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Chemical composition and grain quality traits are important factors related to the end-use quality of sorghum. Thus, rapid and non-destructive analytical methods for screening sorghum for desirable grain quality traits benefit the industries using sorghum for food, feed, and biofuels as well as sorghum breeders and seed companies working to improve the grain quality of sorghum. In the present study, a method based on Fourier-transform infrared spectroscopy (FTIR) was developed to characterize the major chemical components in sorghum flour. Sorghum flour had three major FTIR active regions from 1800 to 800 cm−1. As expected, FTIR spectra revealed that starch was the primary compound in sorghum flour, followed by protein with only minor amounts of lipids and phenolic acids. Phenolic acids were characterized by a peak at 1709 cm−1, which varied in intensity across sorghum varieties. Tannin sorghum could be discriminated from non-tannin sorghum by a shift in O–H stretch band around 3300 cm−1 and their C=C absorption peaks at 1608 and 1522 cm−1. Flour from the outer part of the kernel (corneous endosperm) had greater protein and lipid absorbance while the inner kernel (floury endosperm) had stronger starch absorbance. Pearson’s correlation analyses between FTIR peak intensities and protein/starch content showed that starch content did not have a significant correlation with infrared peaks, whereas the amide I peak at 1652 cm−1 (C=O stretching group), highly correlated with protein content (P ≤ 0.05). A calibration curve (Y = 127.79X-14.345, R2 = 0.9454) was built using peak height at 1652 cm−1 to predict protein content and this was applied to determining protein digestibility.

BACKGROUND In a world constantly challenged by climate change, corn and sorghum are two important grains because of their high productivity and adaptability, and their multifunctional use for different purposes such as human food, animal feed, and feedstock for many industrial products and biofuels. Corn and sorghum can be utilized interchangeably in certain applications; one grain may be preferred over the other for several reasons. The determination of the composition corn and sorghum flour mixtures may be necessary for economic, regulatory, environmental, functional, or nutritional reasons. RESULTS Laser-induced breakdown spectroscopy (LIBS) in combination with chemometrics, was used for the classification of flour samples based on the LIBS spectra of flour types and mixtures using partial least squares discriminant analysis (PLS-DA) and the determination of the sorghum ratio in sorghum / corn flour mixture based on their elemental composition using partial least squares (PLS) regression. Laser-induced breakdown spectroscopy with PLS-DA successfully identified the samples as either pure corn, pure sorghum, or corn-sorghum mixtures. Moreover, the addition of various levels of sorghum flour to mixtures of corn-sorghum flour were used for PLS analysis. The coefficient of determination values of calibration and validation PLS models are 0.979 and 0.965, respectively. The limit of detection of the PLS models is 4.36%. CONCLUSION This study offers a rapid method for the determination of the sorghum level in corn-sorghum flour mixtures and the classification of flour samples with high accuracy, a short analysis time, and no requirement for time-consuming sample preparation procedures. (c) 2020 Society of Chemical Industry WOS:000564850000001 2-s2.0-85090065302 PubMed: 32776325

Starch, mainly composed of amylose and amylopectin, is the major nutrient in grain sorghum. Amylose and amylopectin composition affects the starch properties of sorghum flour which in turn determine the suitability of sorghum grains for various end uses. Partial least squares regression models on near infrared (NIR) spectra were developed to estimate starch and amylose contents in intact grain sorghum samples. Sorghum starch calibration model with a coefficient of determination (R2) = 0.87, root mean square error of cross validation (RMSECV) = 1.57% and slope = 0.89 predicted the starch content of validation set with R2 = 0.76, root mean square error of prediction (RMSEP) = 2.13%, slope = 0.93 and bias = 0.20%. Amylose calibration model with R2 = 0.84, RMSECV = 2.96% and slope = 0.86 predicted the amylose content in validation samples with R2 = 0.76, RMSEP = 2.60%, slope = 0.98 and bias = −0.44%. Final starch and amylose cross validated calibration models were constructed combining respective calibration and validation sets and used to predict starch and amylose contents in 1337 grain samples from two diverse sorghum populations. Protein and moisture contents of the samples were determined using previously tested NIR spectroscopy models. The distribution of starch and protein contents in the samples of low amylose (&lt, 5%) and normal amylose (&gt, 15%) and the overall relationship between starch and protein contents of the sorghum populations were investigated. Percent starch and protein were negatively correlated, low amylose lines tended to have lower starch and higher protein contents than lines with high amylose. The results showed that NIR spectroscopy of whole grain can be used as a high throughput pre-screening method to identify sorghum germplasm with specific starch quality traits to develop hybrids for various end uses.

Deoxynivalenol (DON) levels in harvested grain samples are used to evaluate the Fusarium head blight (FHB) resistance of wheat cultivars and breeding lines. Fourier transform near-infrared (FT-NIR) calibrations were developed to estimate the DON level and moisture content (MC) of bulk wheat grain samples harvested from FHB screening trials. Grains in a rotating glass petri dish were scanned in the 10,000–4,000 cm−1 (1,000–2,500 nm) spectral range using a Perkin Elmer Spectrum 400 FT-IR/FT-NIR spectrometer. The DON calibration predicted the DON levels in test samples with R2 = 0.62 and root mean square error of prediction (RMSEP) = 8.01 ppm. When 5–25 ppm of DON was used as the cut-off to classify samples into low- and high-DON groups, 60.8–82.3% of the low-DON samples were correctly classified, whereas the classification accuracy of the high-DON group was 82.3–94.0%. The MC calibration predicted the MC in grain samples with R2 = 0.98 and RMSEP = 0.19%. Therefore, these FT-NIR calibrations can be used to r...

Fusarium head blight (FHB) reduces grain yield and accumulates mycotoxins in wheat kernels and flour and thus compromise the end-use quality. In this study, quantitative trait loci (QTL) associated with components of FHB resistance were mapped in the Kansas wheat variety Everest. A doubled haploid (DH) population with 176 lines was developed from a cross between Everest and WB-Cedar, which are moderately resistant and moderately susceptible to FHB, respectively. Two-year field evaluations were conducted using a randomized complete block design with three replications. Deoxynivalenol (DON) accumulation and Fusarium-damaged kernels (FDK) were estimated using a single-kernel near-infrared (SKNIR) system. Four QTL from Everest were identified on 1BS, 3DS, 4BL, and 5AS, indicating that this variety is a source of native FHB resistance conditioned by multiple loci. A large-effect QTL (Qksu-fhbE-5AS) from Everest explained up to 13% of the DON variation in the 2-year experiment average. A single QTL from WB-Cedar, Qksu.fhbC-1AS, was identified contributing FHB resistance. QTL grouping analysis showed that individuals containing multiple QTL were significantly more resistant, indicating that QTL pyramiding enhances FHB resistance. A 36% reduction in DON content was observed in DH lines carrying all mapped QTL for DON accumulation. Further validation of the QTL mapped here will allow breeding programs to increase FHB resistance in other genetic backgrounds. This is the first study that identified QTL associated with low DON accumulation in multiple years of field experiment using the SKNIR technology, supporting the use of this methodology in future genetics and breeding studies.

Wegulo, S. N., Bockus, W. W., Hernandez Nopsa, J., De Wolf, E. D., Eskridge, K. M., Peiris, K. H. S., and Dowell, F. E. 2011. Effects of integrating cultivar resistance and fungicide application on Fusarium head blight and deoxynivalenol in winter wheat. Plant Dis. 95:554-560. Fusarium head blight (FHB) or scab, incited by Fusarium graminearum, can cause significant economic losses in small grain production. Five field experiments were conducted from 2007 to 2009 to determine the effects on FHB and the associated mycotoxin deoxynivalenol (DON) of integrating winter wheat cultivar resistance and fungicide application. Other variables measured were yield and the percentage of Fusarium-damaged kernels (FDK). The fungicides prothioconazole + tebuconazole (formulated as Prosaro 421 SC) were applied at the rate of 0.475 liters/ha, or not applied, to three cultivars (experiments 1 to 3) or six cultivars (experiments 4 and 5) differing in their levels of resistance to FHB and DON accumulation. The effect of cultivar on FHB index was highly significant (P < 0.0001) in all five experiments. Under the highest FHB intensity and no fungicide application, the moderately resistant cultivars Harry, Heyne, Roane, and Truman had less severe FHB than the susceptible cultivars 2137, Jagalene, Overley, and Tomahawk (indices of 30 to 46% and 78 to 99%, respectively). Percent fungicide efficacy in reducing index and DON was greater in moderately resistant than in susceptible cultivars. Yield was negatively correlated with index, with FDK, and with DON, whereas index was positively correlated with FDK and with DON, and FDK and DON were positively correlated. Correlation between index and DON, index and FDK, and FDK and DON was stronger in susceptible than in moderately resistant cultivars, whereas the negative correlation between yield and FDK and yield and DON was stronger in moderately resistant than in susceptible cultivars. Overall, the strongest correlation was between index and DON (0.74 ≤ R ≤ 0.88, P ≤ 0.05). The results from this study indicate that fungicide efficacy in reducing FHB and DON was greater in moderately resistant cultivars than in susceptible ones. This shows that integrating cultivar resistance with fungicide application can be an effective strategy for management of FHB and DON in winter wheat.

Fusarium head blight (FHB) is a serious disease in wheat that affects grain quality owing to the accumulation of mycotoxins such as deoxynivalenol (DON) in grains. Near-infrared (NIR) spectroscopy has been used to develop techniques to estimate DON levels in single wheat kernels to facilitate rapid, nondestructive screening of FHB resistance in wheat breeding lines. The effect of moisture content (MC) variation on the accuracy of single-kernel DON prediction by NIR spectroscopy was investigated. Sample MC considerably affected accuracy of the current NIR DON calibration by underestimating or overestimating DON at higher or lower moisture levels, respectively. DON in single kernels was most accurately estimated at 13–14% MC. Major NIR absorptions related to Fusarium damage were found around 1,198–1,200, 1,418–1,430, 1,698, and 1,896–1,914 nm. Major moisture related absorptions were observed around 1,162, 1,337, 1,405–1,408, 1,892–1,924, and 2,202 nm. Fusarium damage and moisture related absorptions overlap...

Fusarium head blight (FHB) symptoms, single-kernel deoxynivalenol (DON) levels, and distribution of DON levels among kernels in response to artificial FHB inoculation were investigated in three selected wheat cultivars that had different reported levels of FHB resistance. DON levels were estimated with near-infrared spectroscopy. The percentages of DON-containing spikelets per spike of 15.2, 49.7, and 89.1% were significantly different among point-inoculated spikes of Everest, Karl 92, and Overley, respectively. The percentage of visually Fusarium-damaged kernels in point-inoculated Karl 92 and Overley spikes was significantly higher than for Everest. However, the DON-containing spikelets per spike and visually Fusarium-damaged kernels values for spray-inoculated spikes were not significantly different among the three cultivars. In spray-inoculated spikes, DON levels in kernels ranged from 0 to 291.3 ppm, whereas the variation of DON levels in spikelet positions was random. In contrast, DON levels in spik...

Enhancing chilling tolerance to attain uniform emergence with better seedling vigor under temperatures

A white low polyphenol sorghum, a red-waxy starch sorghum, a red-tannin sorghum with moderate polyphenol levels, and a red non-tannin sorghum were evaluated for susceptibility to Rhyzopertha dominica (Fab.) (Coleopter: Bostrychidae), the lesser grain borer. Density levels of 0 (untreated controls), 10, 20, or 30 mixed-sex adults were exposed on 100 g replicates of each of the varieties and removed after two weeks. Progeny production and physical damage were evaluated on each variety, along with quality characteristics such as moisture content, protein, starch, phenolic content, and kernel vitreousity. Progeny production and physical damage varied with density level and variety, but was generally lowest on the red-waxy sorghum. At the density level of 30 parental adults more progeny were found in the red-tannin sorghum compared to the other varieties. Starch content, kernel vitreousity and hardness was lower in the red-tannin sorghum. Total phenolic content was 2–3x greater in the red-tannin sorghum compared to the other varieties, but the high phenolic content did not seem to affect R. dominica progeny production. Results suggest the insects bypassed the bran layer of the sorghum varieties to feed on the germ and endosperm. Results of this study could be used to further explore the relationships between kernel hardness, chemical composition, and susceptibility to stored product insects, and incorporate results into management programs for maintaining quality of stored sorghum and processed sorghum food by-products.

This report describes a method to estimate the bulk deoxynivalenol (DON) content of wheat grain samples with the single-kernel DON levels estimated by a single-kernel near-infrared (SKNIR) system combined with single-kernel weights. The described method estimated the bulk DON levels in 90% of 160 grain samples to within 6.7 ppm of DON when compared with the DON content determined with the gas chromatography–mass spectrometry method. The single-kernel DON analysis showed that the DON content among DON-containing kernels (DCKs) varied considerably. The analysis of the distribution of DON levels among all kernels and among the DCKs of grain samples is helpful for the in-depth evaluation of the effect of varieties or fungicides on Fusarium head blight (FHB) reactions. The SKNIR DON analysis and estimation of the single-kernel DON distribution patterns demonstrated in this study may be helpful for wheat breeders to evaluate the FHB resistance of varieties in relation to their resistance to the spread ...

Mid-infrared attenuated total reflection (Mid-IR-ATR) spectra (4000-380 cm−1) of pericarp, germ, and endosperm sections from sound and Fusarium-damaged wheat kernels of cultivars Everest and Tomahawk were collected using a Fourier transform infrared (FT-IR) spectrometer. The differences in infrared absorption bands between sound and Fusarium-damaged kernels were examined. Absorption bands in which differences were identified were compared with the mid-IR-ATR absorption bands of deoxynivalenol (DON) and Fusarium graminearum hyphae. Marked differences in absorption patterns were observed between sound and Fusarium-damaged pericarp and germ spectra, whereas those differences were negligible in the endosperm spectra. Fusarium-damaged pericarp and germ spectra exhibited a shift in the peak position of the band near 1035 cm−1 along with increased absorptions at 1160, 1203, 1313, and 1375 cm−1, likely due to the influence of DON and fungi in the Fusarium-damaged kernel tissue matrix. These results suggest that infrared spectroscopy can detect DON in the surface tissues of Fusarium-damaged wheat kernels.

Fusarium head blight (FHB) or scab, caused by Fusarium graminearum Schwabe [sexual stage Gibberella zeae (Schwein.) Petch], is a destructive disease of small grain cereals. Fusarium graminearum produces the mycotoxin deoxynivalenol (DON), which accumulates in and lowers the value and quality of grain. Field experiments were conducted from 2007 to 2009 to determine if two winter wheat cultivars varying in FHB phenotype response differentially accumulated DON. Secondary objectives were to model the relationship between FHB severity and DON, determine if environment (= year) influenced DON accumulation in the two cultivars, and measure the percentage of Fusarium-damaged kernels (FDK) in the two cultivars. The cultivar ‘Harry’ with a moderately resistant FHB phenotype consistently accumulated more DON (P ≤ 0.0358) than ‘2137’ with a susceptible phenotype. The relationship between FHB severity and DON was linear and positive for both cultivars in all three years (0.32 ≤ R2 ≤ 0.60; 0.0053 ≤ P ≤ 0.1092)...

Single kernel moisture content (MC) is important in the measurement of other quality traits in single kernels because many traits are expressed on a dry weight basis. MC also affects viability, storage quality, and price. Also, if near-infrared (NIR) spectroscopy is used to measure grain traits, the influence of water must be accounted for because water is a strong absorber throughout the NIR region. The feasibility of measurement of MC, fresh weight, dry weight, and water mass of single wheat kernels with or without Fusarium damage was investigated using two wheat cultivars with three visually selected classes of kernels with Fusarium damage and a range of MC. Calibration models were developed either from all kernel classes or from only undamaged kernels of one cultivar that were then validated using all spectra of the other cultivar. A calibration model developed for MC when using all kernels from the wheat cultivar Jagalene had a coefficient of determination (R2) of 0.77 and standard error of ...

Cereal Chem. 87(6):511–517 Fusarium Head Blight (FHB), or scab, can result in significant crop yield losses and contaminated grain in wheat (Triticum aestivum L.). Growing less susceptible cultivars is one of the most effective methods for managing FHB and for reducing deoxynivalenol (DON) levels in grain, but breeding programs lack a rapid and objective method for identifying the fungi and toxins. It is important to estimate proportions of sound kernels and Fusarium-damaged kernels (FDK) in grain and to estimate DON levels of FDK to objectively assess the resistance of a cultivar. An automated single kernel near-infrared (SKNIR) spectroscopic method for identification of FDK and for estimating DON levels was evaluated. The SKNIR system classified visually sound and FDK with an accuracy of 98.8 and 99.9%, respectively. The sound fraction had no or very little accumulation of DON. The FDK fraction was sorted into fractions with high or low DON content. The kernels identified as FDK by the SKNIR system had better correlation with other FHB assessment indices such as FHB severity, FHB incidence and kernels/g than visual FDK%. This technique can be successfully employed to nondestructively sort kernels with Fusarium damage and to estimate DON levels of those kernels. Single kernels could be predicted as having low ( 60 ppm) DON with ≈96% accuracy. Single kernel DON levels of the high DON kernels could be estimated with R 2 = 0.87 and standard error of prediction (SEP) of 60.8 ppm. Because the method is nondestructive, seeds may be saved for generation advancement. The automated method is rapid (1 kernel/sec) and sorting grains into several fractions depending on DON levels will provide breeders with more information than techniques that deliver average DON levels from bulk seed samples.

The near infrared (NIR) absorption spectra of deoxynivalenol (DON) and single wheat kernels with or without DON were examined. The NIR absorption spectra of 0.5–2000 ppm of DON in acetonitrile were recorded in the 350–2500 nm range. Second derivative processing of the NIR spectra and spectral subtractions showed DON absorption bands at 1408 nm, 1904 nm and 1919 nm. NIR spectra of sound and Fusarium-damaged kernels were also acquired using two instruments. Subtraction of average absorption spectra and second derivative spectra were evaluated to identify different NIR signatures of the two types of kernel. Differences in peak height and positions of the NIR absorption bands of the kernels were noted. At 1204 nm, 1365 nm and 1700 nm, the differences were in the heights of the absorption peaks. Such differences may be attributed to changes in the levels of grain food reserves such as starches, proteins and lipids and other structural compounds. Shifts in absorption peak positions between the two types of kernels were observed at 1425–1440 nm and 1915–1930 nm. These differences may arise from other NIR active compounds, such as DON, which are not common for the two types of kernel. Since the NIR absorption of DON may have contributed to the shifts between sound and Fusarium-damaged kernels, this study indicates the potential for NIR spectrometry to evaluate Fusarium damage in single kernels based on the DON levels.

Biting midges can transmit diseases that significantly impact livestock in many parts of the world. The age structure of an insect vector population determines its likelihood of transmitting pathogens because the older insects are more likely to be infected than younger ones. Understanding the insect age distribution allows for predictions of their behavior, habitat, vector competence and the vector-borne disease epidemiology. Most insect age grading techniques are laborious and slow, thus we investigated the novel application of midinfrared (MIR) spectroscopy to determine insect age. Female biting midges (Culicoides sonorensis) were anesthetized with chloroform at 1, 4, 7, 10, 13, and 16 days after eclosion. MIR Attenuated Total Reflectance (ATR) spectra of desiccated insects were collected using a Fourier Transform Infrared spectrometer. Transmission spectra of 1, 7, and 13 day old midges were also taken via potassium bromide (KBr) disks prepared with homogenized desiccated insects in each age group. ATR and transmission spectra had identical bands and provide chemical information about the whole insect. The ratio of absorbance of ATR spectra at 1634/1540 cm -1 showed a systematic change with increasing insect age. A similar trend was also observed in the transmission spectra. These absorption bands may be due to the absorbance of chitins and proteins. Therefore, the observed changes in absorption ratios may reflect qualitative or quantitative changes in insect cuticle and/or body proteins in relation to chronological age. When using absorbance data, insects were classified as young (

Spatial variation in soluble solids content (SSC) of fruits of apple (Malus ×domestica Borkh. cv. Red Delicious), cantaloupe (Cucumis melo L. Cantaloupensis group), grapefruit (Citrus paradisi Macf. cv. Indian River Ruby Red), honeydew melon (Cucumis melo L. Inodorus group), mango (Mangifera indica L. cv. Hayden), orange (Citrus sinensis L. Osbeck. cv. Valencia), peach (Prunus persica L. Batsch. cv. Windblow), pineapple (Ananas comosus L. Merr. cv. Kew) and tomato (Lycopersicon esculentum Mill.), and of bulbs of onion (Allium cepa L. Cepa group) and in dry-matter content (DMC) of potato (Solanum tuberosum L. cv. Russet Burbank) tubers was measured along three directional orientations (i.e., proximal to distal, circumferentially midway along the proximal to distal axis, and radially from the center of the interior to the outer surface). The pattern and magnitude of constituent variation depended on the type of product and the direction of measurement. Radial and proximal to distal variation was greater than circumferential variation in all the products tested. Honeydew had the highest radial variation with a SSC difference of 6.0 % and a cv of 22.8%, while tomato displayed lower radial variation with a cv of 1.0%. Pineapple had a proximal to distal SSC difference of 4.6% with a cv of 13.8%, while the difference in tomato was 0.6% with a cv of 5.1%. Circumferential variation of SSC in all products tested was cv ranging from 1.1% to 3.8%. The results confirm that considerable constituent variability exists within individual fruit and vegetable organs. This variability may affect the accuracy of calibration equations and their prediction capability. Therefore, within-unit constituent variability should be meticulously assessed when an NIR spectrometric method is being developed for the nondestructive quality evaluation and sorting of a product.

A nondestructive method for measuring the soluble solids content (SSC) of individual processing tomatoes (Lycopersicon esculentum Mill.) was developed using NIR spectrometry. A diode array fiber optic spectrometer was used to measure NIR transmittance. Each fruit was scanned at two locations on opposite sides midway along the proximal-distal axis. After scanning, each fruit was processed and pureed, and SSC was determined using a refractometer. Multiple linear regression (MLR), partial least squares (PLS) regression, and neural network (NN) calibration models were developed using the second derivatives of averaged spectra from 780 to 980 nm. The validation results showed that NN calibration was better than MLR or PLS calibrations. The NN calibration could estimate the processed SSC of individual unprocessed tomatoes with a standard error of prediction of 0.52% and could classify >72% of fruit in an independent population within ±0.5% of SSC.

A nondestructive method for measuring the soluble solids (SS) content of peaches [Prunus persica (L.) Batsch] was developed using near-infrared (NIR) spectrometry. NIR transmittance in the 800 to 1050 nm region was measured for four cultivars of peaches (`Blake', `Encore', `Red Haven', and `Winblo'), over a period of three seasons (1993 through 1995). Each fruit was scanned on both halves keeping the suture away from the incident light beam. Soluble solids contents of flesh samples taken from corresponding scanned areas were determined using a refractometer. Multiple linear regression models using two wavelengths were developed with second derivative spectral data and laboratory measurements of SS content. Multiple correlation coefficients (R) for individual cultivar calibrations within a single season ranged from 0.76 to 0.98 with standard error of calibration (SEC) values from 0.35% to 1.22%. Selected spectra and corresponding SS data in individual cultivar calibration data sets were combined to create season and cultivar calibration data sets to cover the entire range of SS contents within the season or within the cultivar. These combined calibrations resulted in R values of 0.92 to 0.97 with SEC values ranging from 0.37% to 0.79%. Simple correlations of validations (r) ranged from 0.20 to 0.94 and the standard error of prediction (SEP) ranged from 0.49% to 1.63% while the bias varied from -0.01% to -2.62%. Lower r values and higher SEP and bias values resulted when individual cultivar calibrations were used to predict SS levels in other cultivar validation data sets. Cultivar calibrations, season calibrations and the overall calibration predicted SS content of all validation data sets with a smaller bias and SEP and with higher r values. These results indicate that NIR spectrometry is suitable for rapid nondestructive determination of SS in peaches. Feasible applications of the method include packinghouse sorting of peaches for sweetness and parent and progeny fruit quality assessment in peach breeding programs. Using this technique fruit may be sorted into two or three sweetness classes. The technique may also potentially be extended to other fruit.

© 2013 Wegulo et al., licensee InTech. This is an open access chapter distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Integration of Fungicide Application and Cultivar Resistance to Manage Fusarium Head Blight in Wheat

When screening wheat for Fusarium head blight (FHB) resistance, cultivars are grown under heavy disease pressure and FHB disease levels are assessed using several disease evaluation criteria. The bulk deoxynivalenol (DON) levels of harvested grain samples are often used to evaluate FHB resistance of wheat varieties. In an attempt to reduce the time and cost associated with standard laboratory DON analysis, we developed calibrations for estimating bulk DON levels and moisture content (MC) of wheat grain samples using a Perkin Elmer Spectrum 400 FTIR/FTNIR spectrometer. Grain samples from nursery trials conducted to evaluate FHB resistance of several wheat varieties in 2010 and 2011 were used. Grains in a glass petri-dish were scanned in 10000 – 4000 cm-1 (1000 - 2500 nm) range. The bulk DON levels of grain samples were determined by the standard gas chromatography-mass spectrometry method while the MC was determined by oven drying method. Mean centered absorbance spectra with corresponding DON and MC values were used to develop calibration models using the partial least squares (PLS) regression technique. The DON calibration predicted the bulk DON levels with R2 = 0.48, SEP = 2.4 ppm. Likewise the MC calibration predicted MC in grain samples with R2 = 0.95, SEP = 0.2%. These results suggest that bulk DON level and MC of a grain sample can be non-destructively estimated in about 30 seconds per sample using FTNIR spectroscopy. This also allows adjusting the DON level of samples under a constant MC basis. This method may be used to pre-screen grain samples from scab nursery trials. High DON samples may be identified for culling while those with lower DON levels could be identified for further testing and evaluation using standard laboratory DON analysis. This will reduce the cost of FHB resistance evaluation programs.

Fusarium head blight (FHB) of wheat is caused by Fusarium graminearum and several other Fusarium species. FHB causes significant grain yield and quality losses due to accumulation of mycotoxins such as deoxynivalenol (DON) in infected kernels. Host resistance is considered the most practical and effective means of controlling FHB. DON levels in harvested grains are often used to assess FHB reaction of wheat varieties. A non destructive single kernel method was developed to estimate DON content in wheat grain samples using single kernel DON levels estimated by our single kernel near infrared (SKNIR) system. We estimated DON in 500-kernel grain samples from FHB screening trials conducted in 2010 and 2011 and compared those with DON determined by the gas chromatography-mass spectrometry (GC-MS) method. Results showed that DON levels of small kernel samples can be estimated by the SKNIR method using an estimate of single kernel weight and predicted DON levels. This method estimated DON levels in 90% of 160 samples within 6.7 ppm of DON levels determined by GC-MS. Single kernel DON analysis showed that DON content among DON containing kernels (DCK) varied considerably. Distribution of single kernel DON levels among kernels was used to compare Fusarium head blight (FHB) reaction of wheat varieties. Study of the DON distribution among all kernels as well as among DCK of a grain sample is helpful for an in-depth evaluation of FHB reaction of wheat varieties. The SKNIR single kernel DON analysis and study of single kernel DON distribution patterns demonstrated in this study may help wheat breeders to comprehensively screen varieties in relation to their resistance to spread of disease and resistance to DON accumulation.

HortTechnology · Jan./Mar. 1996 6(1) Summary. Centella asiatica, the Asiatic pennywort, is an herbaceous perennial indigenous to the southeastern United States. In some Asian countries, it is valued as an important vegetable and is widely cultivated. In addition, it is considered an important medicinal herb due primarily to the pentacyclic phytochemical, asiaticoside, which effectively treats a variety of skin diseases. Information on the botany, photochemistry, medicinal, nutritional value, and cultivation of the crop is reviewed. This species may warrant preliminary field and consumer acceptance tests as a speciality vegetable in the United States.

Age-grading of insects is important in the control and monitoring of both insect populations and vector-borne diseases. Microscopy and morphological techniques exist to age-grade most blood-feeding flies, but these techniques are laborious, often destructive to the insects, and slow. Near-infrared spectroscopy (NIRS) can be automated and is a non-destructive technique for age-grading. We applied NIRS techniques to age-grade females of the biting midge, Culicoides sonorensis Wirth & Jones (Diptera: Ceratopogonidae), the vector of bluetongue and other arboviruses in North America. Female flies of five known age cohorts (1, 3, 6, 9 and 12 days post-emergence) from three laboratory colonies were used. The data indicate that NIRS can be used to differentiate age groups of C. sonorensis.

Background Mosquito age and species identification is a crucial determinant of the efficacy of vector control programmes. Near-infrared spectroscopy (NIRS) has previously been applied successfully to rapidly, non-destructively, and simultaneously determine the age and species of freshly anesthetized African malaria vectors from the Anopheles gambiae s.l. species complex: An. gambiae s. s. and Anopheles arabiensis. However, this has only been achieved on freshly-collected specimens and future applications will require samples to be preserved between field collections and scanning by NIRS. In this study, a sample preservation method (RNAlater ®) was evaluated for mosquito age and species identification by NIRS against scans of fresh samples. Methods Two strains of An. gambiae s.s. (CDC and G3) and two strains of An. arabiensis (Dongola, KGB) were reared in the laboratory while the third strain of An. arabiensis (Ifakara) was reared in a semi-field system. All mosquitoes were scanned when fresh and rescanned after preservation in RNAlater ® for several weeks. Age and species identification was determined using a cross-validation. Results The mean accuracy obtained for predicting the age of young (later ® preserved. For both analyses, preserving mosquitoes in RNAlater ® was associated with a highly significant reduction in the likelihood of a misclassification of mosquitoes as young or old using NIRS. Important to note is that the costs for preserving mosquito specimens with RNAlater ® ranges from 3-13 cents per insect depending on the size of the tube used and the number of specimens pooled in one tube. Conclusion RNAlater ® can be used to preserve mosquitoes for subsequent scanning and analysis by NIRS to determine their age and species with minimal costs and with accuracy similar to that achieved from fresh insects. Cold storage availability allows samples to be stored longer than a week after field collection. Further study to develop robust calibrations applicable to other strains from diverse ecological settings is recommended.