Effects of seasonal variability on FT-NIR prediction of dry matter content for whole Hass avocado fruit

Fourier Transform (FT)-near infra-red spectroscopy (NIRS) was investigated as a non-invasive technique for estimating percentage (%) dry matter of whole intact 'Hass' avocado fruit. Partial least squares (PLS) calibration models were developed from the diffuse reflectance spectra to predict % dry matter, taking into account effects of seasonal variation. It is found that seasonal variability has a significant effect on model predictive performance for dry matter in avocados. The robustness of the calibration model, which in general limits the application for the technique, was found to increase across years (seasons) when more seasonal variability was included in the calibration set. The R-v(2) and RMSEP for the single season prediction models predicting on an independent season ranged from 0.09 to 0.61 and 2.63 to 5.00, respectively, while for the two season models predicting on the third independent season, they ranged from 0.34 to 0.79 and 2.18 to 2.50, respectively. The bias for single season models predicting an independent season was as high as 4.429 but <= 1.417 for the two season combined models. The calibration model encompassing fruit from three consecutive years yielded predictive statistics of R-v(2) = 0.89, RMSEP = 1.43% dry matter with a bias of -0.021 in the range 16.1-39.7% dry matter for the validation population encompassing independent fruit from the three consecutive years. Relevant spectral information for all calibration models was obtained primarily from oil, carbohydrate and water absorbance bands clustered in the 890-980, 1005-1050, 1330-1380 and 1700-1790 nm regions. These results indicate the potential of FT-NIRS, in diffuse reflectance mode, to non-invasively predict the % dry matter of whole 'Hass' avocado fruit and the importance of the development of a calibration model that incorporates seasonal variation. Crown Copyright (c) 2012 Published by Elsevier B.V. All rights reserved.

Detection of a putative hemolysin operon, hhdBA, of Haemophilus parasuis from pigs with Glasser disease

The aim of the current study was to investigate whether polymerase chain reaction amplification of 16S ribosomal (r)RNA and a putative hemolysin gene operon, hhdBA, can be used to monitor live pigs for the presence of Haemophilus parasuis and predict the virulence of the strains present. Nasal cavity swabs were taken from 30 live, healthy, 1- to 8-week-old pigs on a weekly cycle from a commercial Thai nursery pig herd. A total of 27 of these pigs (90%) tested positive for H. parasuis as early as week 1 of age. None of the H. parasuis-positive samples from healthy pigs was positive for the hhdBA genes. At the same pig nursery, swab samples from nasal cavity, tonsil, trachea, and lung, and exudate samples from pleural/peritoneal cavity were taken from 30 dead pigs displaying typical pathological lesions consistent with Glasser disease. Twenty-two of 140 samples (15.7%) taken from 30 diseased pigs yielded a positive result for H. parasuis. Samples from the exudate (27%) yielded the most positive results, followed by lung, tracheal swab, tonsil, and nasal swab, respectively. Out of 22 positive samples, 12 samples (54.5%) harbored hhdA and/or hhdB genes. Detection rates of hhdA were higher than hhdB. None of the H. parasuis-positive samples taken from nasal cavity of diseased pigs tested positive for hhdBA genes. More work is required to determine if the detection of hhdBA genes is useful for identifying the virulence potential of H. parasuis field isolates.