the acquisition between 3,000 and 57,000 spores, fungus and other microorganisms in the harvesting process, generate toxins and consequently with harmful
consequences (Bodroza-Solarov et al. 2012). Among the most common fungus
located inside the grain are Helminthosporium spp.; Giberella spp.; Diplodia spp.;
and Colletotrichum sp.
The objective of group algorithms in image processing is to find pixels groups
having similar characteristics (intensity texture, shape, etc.), and that the groups
represent homogenous regions in the image, González and Woods (2008). This kind
of image processing has been widely used in many image segmentation applications in different areas such as medicine, food processing, chemistry, edaphologic,
mechanics, among others (Quintanilla-Domínguez 2009, 2011; Ojeda-Magaña
2010; Cortina-Januchs et al. 2011); being such group determinations important to
achieve characterizations in different fields of study through the generation of
important data for calibrating predictive models and acquisition of morphological
data (Baptista et al. 2012). The use of digital tools in image processing algorithms
has many industrial applications in areas such as harvest, postharvest, and raw
material processing. In these areas, the morphological dimensions of the objects
(such as fruits, grains, cereals, and oilseeds) with defined or atypical geometries are
required to be known (Peregrina-Barreto et al. 2013). The descriptor determination
of a specie or genotype is an easy task; such descriptor makes reference to the
structure and shape of a surface (López et al. 2008; Baptista et al. 2012). The use of
these tools in the food area allows to make technical processes and to have a more
strict control. However, there is little information available about implementation
of monitoring systems based on image processing techniques for evaluating the
effect of grain storage systems and their behavior on the matrix of silos and
warehouses, where the general conditions of the grain may be affected and difficult
to achieve a constant monitoring (Brosnan and Da-Wen 2002).
The study described in this chapter is based on the hypothesis that it is possible
to quantify the morphological characteristic of wheat grains in the postharvest
processing, this is done by using a digital image processing system in monitoring
factors related with humidity that may have an effect in the grain quality during the
storage stage.
The research objectives are: (i) to monitor the behavior of different types of
wheat grains after different conditioning days have been applied, (ii) to evaluate
the possible relationship between variety and water diffusivity capacity in wheat
grains from its morphometry.
Our study is based on the fact that wheat grains humidity is a variable to be
taken into account in the grain storage stage, and it is an important factor to be
controlled in a specific values range along the grain reception, storage, and
conditioning stages. In the case of hard and soft wheat grains, the maximum
recommended humidity in storage stage is less than 14 %. The humidity variable
control is a determinant factor to keep the best conditions of the grain, for higher
humidity and temperatures above 25 °C a microbacterial proliferation may be
present in the environment, since the grain has the capacity of water absorption,
then it implies its combination with the solid and dry gluten material (Sokhansanj
13 Instrumentation and Control to Improve the Crop Yield
367
consequences (Bodroza-Solarov et al. 2012). Among the most common fungus
located inside the grain are Helminthosporium spp.; Giberella spp.; Diplodia spp.;
and Colletotrichum sp.
The objective of group algorithms in image processing is to find pixels groups
having similar characteristics (intensity texture, shape, etc.), and that the groups
represent homogenous regions in the image, González and Woods (2008). This kind
of image processing has been widely used in many image segmentation applications in different areas such as medicine, food processing, chemistry, edaphologic,
mechanics, among others (Quintanilla-Domínguez 2009, 2011; Ojeda-Magaña
2010; Cortina-Januchs et al. 2011); being such group determinations important to
achieve characterizations in different fields of study through the generation of
important data for calibrating predictive models and acquisition of morphological
data (Baptista et al. 2012). The use of digital tools in image processing algorithms
has many industrial applications in areas such as harvest, postharvest, and raw
material processing. In these areas, the morphological dimensions of the objects
(such as fruits, grains, cereals, and oilseeds) with defined or atypical geometries are
required to be known (Peregrina-Barreto et al. 2013). The descriptor determination
of a specie or genotype is an easy task; such descriptor makes reference to the
structure and shape of a surface (López et al. 2008; Baptista et al. 2012). The use of
these tools in the food area allows to make technical processes and to have a more
strict control. However, there is little information available about implementation
of monitoring systems based on image processing techniques for evaluating the
effect of grain storage systems and their behavior on the matrix of silos and
warehouses, where the general conditions of the grain may be affected and difficult
to achieve a constant monitoring (Brosnan and Da-Wen 2002).
The study described in this chapter is based on the hypothesis that it is possible
to quantify the morphological characteristic of wheat grains in the postharvest
processing, this is done by using a digital image processing system in monitoring
factors related with humidity that may have an effect in the grain quality during the
storage stage.
The research objectives are: (i) to monitor the behavior of different types of
wheat grains after different conditioning days have been applied, (ii) to evaluate
the possible relationship between variety and water diffusivity capacity in wheat
grains from its morphometry.
Our study is based on the fact that wheat grains humidity is a variable to be
taken into account in the grain storage stage, and it is an important factor to be
controlled in a specific values range along the grain reception, storage, and
conditioning stages. In the case of hard and soft wheat grains, the maximum
recommended humidity in storage stage is less than 14 %. The humidity variable
control is a determinant factor to keep the best conditions of the grain, for higher
humidity and temperatures above 25 °C a microbacterial proliferation may be
present in the environment, since the grain has the capacity of water absorption,
then it implies its combination with the solid and dry gluten material (Sokhansanj
13 Instrumentation and Control to Improve the Crop Yield
367