Barley Kernels Research Articles

Identifying defects and varieties of Malting Barley Kernels

This study introduces a comprehensive approach for classifying individual malting barley kernels, involving dual-sided kernel imaging, a specifically designed image processing algorithm, an optimized deep neural network architecture, and a mechanical sorting system. The proposed method achieves precise classification into multiple classes, aligning with quality standards for malting material assessment. Throughout the study, various image analysis techniques were assessed, including traditional feature engineering, established transfer learning deep neural network architectures, and our custom-designed convolutional neural network tailored for barley kernel image analysis. Comparative analysis underscores the superior performance of our network model. The study reveals that our proposed deep learning network achieves a 94% accuracy in classifying barley kernel defects and varieties, outperforming well-established transfer learning models to complex architectures that attain 93% accuracy. Additionally, it surpasses the traditional machine learning approach involving feature extraction and support vector machine classifiers, which achieve accuracy below 90% in detecting defective kernels and below 70% in varietal classification. However, we also noted the traditional approach’s advantage in morphological feature recognition. This observation guides new research toward integrating morphological feature extraction techniques with modern convolutional networks. This paper presents a deep neural network designed specifically for the analysis of cereal kernel images in two applications: defect and variety classification. It emphasizes the importance of standardizing kernel orientation and merging images from both sides of the kernel, and introduces a device for image acquisition that fulfills this need.

Comparison of different colored barley hordein/glutelin techno-functional and its ratio modulation on the improvement of reconstituted dough's dynamic thermal processing behavior: A mechanistic investigation

Aiming to boost the high-value utilization of colored barley resources and to broaden its processing depth in cereal products. This study compared the techno-functional characteristics of hordein/glutelin, a key component for gluten in white (W), blue (B), and black (BK) barley, and attempted to modulate their ratios for enhancing reconstituted dough thermal processing suitability. Results indicated that white barley's hordein/glutelin techno-functional profiles are more adapted for dough processing. During dough thermal processing, C2-C3 interval changes were mainly reflected in morphological structure, water distribution, rheological behavior, and textural properties, while the C3-C4 interval variations were interpreted as protein secondary/tertiary structural transitions and intermolecular interactions. Notably, “hordein: glutelin = 50:50″ was a crucial factor in determining the barley dough quality, i.e., low hordein ratio (25:75) was unfavorable for gluten matrix and continuous network formation, whereas its excessive ratio (75:25) weakened the protein aggregation behavior and gluten interaction with starch. Correlation analysis showed that the gluten network's connection density/porosity, protein's secondary structure, and ionic bond strength are key factors modulating dough processing suitability. Therefore, by rationally regulating the hordein/glutelin ratio, barley dough products can be produced with various edible characteristics for consumption. Also, attention should be focused on breeding high hordein ratio barley kernels to improve their gluten profile and thus promote its potential application in cereal processing.

Unraveling cereal physical barriers composed of cell walls and protein matrix: Insights from structural changes and starch digestion

Physical barriers composed of cell walls and protein matrix in cereals, as well as their cooking changes, play important roles in starch digestion. In this study, the physical barriers of native and cooked highland barley (HB), brown rice (BR), and oats (OA) kernels and their contribution to starch digestion were investigated. The resistant starch content was similar in cereal flours, but varied among cooked kernels (HB > BR > OA: 45.05 %, 10.30 %, and 24.71 %). The water adsorption, gelatinization enthalpy, and decrease in hardness of HB kernels were lower than those of OA and BR kernels. Microstructural observations of native kernels showed that HB had the thickest cell walls. After cooking, the lowest cell wall deformation and a dense continuous network developed from the protein matrix were observed in HB kernels. During digestion, undigested starch granules encapsulated by the stable cell walls and strong protein network were observed in HB kernels, but not in BR or OA kernels. Furthermore, the heavily milled HB kernels still had more resistant starch than the intact OA and BR kernels. Therefore, the physical barriers of HB kernels exhibited stronger inhibition of starch gelatinization and digestion. Differences in cereal physical barriers led to various inhibitory effects.

Characterization of mycotoxins produced by two Fusarium species responsible for postharvest rot of banana fruit

AbstractIn an open-air market in southern Italy, we noticed ‘Lady finger’ banana fruit imported from Costa Rica showing a severe rot, whose symptoms consisted of necrotic peel lesions with variable shape and size. Fusarium sacchari and F. proliferatum were consistently isolated from symptomatic fruit. In pathogenicity tests on ‘Lady finger’ banana fruit, F. proliferatum was more virulent than F. sacchari. Quantitative Time-of-Flight Mass Spectrometric analysis of secondary metabolites produced by isolates of these two Fusarium species on three different matrices (banana peel, barley and maize kernels) identified 11 mycotoxins. Seven of them (Fusaproliferin, Fumonisins A1, Fumonisins A2 and Fumonisins B1, Hydrolysed Fumonisin B1, Fusarin C and Moniliformin) were detected in matrices contaminated by F. proliferatum isolates. Fumonisin A1 was the prevalent mycotoxin in both maize kernels and banana peel, while Fumonisin A2 prevailed in barley kernels. Similarly, seven mycotoxins (the cyclic hexadepsipeptides Enniatins B2, B3 and B4, Fumonisins A1 and B2, Hydrolysed Fumonisin B1 and Fusarin C) were detected in matrices contaminated by F. sacchari isolates, but they were only in part the same as those produced by F. proliferatum isolates. Fusarin C prevailed in all three matrices colonized by F. sacchari. Fumonisin A1 was detected exclusively in maize kernels while Enniatins B3 and B4, Fumonisin B2 and Hydrolysed Fumonisin B1 were detected exclusively in barley kernels. Overall, F. proliferatum produced a higher amount of mycotoxins than F. sacchari. Moreover, in banana peel both species produced a lower number and amount of mycotoxins than in the other two matrices.

Risk Assessments and Risk Mitigation to Prevent the Introduction of African Swine Fever into the Danish Pig Population.

African Swine Fever poses a significant threat to pig production. An outbreak in Denmark would have severe economic consequences, potentially resulting in a loss between 335 million and 670 million euros. To mitigate the major risk factors, the Danish authorities and the Danish pig industry have implemented several risk-reducing measures. The small wild boar population in Danish nature has been culled, and a fence between Denmark and Germany has been constructed to stop or reduce the risk of migrating wild boar from Germany. All trucks arriving from abroad, intended for the transport of Danish pigs, are inspected, washed, and disinfected at facilities near the border before being allowed to transport pigs between herds or from herds out of Denmark. Cross-border trade of feedstuffs and potentially risky materials is continuously monitored. Based on risk assessments, feed types or bedding materials from countries with African Swine Fever that could contain parts of wild boar are banned from Danish pig herds. Certain types of fats and oils from countries with African Swine Fever can only be used after heat treatment. The import of whole kernels of corn, wheat, or barley is not considered a risk.

Carpological surveys of the Bronnitsky Settlement in the Novgorod Province

Identification of the diversity of cultivated plants of past historical epochs provides valuable information for clarifying the ways of formation of the cultural flora in a particular region. The medieval economy of ancient northern Russia was formed on the basis of a developed agrarian culture. The revealing of the composition and origin of its traditions is an important fundamental task. The purpose of this work was to study and determine the species identity of carbonized fossil remains of seeds and fruit crops that grew in the medieval northwestern Russia. Based on the results of morphological analysis of fossil plant remains, the presence of wheat, rye, barley and oat kernels was revealed.

Population growth of different stored product species on wheat, barley, and tritordeum

Stored product species can be developed in a variety of stored product grains. In this study, were compare three different grains for their suitability for population growth of primary and secondary stored product insects. In the first series, we evaluated the population growth and damage of Rhyzopertha dominica (F.) (Coleoptera: Bostrychidae), Sitophilus granarius (L.) (Coleoptera: Curculionidae) and Sitophilus oryzae (L.) (Coleoptera: Curculionidae) on whole wheat, barley and tritordeum kernels after 65 days. In the second series, three different percentages of whole and cracked kernels were tested: 100% cracked kernels, 100% whole kernels and 50% cracked +50% whole kernels, for Oryzaephilus surinamensis (L.) (Coleoptera: Silvanidae) and Tribolium castaneum (Herbst) (Coleoptera: Tenebrionidae). The results showed that tritordeum was suitable for the population growth of all species tested. In most of the cases, R. dominica showed higher frass production but S. granarius showed a higher number of damaged kernels. Cracked kernels were preferred by secondary pests than whole kernels and wheat showed the highest progeny production than tritordeum and barley. Overall, commodity, and grain type and percentage of cracked kernels can affect the population growth of stored product insect species. Results of this study showed that stored product insect species can develop in tritordeum and thus should be taken into consideration for further results as may be damaged during storage.

Enhancing malting performance of harder barley varieties through ultrasound treatment

Harder kernels of barley are regarded as one of the factors that restrict water and enzyme movement within the endosperm during malting. A comprehensive study of two domestic varieties was performed for evaluating malting quality. Both β-glucan and total protein content of the Chinese domestic barley (Ganpi-6 and Kenpi-14) were significantly higher than Copeland. Grain hardness of the Chinese domestic barley was higher and water uptake ratio was lower compared with the Copeland. During germination, the expression levels of NCED1, NCED2 (major key regulatory enzymes for abscisic acid biosynthesis genes) were higher, whereas gibberelic acid (GA) synthesis genes (GA20ox1, GA2ox3, GA3ox2) were lower in the Ganpi-6, Kenpi-14 compared with Copeland. These two domestic barley varieties also showed significantly lower limit dextrinase and β-glucanase activity compared with Copeland. Ultrasound treatment improved the malting quality of Ganpi-6 by enhancing water uptake and GA synthesis gene expression increased. Therefore, these findings provided insights into the future direction on the utilization of ultrasonication for the applications towards the improvement of the harder barley variety.

Aberrant Behavior of Deoxynivalenol Production in the Malting of Fusarium Head Blight Infected Barley: Mycotoxin Accumulation and Hyphal Localization in Single Kernels

The malting industry faces a dilemma in which barley, initially containing low deoxynivalenol levels, occasionally exhibits an unexpected increase in deoxynivalenol levels during malting. In the current study, we investigated mycotoxin accumulation and hyphal localization in single kernels from Fusarium head blight infected barley and malt samples which showed an aberrant behavior of deoxynivalenol increases during malting. While deoxynivalenol levels in these bulk barley samples already ranged from <0.20 to 1.27 µg/g, they further increased on average by approximately 500% after malting, along with Fusarium growth. In addition, deoxynivalenol-3-glucoside and 3-acetyl deoxynivalenol levels increased from <0.20 µg/g to the mean levels of 2.47 µg/g and 1.03 µg/g in the bulk malt, respectively. In the investigation of single kernels, results showed that only 7% of barley single kernels (n = 385) had deoxynivalenol >1.00 μg/g, with the maximum level of 35.97 μg/g. However, 31% of malt single kernels contained deoxynivalenol >1.00 μg/g and up to 255.43 μg/g. Deoxynivalenol-3-glucoside and 3-acetyl deoxynivalenol were found in 40% of malt single kernels. Fungal hyphae were observed in the aleurone layer and embryo of barley kernels with deoxynivalenol >10.00 μg/g, in addition to the husk and vascular bundles of kernels with deoxynivalenol <1.00 μg/g. Hyphae spread largely in these tissues following malting, and even into the endosperm and pericarp cavities of extremely high deoxynivalenol kernels (i.e., >100.00 μg/g).

Study on establishment of residual analysis methods and residue degradation regulation of natural pyrethrin in barley plants and soil on Qinghai Plateau

The purpose of this study is to develop an accurate and efficient assay for the detection of pyrethroid residues and degradation in barley and soil in the Qinghai Plateau region. A sensitive and selective method was developed for the determination of pyrethrin residues in highland barley (kernel, stem, and root) and soil in the Qinghai Plateau by liquid chromatography (LC-MS/MS). Multi-residue analysis of pyrethrin in samples involves simple extraction with acetonitrile, salt-out with NaCl, MgSO4 absorption of water, cleaning with GCB and PSA, respectively, followed by separation with XR-ODS II column, and multi-reaction detection mode detection using a positive mode electrospray ionization source (ESI + ). The results showed that the 6 different components of pyrethrin had a good detection effect in the concentration range of 0.01 ∼ 1.0 mg/L, and the correlation coefficient was greater than 0.9990. The limits of quantitation of each component on each substrate were 0.01 ∼ 0.05 mg/kg, the average daily recoveries were 87.58 ∼ 95.44 %, and the relative standard deviations were 0.4 ∼ 3.8 %. The half-life of pyrethrin in barley grains, stems and soil was 0.77 ∼ 2.57 d. In soil and highland barley, the maximum dose of pyrethrin and twice the maximum dose of pyrethrin were applied, and the final residue 7 days after treatment was less than 0.2 mg/kg. The degradation behavior of pyrethrin in soil at three test sites showed that organic carbon and pH were important factors affecting the degradation of pyrethrin, and the effect of pH on the degradation of six pyrethrin components was greater than that of organic carbon. These studies provide theoretical basis for environmental safety evaluation caused by pyrethrin use in the Qinghai Plateau.

Dry fractionation for endosperm recovery from a barley malt waste stream

Cereal processing industry removes the fibrous tissues from kernels via abrasive milling, but this tends to remove part of the valuable endosperm components as well. Therefore, endosperm recovery from such abraded barley malt material (53% endosperm and 47% husk) was evaluated for three dry separation technologies. Electrostatic separation recovered 25% of the endosperm at 85% purity and this recovery increased to 39% in a second run, which indicated potential to further improve the setup. Increasingly finer sieves removed up to 40% of the husk with little endosperm loss, but further husk removal up to 95% by the finest sieve reduced the endosperm yield to 54% due to decreasing differences in smallest diameter between the endosperm and husk particles. Air classification outperformed sieving by yielding 71% of the endosperm while removing 95% of the husk, and further, less selective air classification steps could yield up to 94% of the endosperm while still removing 59% of the husk. Moreover, such additional air classification steps currently recovered residual endosperm particles more selectively than electrostatic separation after an initial air classification. Overall, air classification after abrasive milling increased the removal of insoluble matter from malted barley kernels. The loss of soluble endosperm components remained similar to the loss as observed in a single abrasive milling step.

Identification of mutations related to phytate accumulation in barley kernels

Aim. To conduct DNA marker testing on a sample of Ukrainian selection barley samples for identify various lpa-mutations that affect to the qualitative composition of phosphorus in barley grains. Мethods. Isolation of DNA (CTAB method), polymerase chain reaction (PCR) and electrophoretic determination of DNA amplification products in agarose gel for the identification of lpa mutations in barley grains. Results. The conducted molecular genetic studies of 20 breeding lines of hulless barley made possible to identify samples that have lpa-1 and lpa-2 mutations. The presence of such mutant genes determines a low content of organic (unavailable inorganic) phosphorus and an increased content of mineral (available) phosphorus that can be absorbed by the human body. Conclusions. The applied methods of identification of lpa-1 and lpa-2 mutations that affecting to the phytate content in whole grain barley allow for effective analysis of selection lines and mutant samples that can be used in future crossing schemes.

Impact of Erwinia gerundensis as a Biocontrol Agent on the Sanitary and Technological Quality of Barley Malt

This study investigates the use of a barley-associated Erwinia gerundensis strain as a biocontrol agent for the protection of malt against fungal development and mycotoxin production during the malting of barley. First, the antifungal activity of E. gerundensis was studied via simultaneous co-cultures in Yeast Malt broth and on barley kernels artificially infected with Fusarium tricinctum. Then, the effect of E. gerundensis on the fungal load and mycotoxin content of malt obtained from naturally contaminated barley was studied by applying different doses of the bacterial strain at the steeping step of the malting process. Mycotoxin concentrations were determined using the technique of liquid chromatography coupled to the mass spectrometry detector in tandem (LC-MS/MS). Also, the effect of E. gerundensis on the technological quality of the final malt was evaluated using European Brewery Convention standard methods. The bacterial strain reduced the production of enniatin (ENN) by 97.7–99.8% and 38–68% in the liquid medium and on barley kernels, respectively, along with 0–82% Fusarium tricinctum growth reduction on barley kernels. Application of E. gerundensis at the beginning of the steeping step reduced the fungal load of the final malt by 67–72% and its ENN and deoxynivalenol (DON) contents by 32–50% and 15–33%, respectively, depending on the treatment dose. Barley malts treated with E. gerundensis showed no degradation in their technological quality, thus making E. gerundensis a potentially interesting biocontrol agent for the malting and brewing industries. Further investigation should be focused on improving the bioprotective capability of the proposed biocontrol agent.

Multiblock spectral imaging for identification of pre-harvest sprouting in Hordeum vulgare

A novel data fusion method based on the use of visible/near-infrared (VNIR) and shortwave infrared (SWIR) imaging sensors, to distinguish between pregerminated and ungerminated barley grain is proposed. Spectral imaging was used to fingerprint germinated and ungerminated barley grain from a total of 5640 average spectra representing single barley kernels varying with respect to germination time. Chemometric approaches utilising partial least squares-discriminant analysis (PLS-DA) and multiblock sequential and orthogonalized partial least squares-linear discriminant analysis (SO-PLS-LDA) and sequential and orthogonalized covariance selection-linear discriminant analysis (SO-CovSel-LDA) were used to build classification models. SO-PLS-LDA achieved a total classification rate of 99.88%, while SO-CovSel-LDA resulted in a classification accuracy of 97.46% when a maximum of 8 variables were selected from each data block (VNIR and SWIR) – models were validated on an independent test set. The use of multiblock approaches led to increased prediction accuracy, compared to PLS-DA, and a viable solution to address the industry problem to detect pregerminated malting barley in a rapid, non-destructive manner. This represents a significant advance with respect to the current dated methods which are hindered by time-consuming wet chemistry techniques and human subjective bias. The potential of the proposed new technique also has the further advantage of moving toward multispectral systems which can be used to detect pre-harvest germinated barley using an even more computationally rapid and affordable online sorting machine incorporating the wavebands of importance selected by SO-CovSel-LDA. The study highlights how sequential and orthogonalised data fusion approaches, in the food and agricultural sector, are powerful solutions to real world problems.

Evaluation of models based on a generic infection model for controlling early blight in potatoes

TOMCAST and two models (risk hours and critical days) based on a generic infection model (GI model) were evaluated for the timing of fungicide application to control early blight (Alternaria solani) in field experiments. A five-year experiment was conducted at AU Flakkebjerg with the starch potato cultivars Kardal (2016 & 2017), Avarna (2019 & 2020), and Allstar (2021). Barley kernels infested with Alternaria solani were used to inoculate the potatoes. The disease was assessed weekly, starting from the onset of the first symptoms. The impact of disease development was quantified using the area under the disease progress curve (AUDPC), the relative area under the disease progress curve (rAUDPC) as well as starch yield. An economic analysis was done to determine the profitability of the models. Fungicide application significantly suppressed early blight development in comparison to untreated plots. The fungicide-treated plants gave higher yields (10–35%) than the untreated plants. Nevertheless, the models reduced fungicide use by an average of 37–49%, without any yield or economic penalty. Most fungicides were saved with the TOMCAST model, but disease control and yield were generally lower than in plots treated according to the GI-based models. Overall, our study emphasizes the economic importance of early blight and the necessity of applying fungicides to control it. We also show the possibility of significantly reducing fungicide use by using decision support systems. For the first time, we demonstrate the feasibility of using GI models to time fungicide application to control early blight.

Discrimination of Deoxynivalenol Levels of Barley Kernels Using Hyperspectral Imaging in Tandem with Optimized Convolutional Neural Network.

Deoxynivalenol (DON) in raw and processed grain poses significant risks to human and animal health. In this study, the feasibility of classifying DON levels in different genetic lines of barley kernels was evaluated using hyperspectral imaging (HSI) (382-1030 nm) in tandem with an optimized convolutional neural network (CNN). Machine learning methods including logistic regression, support vector machine, stochastic gradient descent, K nearest neighbors, random forest, and CNN were respectively used to develop the classification models. Spectral preprocessing methods including wavelet transform and max-min normalization helped to enhance the performance of different models. A simplified CNN model showed better performance than other machine learning models. Competitive adaptive reweighted sampling (CARS) in combination with successive projections algorithm (SPA) was applied to select the best set of characteristic wavelengths. Based on seven wavelengths selected, the optimized CARS-SPA-CNN model distinguished barley grains with low levels of DON (<5 mg/kg) from those with higher levels (5 mg/kg < DON ≤ 14 mg/kg) with an accuracy of 89.41%. The lower levels of DON class I (0.19 mg/kg ≤ DON ≤ 1.25 mg/kg) and class II (1.25 mg/kg < DON ≤ 5 mg/kg) were successfully distinguished based on the optimized CNN model, yielding a precision of 89.81%. The results suggest that HSI in tandem with CNN has great potential for discrimination of DON levels of barley kernels.

The Type of Grain Counts: Effectiveness of Three Essential Oil-Based Nanoemulsions against Sitophilus oryzae

Essential oil (EO)-based nanoemulsions (NEs) are promising grain protectants in the management of stored-product pests. However, the potential impact of the stored-grain species on the green insecticide effectiveness has been poorly studied. In this study, two concentrations of EO-based NEs from Carlina acaulis L., Mentha longifolia (L.) Huds., and Hazomalania voyronii (Jum.) Capuron were evaluated as insecticides against the major stored-product pest Sitophilus oryzae (L.) on barley, oats, and maize kernels. The C. acaulis EO-based NE applied at 1000 ppm on barley achieved the highest mortality, killing 94.4% of S. oryzae adults after a 7-day exposure, followed by 1000 ppm of H. voyronii EO-based NE (83.3%). The lowest mortality (1.1%) was recorded with 500 ppm of M. longifolia EO-based NE on maize after the same interval. All tested NEs exhibited elevated efficacy when applied on barley, while mortalities were lower on oats and maize. Furthermore, C. acaulis EO-based NE was the most effective when applied on all commodities, followed by H. voyronii and M. longifolia EO-based NEs. Overall, our results highlighted the significant impact of the stored cereal on the insecticidal effectiveness of EO-based NE used for stored-product pest control. Sitophilus oryzae adults on barley can be adequately controlled through the application of C. acaulis and H. voyronii EO-based NEs.

Testing Barley Samples for Potential Insect Infestations with a Conductance Mill

Highlights The conductance mill successfully detected seeds infested with large larvae, over 80% in barley and wheat. Barley seeds, infested with medium larvae, were detected at a lower rate than wheat; ~40% for barley vs. ~65% for wheat. The feed-rate of barley samples was slower than the wheat and the resulting ground barley material contained higher fractions of large particles, over #20 mesh sieve. Abstract. A laboratory mill was developed by Pearson and Brabec (2007) which typically detects 50% to 80% of infested kernels of wheat, brown rice, or popcorn. Barley is another cereal grain of similar size as wheat. Barley is normally sold with its hull attached to the seed, which makes detection of insect infestations more difficult. The objective of this study was to determine the potential of using the conductance mill to detect barley kernels infested by the lesser grain borer, Rhyzopertha dominica (F.), in comparison to detection in wheat. As in previous studies, these experiments found that the conductance mill could detect infested kernels of wheat containing large and medium larvae at a rate of ~90% and ~65%, respectively. For barley, the detection of infested kernels was over ~80% for large larvae and ~40% for medium larvae. Also, we showed that adults that were freely moving throughout the grain mass could also be detected. Approximately ~65% of the adults were detected in wheat while that percentage was reduced to ~35% in barley. The hull on the barley seems to function as an insulator during the conductance measurement and thus reduces detections. Also, the hull seems to affect the feed rate of material through the mill. The feed-rate for wheat was 500 g in 50 s, while the feed-rate for barley was 500 g in ~80 s. Despite these pitfalls, the conductance mill could still be considered as a useful tool with inspecting barley sample, because there was significant detection of insects in the samples and 1000 g sample of barley could be processed in ~4 min. Keywords: Barley, Detection, Rhyzopertha dominica, Sampling, Wheat, X-ray.

Effects of composition, starch structural orders, and kernel structure on starch in vitro digestion of highland barley

In this study, the widely used varieties in China were selected to explore the low starch digestive properties of highland barley from three aspects of composition, starch structural orders, and kernel structure. Two digestive systems were constructed, with highland barley in flour and chyme forms, to investigate the contribution of these inherent properties to starch digestion under different physical forms. Compared with white and black highland barley, blue varieties showed poor chemical composition, lower starch crystallinity, and higher short-range structural order degree, but the starch digestibility as flour was only slightly higher. All varieties of chyme demonstrated lower starch digestibility compared to flour; however, blue highland barley chyme showed much lower starch digestibility than other chyme. Furthermore, kernel structural analysis showed that the blue highland barley kernel structure effectively inhibited digestion. These results indicated that the kernel structure had a critical influence on the starch digestibility of highland barley.

Revealed interactive association between macro-molecular structures and true nutrition supply in cool-season adapted CDC chickpeas and CDC barley using advanced vibrational molecular spectroscopic techniques

Recently, an interactive association between molecular structures and nutrition of protein could be used for evaluation of truly absorbable nutrient supply, nutrient utilization and availability. However, there was no study found in cool-season adapted chickpeas. The objectives of this study were to: (1) reveal an interactive association between macro-molecular structures and nutrition of protein in cool-season adapted CDC chickpeas; (2) Characterize macro-molecular structure features of cool-season adapted CDC chickpeas and their genotypic impact on nutrient profile, fractionation, bioenergy values and biodegradation function in comparison with CDC barley kernel. Macromolecular structures determination was carried out using molecular vibrational spectroscopy-ATR-FTIR. Results showed that with vibrational molecular spectroscopy, the macromolecular spectral characteristics could be revealed among the varieties and between types of CDC developed grain (Chickpea vs CDC barley). The molecular spectral characteristics had significant relationship (P < 0.05) with carbohydrate profiles, sub-fractions and degradation, bypassed, total digestible carbohydrate and protein. Multiple regression with model nutrient variable selection study showed that protein and carbohydrate-related macro-molecular structural parameters were associated with nutrient profiles and degradation characteristics. The results indicated that there was an interactive association between macro-molecular structures and nutrition of protein in cool-season chickpeas.