Characterization of the desiccation of wheat kernels by multivariate imaging

Abstract

Variations in the quality of wheat kernels can be an important problem in the cereal industry. In particular, desiccation conditions play an essential role in both the technological characteristics of the kernel and its ability to sprout. In planta desiccation constitutes a key stage in the determinism of the functional properties of seeds. The impact of desiccation on the endosperm texture of seed is presented in this work. A simple imaging system had previously been developed to acquire multivariate images to characterize the heterogeneity of food materials. A special algorithm for the use under principal component analysis (PCA) was developed to process the acquired multivariate images. Wheat grains were collected at physiological maturity, and were subjected to two types of drying conditions that induced different kinetics of water loss. A data set containing 24 images (dimensioned 702 × 524 pixels) corresponding to the different desiccation stages of wheat kernels was acquired at different wavelengths and then analyzed. A comparison of the images of kernel sections highlighted changes in kernel texture as a function of their drying conditions. Slow drying led to a floury texture, whereas fast drying caused a glassy texture. The automated imaging system thus developed is sufficiently rapid and economical to enable the characterization in large collections of grain texture as a function of time and water content.

Grain morphology, texture and colour-related compounds of bread wheat cultivars in relation to cultivation regimes and growing location

“…The summarized effect of interactions of the main factors was the highest for phlobaphenes (70.63%). This generally confirms the results of previous studies, in which morphology, colour, hardness / texture and chemical composition were only partly affected by the cultivar (Morris et al, 2005;Hrušková, Švec, 2009;Knievel et al, 2009;Stracke et al, 2009;Fratianni et al, 2013;Lv et al, 2013).…”

“…This texture is defined as repeating patterns of local variations in image intensity, which are too fine to be distinguished as separate objects (Jain, Karu, 1995). Both endosperm and image texture may be determined using different vision systems; however, near-infrared reflectance (NIR) spectroscopy is proposed as probably the best-known technique able to characterize the global texture of wheat grain (Jaillais et al, 2011). The accuracy of grain sample classification / distinguishing by digital…”

“…44-46 NIR units, while the grain of the 'Batuta' was characterized by a substantially higher value -on average 56.87 NIR units (Table 3). These values classified the first group to the medium-soft category, while the 'Batuta' was classified as medium-hard (Hrušková, Švec, 2009). A detailed analysis showed that hardness was the most variable intra-cultivar feature, with variation from approx.…”

Detection of Drechslera avenae (Eidam) Sharif [Helminthosporium avenae (Eidam)] in Black Oat Seeds (Avena strigosa Schreb) Using Multispectral Imaging

“…Thus, the different reflectances showed for different seed health classes may also be explained by increased surface roughness due to fungal infestation. Furthermore, there are evidences that UV images can provide spatial information on texture variations [25] as well as physical surface properties such as intactness and surface density profiles [24]. In the NIR region, the distinctive spectral patterns correspond to the energy absorption of functional groups containing a hydrogen atom (combination of C-H, N-H and O-H).…”

The Use of Image-Spectroscopy Technology as a Diagnostic Method for Seed Health Testing and Variety Identification

“…NIR spectroscopy and imaging have been developed and introduced to classify and compare wheat varieties. Furthermore, these methods reduced human error, saved money and time and also provided more reliable and replicable results [ 7 , 11 , 12 , 13 ].…”