Srivastava et al. 2018; Dasgupta et al. 2015; Neethirajan and Jayas 2009).
Nanosensors based on nanoparticles have been devised to detect moisture content
inside a food package (Pathakoti et al. 2017). Such kind of nanosensor is usually
based upon carbon-coated copper nanoparticles dispersed in a tenside film
(Luechinger et al. 2007). Principally, under humid and moist conditions, swelling
of the polymer matrix results in separation of inter-nanoparticle. These changes
cause sensor strips to reflect or absorb different colors of light that can be monitored
for quick and accurate determination of package moisture levels without invasive
sampling. For instance, Neethirajan et al. (2009) developed grain quality monitoring
nanosensors by using conducting polymer nanoparticles which respond to analytes
and volatiles in the food storage environment and thereby detect the source and the
type of spoilage (Neethirajan et al. 2009). Because of the miniaturization and
requirement of low power, such type of nanosensors can be designed and deployed
into the crevices of grain bulk, where the stored product pests often hide. Jonsson
et al. (1997) developed an e-nose with three different complementary sensors (ten
gas-sensitive metal oxide semiconductor field effect transistors, four tin dioxidebased sensors, and a carbon dioxide sensor) to test wheat samples with different
levels of ergosterol, fungal, and bacterial contamination. In wheat, high degrees of
correlation between artificial neural network predictions and measured ergosterol as
well as fungal and bacterial colony forming units were observed. Campagnoli et al.
(2011) developed electronic nose equipped with metal oxide semiconductor sensors
and used it as a screening tool for the recognition of durum wheat naturally
contaminated by deoxynivalenol. The e-nose was able to detect durum wheat
whole-grain samples naturally contaminated with deoxynivalenol at the concentration level recommended by the European legislation, employing principal component analysis processing and a classifier based on classification and regression trees.
Further, Eifler et al. (2011) showed that the metalloporphyrin-based e-nose can be
used to qualitatively detect Fusarium-infected wheat grains. The developed electronic nose was capable of distinguishing between four wheat Fusaria species with
an accuracy of more than 80%, which allowing them to be excluded from the food or
feed chain. Similarly, Wu et al. (2013) assessed the feasibility of the application of
e-nose technology to detect insect infestation in wheat. Wu et al. (2013) used an
Alpha MOS FOX-3000 electronic nose equipped with 12 metal oxide semiconductor sensors to evaluate the presence of rusty grain beetle and red flour beetle in
wheat. The e-nose detects the presence of red flour beetle in wheat with 20 insects
Kg
À1 of grains at 14–16% moisture content. These results clearly indicated that
e-nose could also be used to detect other species of insects, in stored grains.
Nanotechnology offers food safety in terms of packaging for ensuring a longer
shelf life by avoiding spoilage or loss of food nutrients (Sharma et al. 2017b). Active
packaging has a desirable role in food preservation other than providing an inert
barrier to the external conditions (Pathakoti et al. 2017). Active type of packaging
includes usage of metal and metal oxide nanoparticles as antimicrobial agents in the
form of nanocomposites for food packaging. Several companies like Nanocor Inc.
and Southern Clay Products in the USA use montmorillonite as an additive in
nanocomposite production. The supplementation of 3–5% montmorillonite makes
5 Nanotechnology in Wheat Production and Protection
183
Nanosensors based on nanoparticles have been devised to detect moisture content
inside a food package (Pathakoti et al. 2017). Such kind of nanosensor is usually
based upon carbon-coated copper nanoparticles dispersed in a tenside film
(Luechinger et al. 2007). Principally, under humid and moist conditions, swelling
of the polymer matrix results in separation of inter-nanoparticle. These changes
cause sensor strips to reflect or absorb different colors of light that can be monitored
for quick and accurate determination of package moisture levels without invasive
sampling. For instance, Neethirajan et al. (2009) developed grain quality monitoring
nanosensors by using conducting polymer nanoparticles which respond to analytes
and volatiles in the food storage environment and thereby detect the source and the
type of spoilage (Neethirajan et al. 2009). Because of the miniaturization and
requirement of low power, such type of nanosensors can be designed and deployed
into the crevices of grain bulk, where the stored product pests often hide. Jonsson
et al. (1997) developed an e-nose with three different complementary sensors (ten
gas-sensitive metal oxide semiconductor field effect transistors, four tin dioxidebased sensors, and a carbon dioxide sensor) to test wheat samples with different
levels of ergosterol, fungal, and bacterial contamination. In wheat, high degrees of
correlation between artificial neural network predictions and measured ergosterol as
well as fungal and bacterial colony forming units were observed. Campagnoli et al.
(2011) developed electronic nose equipped with metal oxide semiconductor sensors
and used it as a screening tool for the recognition of durum wheat naturally
contaminated by deoxynivalenol. The e-nose was able to detect durum wheat
whole-grain samples naturally contaminated with deoxynivalenol at the concentration level recommended by the European legislation, employing principal component analysis processing and a classifier based on classification and regression trees.
Further, Eifler et al. (2011) showed that the metalloporphyrin-based e-nose can be
used to qualitatively detect Fusarium-infected wheat grains. The developed electronic nose was capable of distinguishing between four wheat Fusaria species with
an accuracy of more than 80%, which allowing them to be excluded from the food or
feed chain. Similarly, Wu et al. (2013) assessed the feasibility of the application of
e-nose technology to detect insect infestation in wheat. Wu et al. (2013) used an
Alpha MOS FOX-3000 electronic nose equipped with 12 metal oxide semiconductor sensors to evaluate the presence of rusty grain beetle and red flour beetle in
wheat. The e-nose detects the presence of red flour beetle in wheat with 20 insects
Kg
À1 of grains at 14–16% moisture content. These results clearly indicated that
e-nose could also be used to detect other species of insects, in stored grains.
Nanotechnology offers food safety in terms of packaging for ensuring a longer
shelf life by avoiding spoilage or loss of food nutrients (Sharma et al. 2017b). Active
packaging has a desirable role in food preservation other than providing an inert
barrier to the external conditions (Pathakoti et al. 2017). Active type of packaging
includes usage of metal and metal oxide nanoparticles as antimicrobial agents in the
form of nanocomposites for food packaging. Several companies like Nanocor Inc.
and Southern Clay Products in the USA use montmorillonite as an additive in
nanocomposite production. The supplementation of 3–5% montmorillonite makes
5 Nanotechnology in Wheat Production and Protection
183