Quantification of salt stress in wheat leaves by Raman spectroscopy and machine learning

The salinity level of the growing medium has diverse effects on the development of plants, including both physical and biochemical changes. To determine the salt stress level of a plant endures, one can measure these structural and chemical changes. Raman spectroscopy and biochemical analysis are some of the most common techniques in the literature. Here, we present a combination of machine learning and Raman spectroscopy with which we can both find out the biochemical change that occurs while the medium salt concentration changes and predict the level of salt stress a wheat sample experiences accurately using our trained regression models. In addition, by applying different machine learning algorithms, we compare the level of success for different algorithms and determine the best method to use in this application. Production units can take actions based on the quantitative information they get from the trained machine learning models related to salt stress, which can potentially increase efficiency and avoid the loss of crops.

RESEARCH AND OPTIMISATION OF THE QUANTITATIVE AND QUALITATIVE CHARACTERISTICS OF GRAIN SHIPLOAD LOTS IN GRAIN TERMINALS

The structure of loading different crops onto vessels at the company Ukrelevatorprom’s grain terminal has been considered. The total grain shipped in 2012–2015 was comprised of 33.7–41.5% of maize, 19.7– 32.2% of wheat, 14.4–26.0% of rapeseed, 6.7–14.2% of barley, and 5.4– 11.0% of soya beans. When forming a 35,000-tonne grain shipload, grain lots stored in silos are sometimes of lower quality than contracts require: the protein and gluten contents can be inappropriate, or there can be smut grains or those damaged by sunn pests. The accepted technology of grain shipload formation does not guarantee that the grain quality will be uniform throughout the whole period of loading a vessel, especially in the beginning. In the first 1,000 tonnes of a grain shipload formed, the weight content of wet gluten was found to be 22.6% instead of 23%, the Falling Number was 145–180 s instead of 230s, and the content of smut grains was not the tolerable 5%, but 6.95–7.8%. The subsequent 2,000–3,000 tonnes of wheat, too, had the Falling Number lower than the contract prescribed (142–215 s), and only further on, its value achieved the required range 295–356 s. In the wheat sample formed from 5,000 tonnes, only the test values of the Falling Number (176s) and the content of smut grains (5.1%) were different from what the contract required. The calculated arithmetic means of the quality parameters of the 5,000-tonne wheat samples formed were practically the same as those determined experimentally, except for the values of the Falling Number and the smut grain content. The values of the coefficient of variation obtained showed that the grain lot was of non-uniform quality: it varied in such parameters as the foreign material (20.82–50.93%), sunn pest-damaged grains (7.41–25.76%), Falling Number (8.76–36.36%), and smut grain content (35.88–78.34%). Application of linear programming methods to optimise the shipload composition has allowed all the quality parameters to meet the contract requirements. Loading grain from all silos simultaneously, with the optimum flow ratio, will result in its even distribution in a shipload, and the grain lot will be of higher quality by all the parameters the contract specifies.

Determination Of T-2 And HT-2 Toxin In Wheat Grain By HPLC With Fluorescence Detection

The procedure of the T-2 and HT-2 toxins determination in wheat grain was developed by high performance liquid chromatography according to the following criteria: specificity, linearity, limits of detection (LOD), limits of quantification (LOQ), trueness (recovery), precision, stability. It was found that the correlation coefficient (R2) for T-2 and HT-2 toxin was 0.9999. Mean recoveries from (R, %) for T-2 and HT-2 toxin at the level of 50–150 μg·Kg-1 from wheat (sample blank) were 91 and 87 %, respectively. The relative standard deviation (RSD, %) of the measurement results under conditions of repeatability and intra-laboratory precision ranged from 0.23 to 3.93 %. The limits of quantification of the method for T-2 and HT-2 toxin was 2.2 and 1.2 μg·Kg-1, respectively. These data are within the range of acceptable minimum levels in accordance with Commission Regulation (EC) No 401/2006. It is confirmed that the standards of T-2, HT2 toxins in solutions can be stored up to 7 days in a freezing chamber, a refrigerator and at room temperature in a tightly closed container without actual loss of concentration. It was found that T-2 and HT-2 in a solution cannot be stored in a lit place, because according to the data obtained, sunlight leads to the destruction of these mycotoxins by 52 % and 59 %, respectively.

Comparison of the Aroma Profiles of Intermediate Wheatgrass and Wheat Bread Crusts

The aroma profiles of bread crusts made from intermediate wheatgrass (Thinopyrum intermedium) and whole wheat (Triticum aestivum) flours were compared. Based on gas chromatography/mass spectrometry/olfactometry analysis, twenty-four odorants were identified and further quantified. The concentrations of seventeen compounds were significantly different between intermediate wheatgrass and whole wheat bread crusts, of which sixteen compounds were higher in the whole wheat sample. The aroma profiles of the bread samples were subsequently characterized using sensory descriptive analysis (DA) and indicated that the roasted attribute was perceived at a significantly higher intensity in the whole wheat sample due to a greater amount of Maillard reaction compounds. Alternatively, bran and green notes were perceived at higher intensities in the intermediate wheatgrass sample, however they were not attributed to the presence of specific compounds but rather to a change in the aroma composition. Aroma recombination DA of the whole wheat and intermediate wheatgrass aroma models was similar to the original aroma profiles of the bread samples, demonstrating the sensory relevance of the identified odorants.

Evaluation of wheat/non-traditional flour composite

We examine the nutritional effect of selected non-traditional grain samples added into wheat flour. In a form of flour, amaranth, quinoa, lupine, 5 hemp types, 2 teff types and 2 chia types were used for wheat flour substitution on a low and high level. Samples with amaranth and lupine flour showed the best improvement in terms of protein content (in the range between 21.1 and 26.0%). The highest total dietary fibre was found in lupine composites (7.1 and 9.8%). Hemp samples contained a significant amount of minerals in comparison with the control wheat sample (from 1.16% to 1.98%). According to the above-mentioned differences, flour composites containing single tested grains were distinguished by principal component analysis. All examined plant materials could be recommended for wheat flour fortification in terms of nutritional improvement. The addition of non-traditional flours partially changed both the volume and shape of laboratory prepared bread correspondingly to the type and added amount.

Effects of sprout damage on durum wheat milling and pasta processing quality

Fu, B. X., Hatcher, D. W. and Schlichting, L. 2014. Effects of sprout damage on durum wheat milling and pasta processing quality. Can. J. Plant Sci. 94: 545–553. Due to concerns over the unusual sprouting problem observed in the 2010 harvest of Canada Western Amber Durum Wheat (CWAD), it was deemed necessary by the industry to investigate and determine if appropriate tolerances for sprout damage were in place, particularly for No. 3 CWAD. More information on the impact of visually assessed sprout damage on durum quality is needed to better define the associated acceptable level of falling number (FN). To this end, two different samples of CWAD were sourced for this project: a No. 1 CWAD (FN 479 s) and a No. 5 CWAD (FN 68 s) degraded primarily due to sprout damage. A total of 19 samples were used in the study, i.e., a series of eight composite samples prepared by blending the No. 1 with increasing amounts of No. 5, as well as the two control extremes. The FNs of the blends were well characterized, displaying an incremental decrease of ∼50 s with increasing sprout damage. Each wheat sample was milled in duplicate. The resulting semolina was analyzed for ash, pigment, pigment loss, yellowness (b*), and speckiness. Protein content, gluten index and alveograph parameters were also evaluated. The semolina was made into spaghetti for colour measurement and texture evaluation. Results indicated that there was no change in ash content, pigment or semolina b* value even at 50% blend (FN 101 s). However, a noticeable increase in total speck count and the number of dark specks in the semolina were detected once the blending ratio reached the 35% level (FN 208 s). The increase in speck count was largely due to mildew associated with the No. 5 CWAD sample. The influence of sprout damage on gluten strength was minimal at all levels of blending. A significant increase in spaghetti redness (a*) was detected in blends with 25% (FN 152 s) or more of No. 5 CWAD. A decline in spaghetti brightness (L*) was also observed when transitioning from the 15% blend (FN 204 s) and very evident at the 35% blend (FN 123 s) level. No discernible differences due to sprout damage were noticed within the composite blends in terms of processing properties, firmness and cooking loss of the cooked pasta, although spaghetti made from the No. 5 sample showed slight checking, higher cooking loss and lower firmness.

Effects of washing and drying applications on deoxynivalenol and zearalenone levels in wheat

In this study, the effects of washing and drying procedures on deoxynivalenol (DON) and zearalenone (ZEA) levels of a naturally contaminated wheat sample were investigated. Wheat grain was washed with water, chlorinated water, and sodium carbonate and sodium hydroxide solutions for 1 and 2 min with a pressurised washing system. Washed wheat samples were dried by using three different procedures, i.e. oven drying at low temperatures, and microwave and infrared drying. Pressure washing of wheat grains with water followed by oven drying reduced mycotoxin levels with a minimum of 30.3% for DON and 21.1% for ZEA. Infrared and microwave drying of pressure washed grains caused further reductions in DON and ZEA concentrations up to 89.0%. Using chlorinated water, sodium carbonate and sodium hydroxide solutions for 1 min reduced DON levels in the range of 37.3-91.2% and ZEA levels in the range of 31.6-83.6%. The results of this study indicated that pressure washing and microwave and infrared drying are promising methods for decontamination of wheat grains, even at high mycotoxin concentrations.

Fungal contamination and the levels of mycotoxins (Don and Ota) in cereal samples from poland and east slovakia

The cereal samples were taken immediately after harvest from the selected localities of Poland(45 samples) and East Slovakia(60 samples). Fungal contamination of these samples was investigated and subsequently the presence of two important mycotoxins, deoxynivalenol (DON) and ochratoxin A (OTA), was quantitatively examined. Concerning mould contamination, no difference was observed between the samples from Polandand East Slovakia. The highest incidence was observed of Fusarium, Aspergillus, and Penicillium genera. However, most of the investigated samples of wheat, rye, and barley contained less than 10⁴ cfu/g. The limit 750 ppb for DON in cereals and their products, recommended by the European Mycotoxin Awareness Network (EMAN), was exceeded only by one wheat sample (4.5%) fromPoland, but by seven wheat samples (14.6%) fromSlovakia. None cereal sample investigated for OTA exceeded the allowed limit – 5 µg/kg.