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.

Cereal Chem. 87(6):511-517Fusarium 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 frac-* The e-Xtra logo stands for "electronic extra" and indicates that Figures 1 and 3 appear in color online.

BackgroundMosquito 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.MethodsTwo 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.ResultsThe mean accuracy obtained for predicting the age of young (<7 days) or old (≥ 7 days) of all fresh (n = 633) and all preserved (n = 691) mosquito samples using the cross-validation technique was 83% and 90%, respectively. For species identification, accuracies were 82% for fresh against 80% for RNAlater® 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.ConclusionRNAlater® 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.

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.

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 <2% with 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 (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.

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