans for Sitophilus species associated with pet specialty stores. p. 115–120. In: Advances in Stored Product Protection (P.F. Credland, D.M. Armitage, C.H. Bell, P.M. Cogan, E. Highley, eds.). Proc. 8th Int. Working Conference on Stored Product Protection, York, UK, 22–26 July 2002. CABI International, Wallingford, UK.
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Wegbe, K., C. Cilas, B. Decazy, C. Alauzet, and B. Dufour. 2003. Estimation of production losses caused by the coffee berry borer (Coleoptera: Scolytidae) and calculation of an economic damage threshold in Togolese coffee plots. J. Econ. Entomol. 96: 1473–1478.
Zakladnoi GA. 1991. Modern technologies for stored-grain protection against insect pests in the USSR. p. 1983–1990. In Proc. Intern.Work. Conf. Stored-Prod. Prot. 5th, Bordeaux, Sept. 9–14, Bordeaux, France:M´edoc
Other Sampling and Detection Studies
Armitage DA. 2003. Grain sampling methods to achieve consumer confidence and food safety. Home-Grown Cereal Authority Research Review (UK) No. 50, 21 p.
Brabec, D., Pearson, T., Flinn, P., Katzke, D., 2010. Detection of internal insects in using a conductive roller mill and estimation of insect fragments in the resulting flour. J. Stored Prod. Res. 46, 180-185.
Buckman, K.A., Campbell, J.F. 2013. How varying pest and trap densities affect Tribolium castaneum capture in pheromone traps. Entomologia Experimentalis et Applicata 3: 404-412.
Cogan, P.M., Stubbs, M.R. and Wakefield, M.E. 1985. Detection of insects in large bulks of grain. M.A.F.F.,A.D.A.S. Slough Lab. Rep. 14. 22 p.
Elmouttie, D., Kiermeier, A. and Hamilton, G. 2010. Improving detection probabilities in stored grain. Pest Management Science 66: 1280-1286.
Elmouttie, David, Hammond, Nicole Elana and Hamilton, Grant S. 2013. A review of current statistical methodologies for in storage sampling and surveillance in the grains industry. Bulletin of Entomological Research, 103(02), pp. 140-147.
Elmouttie, David, Paul Flinn, Andreas Kiermeier, Bhadriraju Subramanyam, David Hagstrum and Grant Hamilton. 2013. Sampling stored-product insect pests: a comparison of four statistical sampling models for probability of pest detection. Pest Manag. Sci. 69: 1073–1079.
Fleurat-Lessard, Francis 2011. Monitoring insect pest populations in grain storage: the European context. Stewart Postharvest Review doi: 10.2212/spr.2011.3.4
Flinn, P.W., Opit, G.P. and Throne, J.E. 2009. Predicting stored grain insect population densities using an electronic probe trap. Journal of Economic Entomology 102: 1696-1704.
Hamilton, G., and D. Elmouttie. 2011. Insect distributions and sampling protocols for stored commodities. Stewart Postharvest Review doi: 10.2212/spr.2011.3.2.
Jian, F., R. Larson, D. S. Jayas, and N. D. G. White. 2011. Three-dimensional spatial distribution of adults of Cryptolestes ferrugineus (Coleoptera: Laemophloeidae) in stored wheat under different temperatures, moisture contents, and adult densities. J. Stored Prod. Res. 47:293-305.
Jian, F., R. Larson, D. S. Jayas and N. D. G. White. 2012. Three dimensional temporal and spatial distribution of adult Oryzaephilus surinamensis and Sitophilus oryzae in stored wheat under different temperatures, moisture contents, and adult densities. J. Stored Prod. Res. 49: 155-165.
Jian, Fuji, Ron Larson, Digvir S. Jayas and Noel D. G. White. 2012. Three-Dimensional Temporal and Spatial Distribution of Adult Rhyzopertha dominica in Stored Wheat and Corn Under Different Temperatures, Moisture Contents, and Adult Densities. J. Econ. Entomol. 105(4): 1194-1204.
Jian, F., D. S. Jayas, N. D. G. White, P. G. Fields, and N. Howe. 2014. An evaluation of insect expulsion from wheat samples by microwave treatment for disinfestation. Biosyst. Eng. 130:1-12.
Jian, F., D. S. Jayas, N. D. G. White and P. G. Fields. 2014. Insect detection and density estimation in stored grain bins: is it a needle in a haystack or an elephant in a room?, p. 230-245. In F. H. Arthur, R. Kengkanpanich, W. Chayaprasert and D. Suthisut (eds.), Proceedings of the 11th International Working Conference on Stored Product Protection, 24-28 November 2014, Chiang Mai, Thailand.
Jian, F., Jayas, D.S., Fields, P.G. and White, N.D.G. 2015. A new method to rapidly detect the rusty grain beetle, Cryptolestes ferrugineus, in stored grain. J. Stored Prod. Res. 63: 1-5.
Jian, Fuji, Sara Doak, Digvir S. Jayas , Paul G. Fields, Noel D.G. White. 2016. Comparison of insect detection efficiency by different detection methods. Journal of Stored Products Research 69: 138-142. (Berlese funnel, shaking grain on a metal sieve, shaking grain on an acrylic device, microwave heating)
Knight, J., R. Wilkin, and J. Rivett. 2004, Grain Sampling and Assessment: Sampling Grain in Lorries. Home-Grown Cereals Authority (HGCA) Project Report, London Project Report 339
Knight, J. D., and R. Wilkin. 2006. Assessment of three commercial automatic grain samplers fitted to front loader buckets.” HGCA Project Report 407, 20 p.
Knight, J. D., and D. R. Wilkin. 2010. Development and validation of on-farm sampling methods for the collection of marketing (quality) samples at harvest. Journal of stored products research 46(4): 221-227.
Krizkova-Kudlikova, I., Hubert, J. 2008. Development of polyclonal antibodies of the detection of Tribolium castaneum contamination in wheat grain. J. Agric. Food Chem. 56: 8035-8040.
Laopongsit, W., Srzednicki, G., Craske, J., 2014. Preliminary study of solid phase micro-extraction (SPME) as a method for detecting insect infestation in wheat grain. J. Stored Prod. Res. 59, 88-95.
Manickavasagan, A., Jayas, D.S. and White, N.D.G. 2008. Thermal imaging to detect infestation by Cryptolestes ferrugineus inside wheat kernels. J. Stored Prod. Res. 44: 186-192.
Minkevich, J.M., Demianyk, C.J., White, N.D.G., Jayas, D.S. and Timlick, B. 2002. A rapid method to detect Cryptolestes ferrugineus (Coleoptera: Cucujidae) larvae in stored grain. Can. J. Plant Sci. 82: 591-597.
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Nansen, C., Meikle, W.G., Campbell, J., Phillips, T.W. and Subramanyan, B. 2008. A binomial and species-independent approach to trap capture analysis of flying insects. Journal of Economic Entomology. 101: 1719-1728.
Neethirajan S., Karunakaran, C., Jayas, D.S. and White, N.D.G. 2007. Detection techniques for stored-product insects in grain. Food Control 18: 157–162.
Obrepalska-Steplowska, A., K. Nowaczyk, M. Holysz, M. Gawlak & J. Nawrot 2008. Molecular techniques for the detection of granary weevil (Sitophilus granarius L.) in wheat and flour. Journal Food Additives & Contaminants: Part A 25(10): 1179-1188.
Pearson, T.C. and Brabec, D.L. 2007. Detection of wheat kernels with hidden insect infestations with an electrically conductive roller mill. Appl. Eng. Agric. 19: 727-733.
Pearson, T.C., Brabec, D.L. and Schwartz, C.R. 2003. Automated detection of internal insects infestations in whole wheat kernels using a Perten SKCS 4100. Appl. Eng. Agric. 19: 727-733.
Reed, J.T., Adams, L.C., Abel, C.A., 2010. Comparison of three insect sampling methods in sweet potato foliage in Mississippi. Journal of Entomological Science 45: 111-128.
Savoldelli, S. 2006. Correlation between Plodia interpunctella Hübner (Lepidoptera: Pyralidae) males captured with a wing trap and the real density of moth’s population. p. 487-491. In Lorini, I., Bacaltchuk, B., Beckel, H., Deckers, D., Sundfeld, E., Biagi, J.P., Santos, J.D., Celaro, J.C., Faroni, L.R.D’A., Bortolini, L.de O.F., Sartori, M.R., Elias, M.C., Guedes, R.N.C., Fonseca, R.G.da, Scussel, V.M. (eds.). Proceedings of the Ninth International Working Conference on Stored Product Protection, 15-18 October 2006, Brazil. Campinas, Sao Paulo, Brazilian Post-Harvest Association – ABRAPOS, Passo Fundo
Singh, C.B., Jayas, D.S., Paliwal, J., White, N.D.G., 2009. Detection of insect-damaged wheat kernels using near-infrared hyperspectral imaging. J. Stored Prod. Res. 45, 151-158.
Stejskal, V., Aulicky, R., Kucerova, Z. and Lukas, J. 2008. Method of sampling and laboratory extraction affects interpretation of grain infestation by storage pests. Journal of Plant Diseases and Protection 115: 129-133.
Thind, B. 2005. A new versatile and robust trap for detection and monitoring of stored product pests in the cereal and allied industries. Experimental and Applied Acarology 35: 1-15.
Toews M.D. and Nansen C. 2011. Chapter 21, Trapping and interpreting captures of stored grain insects. p. 243-261. In: Hagstrum, D.W., Phillips, T.W., Cuperus, G., (Eds.), Stored Product Protection. Manhattan, Kansas, K-state Research and Extension, Manhattan, KS, USA
Wakefield, M. 2006. Storage arthropod pest detection – current status and future directions. p. 371-384. In Lorini, I., Bacaltchuk, B., Beckel, H., Deckers, D., Sunfeld, E., Dos Santos, J.P., Biagi, J.D., Celaro, J.C., Faroni, L.R.D.A., Bortolini, L.O.F., Sartori, M.R., Elias, M.C., Guedes, R.N.C., Da Fonseca, R.G., Scussel, V.M. (eds.) Biology, behavior, and pest detection on stored grain. Proceedings of the Ninth International Working Conference on Stored Product Protection, 15-18 October 2006, Campinas, São Paulo, Brazil
Wilkin, D. R. 1982. Sampling bulk grain. Ministry of Agriculture, Fisheries and Food (MAFF)
Wilkin, D. R. 1982. Detection of infestation in grain. Ministry of Agriculture, Fisheries and Food (MAFF)
Wilkin, D. R. and V. J. Wright. 1984. Sampling bulk grain to check infestation. Slough Laboratory Rpt. No 6569, Ministry of Ag., Fish, and Food, Slough, U.K.
Wilkin, D. R., and B. B. Thind. 1984. Stored product mites detection and loss assessment in animal feed. p. 608-620. In R. B. Mills, V. F. Wright, J. R. Pedersen, W. H. McGaughey, R. W. Beeman, K. J. Kramer, R. D. Speirs and C. L. Storey (eds.), Proceedings of the 3rd International Working Conference on Stored-Product Entomology, 23-28 October, 1983, Manhattan, Kansas. Kansas State University
Wilkin, D. R., Cowe, I. A., Thind, B. B., McNicol and Cuthbertson, D. C. 1986. The detection and measurement of mite infestation in animal feed using near infrared reflectance. Journal of Agricultural Science (Cambridge) 107: 439-448.
Wilkin, D. R. 1990. Detection of insects in bulk grain. Journal of the Kansas Entomological Society 63: 554-558.
Wilkin, D.R., Fleurat-Lessard, F., 1991. The detection of insects in grain using conventional sampling spears. In: Fleurat-Lessard, F., Ducom, P. (Eds.), Proceedings of the Fifth International Working Conference on Stored Product Protection, September 9-14, 1990, Bordeaux, France, pp. 1445-1453.
Wilkin, D.R. 1991. An assessment of methods of sampling bulk grain. HGCA Project Report No. 34. Home Grown Cereals Authority, London.
Wilkin, D. R. 1993. An assessment of practical methods for collecting samples from lorry-loads of grain. Home Grown Cereals Authority (HGCA) Project Report no. 79, 23 p.
Wilkin, D. R., D. Catchpole, and S. Catchpole. 1993. The development of a practical method for removing insects from large samples of grain. Project Report no. 82. Home Grown Cereals Authority, London
Wilkin, D.R., Catchpole, D. and Catchpole, S. 1994. The detection of insects in grain during transit-an assessment of the problem and the developmentof a practical solution. p 463-469. In Highley, E.; Wright, E.J.; Banks, H.J.; Champ, B.R. (Eds.), Stored Product Protection, Proceedings of the 6th International Working Conference on Stored-Product Protection, 17-23 April 1994, Canberra, Australia. CAB International, Wallingford, United Kingdom
Wilkin, D.R. 2003. An alternative approach to assessing pest problems in stored grain. p. 464-467. In: Credland, P.F., Armitage, D.M., Bell, C.H., Cogan, P.M. and Highley, E (Eds.) Proceedings of the 8th International Working Conference on Stored Product Protection, York, July 2002 CABI publishing, Wallingford, UK
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