Detection techniques for stored-product insects in grain

Neethirajan, Suresh; Karunakaran, Chithra; Jayas, Digvir S.; White, N. D. G.

doi:10.1016/j.foodcont.2005.09.008

Cited by 221 publications

(102 citation statements)

References 27 publications

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“…Manual inspection, sieving, cracking-floatation and Berlese funnels are used to detect insects in grain handling facilities. However, these methods are not efficient and are time consuming (Neethirajan et al 2007) with poor accuracy for the developing life stages of pests. Detection of pest infestation in food commodities and in their storage premises is essential to ensure wholesome and acceptable produce for human consumption, for regulatory compliance, for diagnosis of incipient infestation and to ascertain the success of the control measures such as fumigants (Rajendran 1999).…”

Section: Grain Qualitymentioning

confidence: 99%

Measurement techniques and application of electrical properties for nondestructive quality evaluation of foods—a review

et al. 2011

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Non-destructive systems are recent trends for quality evaluation of fruits and vegetables. Information on post-harvest variations in electrical properties is needed to develop new instruments for this purpose. Electrical properties are finding increasing application in agriculture and food processing industries. Knowledge of dielectric properties of foods as a function of moisture content and temperature is essential in the design and control of drying systems. As simple, rapid and non-destructive measuring techniques, dielectric spectroscopy provides information about the dielectric response of materials to electromagnetic field. Electrical properties of agricultural materials have been of interest for many years. The interest in dielectric properties of materials has historically been associated with the design of electrical equipment. This review paper covers theoretical aspects of different electrical properties, their measurement techniques, applications of dielectric properties in agriculture/food processing sector and potential applications of thermal imaging (TI) for quality and safety assessment in food processing. The values of dielectric properties of a number of products including food grains, fruits and vegetables, and meat and meat products are presented in table form. This comprehensive coverage will be useful for academic, scientific and industrial community in treating and applying the facts in developing/testing new processes and products based on electromagnetic energy application.Keywords Electrical properties . Non-destructive . Measuring techniques . Dielectric constant . Loss factor . Thermal imaging technique . Food quality evaluationThe material investigation and moisture measurement using electromagnetic waves in wide spectrum serve for quality control and improvement in many branches like industry, forest and wood-working industry, civil engineering, agriculture, commerce and also foods e.g. for quality evaluation of meat, fruits, coffee etc (Hlavacova 2003; Venkatesh and Raghavan 2004). Non-destructive evaluation of quality based on constituents of fruits and vegetables has been successfully used (Chen et al. 1999;Jha et al. 2001;Kawano 1998). Electrical characteristics of agricultural materials have been of interest for many years (Nelson 2006) and are utilized in many areas of human activities. Techniques for non-destructive determination of quality and related characteristics of agricultural products are helpful to producers, handlers and processors . Permittivity and moisture can be closely correlated when water content is high. Knowledge of dielectric properties in partially frozen material is critical in determining the rates and uniformity of heating in microwave thawing. Electrical properties are important in processing foods with pulsed electric fields, ohmic heating, induction heating, radio frequency, and microwave heating. These properties are also useful in the detection of processing conditions or the quality of foods (Barbosa-Canovas et al. 2006). Considering ...

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Section: Grain Qualitymentioning

confidence: 99%

Measurement techniques and application of electrical properties for nondestructive quality evaluation of foods—a review

et al. 2011

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“…Acoustic methods are available for detecting infestations of internally feeding insects, but commercially marketed instruments (Litzkow et al 1990;Hagstrum et al 1996;Neethirajan et al 2007;Mankin et al 2011;Rohde et al 2013) have been too expensive for general use in small-scale storage facilities in developing countries. However, recent innovations and improvements in the usability of electronic sensing systems suggest it may be possible to develop a low-cost acoustic detection device (e.g., Mankin et al 2010Mankin et al , 2013Dillman et al 2014) incorporating Arduino, Raspberry Pi, or other microcontrollers that could be adopted more widely than previous devices as a tool for insect pest management in maize-and other grain-storage facilities in sub-Saharan Africa.…”

mentioning

confidence: 99%

Acoustic Indicators for Targeted Detection of Stored Product and Urban Insect Pests by Inexpensive Infrared, Acoustic, and Vibrational Detection of Movement

Mankin¹,

Hodges²,

Nagle³

et al. 2010

jnl. econ. entom.

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“…(Tenebrionidae), the grain weevils Sitophilus sp. (Curculionidae), the lesser grain borer Rhyzopertha dominica (F.) (Bostrichidae), the cigarette beetle Lasioderma serricorne (F.) (Anobiidae), and the khapra beetle Trogoderma granarium Everts (Dermestidae) [32][33][34][35].…”

Section: Trap Type #2: the Stored-grain Pitfall Trapmentioning

confidence: 99%

Automated Remote Insect Surveillance at a Global Scale and the Internet of Things

2017

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Abstract:The concept of remote insect surveillance at large spatial scales for many serious insect pests of agricultural and medical importance has been introduced in a series of our papers. We augment typical, low-cost plastic traps for many insect pests with the necessary optoelectronic sensors to guard the entrance of the trap to detect, time-stamp, GPS tag, and-in relevant cases-identify the species of the incoming insect from their wingbeat. For every important crop pest, there are monitoring protocols to be followed to decide when to initiate a treatment procedure before a serious infestation occurs. Monitoring protocols are mainly based on specifically designed insect traps. Traditional insect monitoring suffers in that the scope of such monitoring: is curtailed by its cost, requires intensive labor, is time consuming, and an expert is often needed for sufficient accuracy which can sometimes raise safety issues for humans. These disadvantages reduce the extent to which manual insect monitoring is applied and therefore its accuracy, which finally results in significant crop loss due to damage caused by pests. With the term 'surveillance' we intend to push the monitoring idea to unprecedented levels of information extraction regarding the presence, time-stamping detection events, species identification, and population density of targeted insect pests. Insect counts, as well as environmental parameters that correlate with insects' population development, are wirelessly transmitted to the central monitoring agency in real time and are visualized and streamed to statistical methods to assist enforcement of security control to insect pests. In this work, we emphasize how the traps can be self-organized in networks that collectively report data at local, regional, country, continental, and global scales using the emerging technology of the Internet of Things (IoT). This research is necessarily interdisciplinary and falls at the intersection of entomology, optoelectronic engineering, data-science, and crop science and encompasses the design and implementation of low-cost, low-power technology to help reduce the extent of quantitative and qualitative crop losses by many of the most significant agricultural pests. We argue that smart traps communicating through IoT to report in real-time the level of the pest population from the field straight to a human controlled agency can, in the very near future, have a profound impact on the decision-making process in crop protection and will be disruptive of existing manual practices. In the present study, three cases are investigated: monitoring Rhynchophorus ferrugineus (Olivier) (Coleoptera: Curculionidae) using (a) Picusan and (b) Lindgren trap; and (c) monitoring various stored grain beetle pests using the stored-grain pitfall trap. Our approach is very accurate, reaching 98-99% accuracy on automatic counts compared with real detected numbers of insects in each type of trap.

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Detection techniques for stored-product insects in grain

Cited by 221 publications

References 27 publications

Measurement techniques and application of electrical properties for nondestructive quality evaluation of foods—a review

Measurement techniques and application of electrical properties for nondestructive quality evaluation of foods—a review

Acoustic Indicators for Targeted Detection of Stored Product and Urban Insect Pests by Inexpensive Infrared, Acoustic, and Vibrational Detection of Movement

Automated Remote Insect Surveillance at a Global Scale and the Internet of Things

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