Near Infrared Spectroscopy of Faeces to Predict Diet Quality in Grazing Animals: Development of a Portable System

Faecal near infrared spectroscopy (FNIRS) has been used to predict dietary crude protein (CP) and digestible organic matter (DOM) in grazing animals (Stuth et al., 2003, Coates 2000). Development of robust FNIRS calibrations can be time consuming and costly, thus hindering the application of FNIRS in developing countries. Delivery of samples to central laboratory facilities is dependant upon adequate transportation infrastructure. A take the laboratory to the samples approach is being tested in Mongolia using a portable FNIRS laboratory (Stuth et al,. 2004). The initial step in this process is to duplicate the performance of a static laboratory procedure with portable equipment. The objective of this study was to determine the effectiveness of re-creating existing FNIRS diet quality calibration models on a portable spectrometer

Influence of duration of exposure to field conditions on viability of fecal samples for NIRS analysis.

Abstract: This experiment was conducted to address the issue of spectral integrity of pelleted feces exposed to environmental conditions at different times of the year in near infrared reflectance spectroscopy analysis, using goats as the representative herbivore. Both dietary crude protein and digestible organic matter were predicted. Results indicated that fecal samples collected with up to 7 days of exposure provided similar estimates of diet crude protein and digestible organic matter from samples collected immediately after defecation. Goat feces response to environmental conditions provided useful information as to how collection of many wild herbivores' fecal material could be efficiently sampled for future near infrared reflectance spectroscopy analyses

Application of the Phygrow Forage Production- Runoff Model for Regional Stocking Analysis

A hydrologic-based forage production model, PHYGROW, was used to simulate forage production and carrying capacity of a subtropical shrubland complex of over 34 species grazed by various ratios of cattle and goats with a population of indigenous white-tailed deer over a 20-yr simulated weather profile. The diet selection algorithm allowed the three animal populations to selectively graze preferred foods based on preferences of plant species, plant parts, and live:dead status by phenological stage. A level of maximum utilization of key species was specified. An incremental analysis of cattle:goat demand ratio was analyzed to determine how different combinations of livestock were impacted by variation in weather. Goats were less sensitive to rainfall variation with a greater frequency of severe reductions in numbers of cattle

Beta-Blocker Therapy and Hemophagocytic Lymphohistiocytosis: A Case Report

Objective. The aim of this paper is to describe a fatal case of hemophagocytic lymphohistiocytosis (HLH) in a patient with severe heart failure, who was treated with low-dose propranolol. Patient and Interventions. We report on a 7-month-old boy with Downs syndrome who was born with an unbalanced, left dominant atrioventricular septal defect and aortic coarctation. Despite coarctation repair and pulmonary artery banding he developed intractable heart failure and fever of unknown origin. Since he remained in heart failure he received a trial of low-dose propranolol to stabilize his cardiopulmonary status, which resulted in unexpected immunomodulatory effects. Measurements and Main Result. Immunoactivation was evidenced by high concentrations of procalcitonin, soluble CD 25, tumor necrosis factor α, and interleukin 6 and 8. Propranolol resulting in hepatic compromise as indicated by high lactate dehydrogenase and alanine aminotransferase levels. A therapeutic switch from propranolol to the β1-receptor blocker metoprolol appeared to be instrumental in hemodynamic improvement and allowed discharge from hospital. However, the infant ultimately died from secondary inflammatory reactivation and intractable pulmonary obstructive disease. The autopsy results revealed HLH. Conclusion. Our case describes HLH secondary to heart failure and Downs syndrome. In this highly activated inflammatory state the beneficial hemodynamic effects of propranolol may be accompanied by immunomodulatory effects and the risk of acute liver failure. HLH occurs with a distinct pathophysiology, and specific treatment might be mandatory to increase the chance of survival

Integrating Biophysical and Economic Models for Assessing Impacts of Change on Grazingland Ecosystems

PHYGROW, a hydrologic-based forage simulation model, was parameterized to represent a typical South Texas ranch engaged in the production of cattle and meat goats with an indigenous population of white-tailed deer. Forage production and associated stocking rates for two cattle: goat ratios were simulated for 20 years. Two, ten-year weather scenarios, one representing normal conditions (30% drought years) and one representing dryer weather conditions (50% drought years) were analyzed. Management decision rules were developed for the region to produce estimates of annual animal production and operating cost for the enterprises in each of the four scenarios. These performance and cost data were then used as input into FLIPSIM, a firm level income and policy simulator, along with relevant product and input price data for the region. Integration of modeled results produced useful information showing the socioeconomic consequences for a typical South Texas firm impacted by alternative climatic conditions and management strategies

Optimizing the procedure of grain nutrient predictions in barley via hyperspectral imaging

Hyperspectral imaging enables researchers and plant breeders to analyze various traits of interest like nutritional value in high throughput. In order to achieve this, the optimal design of a reliable calibration model, linking the measured spectra with the investigated traits, is necessary. In the present study we investigated the impact of different regression models, calibration set sizes and calibration set compositions on prediction performance. For this purpose, we analyzed concentrations of six globally relevant grain nutrients of the wild barley population HEB-YIELD as case study. The data comprised 1,593 plots, grown in 2015 and 2016 at the locations Dundee and Halle, which have been entirely analyzed through traditional laboratory methods and hyperspectral imaging. The results indicated that a linear regression model based on partial least squares outperformed neural networks in this particular data modelling task. There existed a positive relationship between the number of samples in a calibration model and prediction performance, with a local optimum at a calibration set size of ~40% of the total data. The inclusion of samples from several years and locations could clearly improve the predictions of the investigated nutrient traits at small calibration set sizes. It should be stated that the expansion of calibration models with additional samples is only useful as long as they are able to increase trait variability. Models obtained in a certain environment were only to a limited extent transferable to other environments. They should therefore be successively upgraded with new calibration data to enable a reliable prediction of the desired traits. The presented results will assist the design and conceptualization of future hyperspectral imaging projects in order to achieve reliable predictions. It will in general help to establish practical applications of hyperspectral imaging systems, for instance in plant breeding concepts