Automated image analysis as a tool to quantify the colour and composition of rainbow trout (Oncorhynchus mykiss W.) cutlets

The goal of this paper is to propose and evaluate automated image analysis methods for describing muscle cutlets in rainbow trout. The proposed automated image analysis methods were tested on a total of 983 scanned images of trout cutlets, and included quality traits such as fat percentage, flesh colour and the size of morphologically distinguishable subparts of the cutlet. A sub-sample of 50 images was randomly selected for manual segmentation of the cutlet, the dorsal fat depot and the red muscle and regions. The identification of these regions by manual and automatic image analysis correlated strongly (r = 0.97, r = 0.95 and r = 0.91, respectively). The estimated fat percentage obtained from image analysis, based on the area of visible fat and the colour of the cutlet flesh, correlated well with chemical fat percentage measured by mid-infrared transmission spectroscopy (MIT) (r = 0.78). The automated image analysis methods are therefore a reliable means of predicting the fat percentage of trout cutlets. Principal component analysis (PCA) loading plots were used to identify subsets of variables from the image analysis of special significance for further studies; cutlet area, dorsal fat depot area, red muscle area, back height, cutlet width, and width of left and right abdomen wall were among the variables selected. PCA loading plots of different colour variables indicated that simple statistical coefficients such as percentiles and mean values can be used to quantify different aspects of flesh colour. In conclusion, the methods presented here provide a powerful toolbox for describing important morphological structures and quality traits of trout cutlets.     

Customer adapted grading of Scots pine sawn timber using a multivariate method

To define new grading rules, or to customize the ones in use in a rule-based automatic grading (RBAG) system of boards, is a time-consuming job for a sawmill engineer. This has the effect that changes are rarely made. The objective of this study was to continue the development of a method that replaces the calibration of grading rule settings by a holistic-subjective automatic grading, using multivariate models. The objective was also to investigate if this approach can improve sawmill profitability and at the same time have a satisfied customer. For the study, 323 Scots pine (Pinus sylvestris L.) boards were manually graded according to the preferences of an important customer. That is, a customer that regularly purchases significant volumes of sawn timber. This manual grading was seen as reference grading in this work. The same boards were also scanned and graded by a RBAG system, calibrated for the same customer. Multivariate models for prediction of board grade based on aggregated knot variables, obtained from the scanning, were calibrated using partial least squares regression. The results show that prediction of board grades by the multivariate models were more correct, with respect to the manual grading, than the grading by the RBAG system. The prediction of board grades based on multivariate models resulted in 76–87% of the boards graded correctly, according to the manual grading, while the corresponding number was 63% for the RBAG system.     

In silico prediction of Gallibacterium anatis pan-immunogens

The Gram-negative bacterium Gallibacterium anatis is a major cause of salpingitis and peritonitis in commercial egg-layers, leading to reduced egg production and increased mortality. Unfortunately, widespread multidrug resistance and antigenic diversity makes it difficult to control infections and novel prevention strategies are urgently needed. In this study, a pan-genomic reverse vaccinology (RV) approach was used to identify potential vaccine candidates. Firstly, the genomes of 10 selected Gallibacterium strains were analyzed and proteins selected on the following criteria; predicted surface-exposure or secretion, none or one transmembrane helix (TMH), and presence in six or more of the 10 genomes. In total, 42 proteins were selected. The genes encoding 27 of these proteins were successfully cloned in Escherichia coli and the proteins expressed and purified. To reduce the number of vaccine candidates for in vivo testing, each of the purified recombinant proteins was screened by ELISA for their ability to elicit a significant serological response with serum from chickens that had been infected with G. anatis. Additionally, an in silico prediction of the protective potential was carried out based on a protein property prediction method. Of the 27 proteins, two novel putative immunogens were identified; Gab_1309 and Gab_2312. Moreover, three previously characterized virulence factors; GtxA, FlfA and Gab_2156, were identified. Thus, by combining the pan-genomic RV approach with subsequent in vitro and in silico screening, we have narrowed down the pan-proteome of G. anatis to five vaccine candidates. Importantly, preliminary immunization trials indicated an in vivo protective potential of GtxA-N, FlfA and Gab_1309.

Electronic supplementary material

The online version of this article (doi:10.1186/s13567-014-0080-0) contains supplementary material, which is available to authorized users.     

Chemical stabilization of soil organic nitrogen by phenolic lignin residues in anaerobic agroecosystems

This review summarizes independent reports of yield decreases in several agricultural systems that are associated with repeated cropping under wet or submerged soil conditions. Crop and soil data from most of these agroecosystems have led researchers to attribute yield decreases to a reduction in crop uptake of N mineralized from soil organic matter (SOM). These trends are most evident in several long-term field experiments on continuous lowland rice systems in the Philippines, but similar trends are evident in a continuous rice rotation in Arkansas, USA and with no-till cropping systems in North American regions with cool, wet climatic conditions in Spring. Soil analyses from some of these systems have found an accumulation of phenolic lignin compounds in SOM. Phenolic compounds covalently bind nitrogenous compounds into recalcitrant forms in laboratory conditions and occurrence of this chemical immobilization under field conditions would be consistent with field observations of reduced soil N supply. However, technological shortcomings have precluded its demonstration for naturally formed SOM. Through recent advances in nuclear magnetic resonance spectroscopy, agronomically significant quantities of lignin-bound N were found in a triple-cropped rice soil in the Philippines. A major research challenge is to demonstrate in the anaerobic agroecosystems that these lignin residues bind sufficient quantities of soil N to cause the observed yield decreases. A key objective will be to elucidate the cycling dynamics of lignin-bound N relative to the seasonal pattern of crop N demand. Anaerobic decomposition of crop residues may be the key feature of anaerobic cropping systems that promotes the accumulation of phenolic lignin residues and hence the covalent binding of soil N. Potential mitigation options include improved timing of applied N fertilizer, which has already been shown to reverse yield decreases in tropical rice, and aerobic decomposition of crop residues, which can be accomplished through field drainage or timing of tillage operations. Future research will evaluate whether aerobic decomposition promotes the formation of phenol-depleted SOM and greater in-season N mineralization, even when the soil is otherwise maintained under flooded conditions during the growing season.     

Partitioning of soil respiration into its autotrophic and heterotrophic components by means of tree-girdling in old boreal spruce forest

Forests accumulate much less carbon than the amount fixed through photosynthesis because of an almost equally large opposing flux of CO₂ from the ecosystem. Most of the return flux to the atmosphere is through soil respiration, which has two major sources, one heterotrophic (organisms decomposing organic matter) and one autotrophic (roots, mycorrhizal fungi and other root-associated microbes dependent on recent photosynthate). We used tree-girdling to stop the flow of photosynthate to the belowground system, hence, blocking autotrophic soil activity in a 120-yr-old boreal Picea abies forest. We found that at the end of the summer, two months after girdling, the treatment had reduced soil respiration by up to 53%. This figure adds to a growing body of evidence indicating (t-test, d.f. = 7, p < 0.05) that autotrophic respiration may contribute more to total soil respiration in boreal (mean 53 ± 2%) as compared to temperate forests (mean 44 ± 3%). Our data also suggests that there is a seasonal hysteresis in the response of total soil respiration to changes in temperature. We propose that this reflects seasonality in the tree below-ground carbon allocation.