Starch digestion rates in multiple samples of commonly used feed grains in diets for broiler chickens

In this study the starch digestion rates in broiler chickens from 18 samples of 5 commonly used feed grains (sorghum, wheat, maize, barley, triticale) were determined. The methodology to determine starch digestion rates in poultry is detailed herein. Starch digestion rates were not significantly different (P = 0.128) across the 18 feed grains, which reflects the wide variations that were observed within a given feedstuff. Nevertheless, starch digestion rates in broiler chickens offered wheat-based diets were significantly more rapid by 56.0% (0.117 versus 0.075 min⁻¹; P = 0.012) than their sorghum-based counterparts on the basis of a pair-wise comparison. In descending order, the following starch digestion rates were observed: wheat (0.117 min⁻¹), barley (0.104 min⁻¹), triticale (0.093 min⁻¹), maize (0.086 min⁻¹), sorghum (0.075 min⁻¹). The implications of these findings are discussed as they almost certainly have implications for poultry nutrition and the development of reduced crude protein diets for broiler chickens.     

Object‐Based Mapping of Karst Rocky Desertification using a Support Vector Machine

Accurate and cost‐effective mapping of karst rocky desertification (KRD) is still a challenge at the regional and national scale. Visual interpretation has been utilised in the majority of studies, while an automated method based on pixel data has been investigated repeatedly. An object‐based method coupling with support vector machine (SVM) was developed and tested using Enhanced Thematic Mapper Plus (ETM+) images from three selected counties (Liujiang, Changshun and Zhenyuan) with different karst landscapes in SW China. The method supports a strategy of defining a mapping unit. It combined ETM+ images and ancillary data including elevation, slope and Normalized Difference Vegetation Index images. A sequence of scale parameters estimation, image segmentation, training data sampling, SVM parameters tuning and object classification was performed to achieve the mapping. A quantitative and semi‐automated approach was used to estimate scale parameters for segmenting an object at an optimal scale. We calculated the sum of area‐weighted standard deviation (WS), rate of change for WS, local variance (LV) and rate of change for LV at each scale level, and the threshold of the aforementioned index that indicated the optimal segment level and merge level. The KRD classification results had overall accuracies of 85·50, 84·00 and 84·86 per cent for Liujiang, Changshun and Zhenyuan, respectively, and kappa coefficients are up to 0·8062, 0·7917 and 0·8083, respectively. This approach mapped six classes of KRD and offered a visually appealing presentation. Moreover, it proposed a conceptual and size‐variable object from the classification standard of KRD. The results demonstrate that the application of our method provides an efficient approach for the mapping of KRD. Copyright © 2012 John Wiley & Sons, Ltd.     

Near‐Infrared Hyperspectral Imaging of Fusarium‐Damaged Oats (Avena sativa L.)

The feasibility of hyperspectral imaging (HSI) to detect deoxynivalenol (DON) content and Fusarium damage in single oat kernels was investigated. Hyperspectral images of oat kernels from a Fusarium‐inoculated nursery were used after visual classification as asymptomatic, mildly damaged, and severely damaged. Uninoculated kernels were included as controls. The average spectrum from each kernel was paired with the reference DON value for the same kernel, and a calibration model was fitted by partial least squares regression (PLSR). To correct for the skewed distribution of DON values and avoid nonlinearities in the model, the DON values were transformed as DON* = [log(DON)]³. The model was optimized by cross‐validation, and its prediction performance was validated by predicting DON* values for a separate set of validation kernels. The PLSR model and linear discriminant analysis classification were further used on single‐pixel spectra to investigate the spatial distribution of infection in the kernels. There were clear differences between the kernel classes. The first component separated the uninoculated and asymptomatic from the severely damaged kernels. Infected kernels showed higher intensities at 1,925, 2,070, and 2,140 nm, whereas noninfected kernels were dominated by signals at 1,400, 1,626, and 1,850 nm. The DON* values of the validation kernels were estimated by using their average spectra, and the correlation (R) between predicted and measured DON* was 0.8. Our results show that HSI has great potential in detecting Fusarium damage and predicting DON in oats, but it needs more work to develop a model for routine application.     

Effect of Fermentation and Oil Incorporation on the Retention of E Vitamers During Breadmaking

All forms of baking and processing cause a loss of nutrients, including vitamin E, but little is known about these occurrences or if they could be avoided. The objective of this research was to study the incorporation of palm oil and the stability of vitamin E in palm oil during breadmaking. Wheat meal and rye breads were baked with and without the addition of 0, 2, 5, or 8% palm oil. The eight E group vitamers (tocopherols and tocotrienols) were extracted by using accelerated solvent extraction, freeze dried, and then analyzed with normal‐phase HPLC. Compared with the controls, the inclusion of palm oil was found to increase the quantity of all forms of vitamin E in the final baked products. It is concluded that palm oil is effective in increasing the vitamin E content of whole grain bread.     

Influence of the Expert Effect on Cultural Models

We examined hunters’ perceptions of fauna to see if expert hunters and other hunters perceive wildlife abundance similarly. We used cultural consensus analysis (CCA) to assess the knowledge of 25 hunters in the Bolivian Amazon about the abundance of 38 animals. CCA indicated highly shared beliefs among hunters concerning wildlife abundance (average agreement = .62). However, expert hunters (as judged by their reported successful hunts of rare species, having hunted recently, and consuming more game in their diet) perceived more animals as abundant than did non-experts, although they all shared the same model. Since the expert hunters did not always agree on which species was more abundant, they had low cultural knowledge scores in CCA results. These experts may be unwilling to curtail hunting efforts on key species that they perceive to be abundant.     

INVITED REVIEW—IMAGE REGISTRATION IN VETERINARY RADIATION ONCOLOGY: INDICATIONS,IMPLICATIONS, AND FUTURE ADVANCES

The field of veterinary radiation therapy (RT) has gained substantial momentum in recent decades with significant advances in conformal treatment planning, image‐guided radiation therapy (IGRT), and intensity‐modulated (IMRT) techniques. At the root of these advancements lie improvements in tumor imaging, image alignment (registration), target volume delineation, and identification of critical structures. Image registration has been widely used to combine information from multimodality images such as computerized tomography (CT), magnetic resonance imaging (MRI), and positron emission tomography (PET) to improve the accuracy of radiation delivery and reliably identify tumor‐bearing areas. Many different techniques have been applied in image registration. This review provides an overview of medical image registration in RT and its applications in veterinary oncology. A summary of the most commonly used approaches in human and veterinary medicine is presented along with their current use in IGRT and adaptive radiation therapy (ART). It is important to realize that registration does not guarantee that target volumes, such as the gross tumor volume (GTV), are correctly identified on the image being registered, as limitations unique to registration algorithms exist. Research involving novel registration frameworks for automatic segmentation of tumor volumes is ongoing and comparative oncology programs offer a unique opportunity to test the efficacy of proposed algorithms.