Potentially toxic elements capture by an active living wall in indoor environments: Effect of species in air phytoremediation

Indoor air pollution is a serious health problem throughout the world. Plants are known to be able to reduce the effect of air pollution and improve indoor air quality (IAQ). The aim of the present study was to compare the effectiveness of four plant species (Tradescantia zebrina hort. ex Bosse, Philodendron scandens K. Koch & Sello, Ficus pumila L. and Chlorophtytum comosum (Thunb.) Jacques) planted in an active living wall (ALW) for capturing particle pollutants. The ALW was introduced in a glass chamber and exposed to large (10-40 μm) and fine (1.2-10 μm) airborne particles containing a fixed concentration of potentially toxic elements (Al, B, Cd, Co, Cr, Cu, Ni and Pb). The surface particle deposition (sPM) was estimated in the leaves from the four species and the potentially toxic element concentration in the particulate matter (PM) was measured in plants, medium culture and in the ALW support system. The distribution of different particle size fractions differed between species. The capacity to trap particles on leaf surfaces was similar among the species (4.7-13 ng cm-2) except when comparing Tradescantia and Chlorophytum with Ficus, being higher in the latter species. Differences in toxic elements accumulation capacity were observed between species depending on the elements considered. The percentage of reduction in indoor pollution using an ALW was in a range of 65-79% being similar between species. Plants were the most important component of the ALW in terms of accumulation of indoor potentially toxic elements. The data presented here could be used to model the effectiveness of ALW systems schemes in improving IAQ.

Authentication of Iberian pork official quality categories using a portable near infrared spectroscopy (NIRS) instrument

A portable near infrared spectroscopy (NIRS) instrument was evaluated for the discrimination of individual Iberian pig carcasses into the four official quality categories (defined by a combination of genotype and feeding regime). Spectra were obtained scanning four anatomical locations (live animal skin, carcass surface, fresh meat and subcutaneous fat samples) at a commercial abattoir, using a handheld micro electro mechanical system instrument. The best assignments into official quality categories with the NIRS measurements in the carcass surface and subcutaneous fat were able to correctly classify 75.9% and 73.8% of the carcasses, respectively. Moreover, 93.2% and 93.4% of carcasses were correctly classified according to feeding regimes by using the spectra from fresh meat and subcutaneous fat samples. The results suggest that, using subcutaneous fat samples, a portable NIRS could be used in commercial abattoirs as a tool to support the control of official quality category assignment in Iberian pig carcasses.

Direct prediction of bioethanol yield in sugar beet pulp using near infrared spectroscopy

Sugar beets are a raw material for the production of sugar and ethanol. The decision on which end product to pursue could be facilitated by fast and reliable means of predicting the potential ethanol yield from the beets. A Near Infrared (NIR) Spectroscopy-based approach was tested for the direct prediction of the potential bioethanol production from sugar beets. A modified partial least squares (MPLS) regression model was applied to 125 samples, ranging from 21.9 to 31.0 gL(-1) of bioethanol in sugar beet brei. The samples were analyzed in reflectance mode in a Direct Contact Food Analyser (DCFA) FOSS-NIRSystems 6500 monochromator, with standard error of cross validation (SECV), standard error of prediction (SEP), coefficient of determination (r(2)) and coefficient of variation (CV) of 0.51, 0.49, 0.91 and 1.9 gL(-1), respectively. The NIR technique allowed direct prediction of the ethanol yield from sugar beet brei (i.e. the product obtained after sawing beets with a proper machine) in less than 3 min.

Pleiotropic effects of the goat prolactin receptor genotype on milk fatty acid composition

In the lactating mammary gland, prolactin (PRL) stimulates the synthesis of lactose as well as fatty acid uptake, lipogenesis, and triacylglycerol synthesis. Associations between bovine PRL receptor (PRLR) genotype and fat yield have been reported, which illustrates the role of PRL in conveying lipids toward the udder as well as in stimulating their local synthesis during lactation. Conversely, and to the best of our knowledge, the effects of PRLR genotype on milk fatty acid content have not been studied so far in any mammalian species. In this study, we sequenced most of the coding region of the caprine PRLR gene in several individuals from the Malagueña and Murciano-Granadina breeds. This approach allowed us to identify 2 long and short mRNA isoforms, produced by alternative splicing, and 4 single-nucleotide polymorphisms (SNPs), namely, c.177T>C, c.1131G>A, c.1201G>A and c.1355C>T. Two of these SNPs are nonsynonymous and involve G401R (c.1201G>A) and T452I (c.1355C>T) amino acid substitutions in the cytoplasmic domain of PRLR, which plays a fundamental role in signal transduction. Performance of an association analysis with milk composition traits in a Murciano-Granadina goat population revealed highly suggestive effects on palmitoleic acid content, whereas suggestive effects were detected for other fatty acids, such as palmitic and linoleic. These results are consistent with the pleiotropic effects of PRL on mammary gland lipid metabolism and milk composition.

Nutritive evaluation of olive tree leaves by near-infrared spectroscopy: effect of soil contamination and correction with spectral pretreatments

Olive leaves obtained as a byproduct in the Mediterranean region could play an important role in the nutrition of extensive ruminant systems. However, the reported variation in their nutritive value, among other reasons due to discrepancies in mineral content, is considered an important obstacle for their common use. Near-infrared spectroscopy (NIRS) could fulfill the requirements of these productive systems, providing analytical information in a rapid and economic way. In this work, the effect of soil contamination on NIR spectra has been studied, as well as its correction with some of the most commonly used spectral pretreatments (derivatives, multiplicative scatter correction, auto scaling, detrending, and a combination of the last two transforms). Effects were evaluated by visual inspection of the transformed spectra and comparison of the calibration statistics obtained to estimate acid insoluble ash and total ash contents and in vitro pepsin cellulase digestibility of organic and dry matter. The incidence of spectral curvature effects caused by soil contamination that can be conveniently corrected with pretreatments such as derivatives was confirmed.

Evaluation of pretreatment strategies for near-infrared spectroscopy calibration development of unground and ground compound feedingstuffs

Chemometric procedures are usually applied to near-infrared (NIR) spectra in order to obtain prediction models. These procedures include the application of different combinations of spectral mathematical pretreatments for the improvement of calibrations and the selection of the best model on the basis of validation results. In this work, we used an automatic routine to obtain calibrations for unground and ground compound feedingstuffs (N=354 samples), including 49 combinations of pretreatments (first and second derivatives, an auto scaling procedure, detrending and two versions of multiplicative scatter correction). Calibrations for crude fiber and crude protein were developed without elimination of outliers and with 2 or 9 maximum passes of elimination of outliers. Validation statistics were highly influenced by the pretreatments used, as a combined result of their ability to improve the detection of outliers and the model adjustment. The standard error of prediction (SEP) values ranged from 0.61 to 1.27 for crude protein (CP) and from 0.74 to 1.33 for crude fiber (CF). In spite of the fact that validation statistics did not show a clear distribution pattern, some combinations of pretreatments provided consistently better results.