8 research outputs found

    Author Correction: The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data

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    The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data

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    The FLUXNET2015 dataset provides ecosystem-scale data on CO2, water, and energy exchange between the biosphere and the atmosphere, and other meteorological and biological measurements, from 212 sites around the globe (over 1500 site-years, up to and including year 2014). These sites, independently managed and operated, voluntarily contributed their data to create global datasets. Data were quality controlled and processed using uniform methods, to improve consistency and intercomparability across sites. The dataset is already being used in a number of applications, including ecophysiology studies, remote sensing studies, and development of ecosystem and Earth system models. FLUXNET2015 includes derived-data products, such as gap-filled time series, ecosystem respiration and photosynthetic uptake estimates, estimation of uncertainties, and metadata about the measurements, presented for the first time in this paper. In addition, 206 of these sites are for the first time distributed under a Creative Commons (CC-BY 4.0) license. This paper details this enhanced dataset and the processing methods, now made available as open-source codes, making the dataset more accessible, transparent, and reproducible.Peer reviewe

    Single nucleotide polymorphisms (SNPs) of Calpain1, Calpastatin and Cathepsin D genes and their association with beef quality traits in Piemontese cattle breed

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    The interest of researchers and meat industry for beef quality (BQ) has grown dramatically, but routinely assessment of BQ is diffi cult and expensive to be carried out. Several gene polymorphisms have been reported to be involved in BQ. The aim of this study was to evaluate the effect of Calpain1(CAPN1), Calpastatin (CAST) and Cathepsin D (CTS) genes on share force, drip loss, cooking loss and meat color in 990 young Piemontese bulls. CAPN1 SNP g.4558 G>A and CAPN1 SNP g.6545C>T, CAST SNP g.2870A>G, CAST SNP g.2959A>G, CAST SNP g.282C>G, and CTSD SNP g.77G>A were investigated by RFLP-PCR and ARMS-PCR techniques. An association study for the aforementioned SNPs was performed using Bayesian methodology via Gibbs sampling. The model included the effects of the fattening herd, the week of BQ analysis, the genotypes of the investigated loci and the additive genetic effects of animals. A weak effect was observed only for CAST g.282C>G and CAPN1 g.4558 G>A on drip loss and for CAST g.2959A>G on redness. Nevertheless, a 95% Bayesian confi dence region of estimates included zero. These results suggest that genotypes at all investigated loci did not strongly affect BQ

    Effect of polymorphisms in candidate genes on carcass and meat quality traits in double muscled Piemontese cattle

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    The aim of this study was to investigate the association between 10 candidate genes and carcass weight and conformation, carcass daily gain, and meat quality (pH, color, cooking loss, drip loss and shear force) in 990 double-muscled Piemontese young bulls. Animals were genotyped at each of the following genes: growth hormone, growth hormone receptor, pro-opiomelanocortin, pro-opiomelanocortin class 1 homeobox 1, melanocortin-4 receptor, corticotrophin-releasing hormone, diacylglycerol O-acyltransferase-1, thyroglobulin, carboxypeptidase E and gamma-3 regulatory subunit of the AMP-activated protein kinase. All the investigated SNPs had additive effects which were relevant for at least one of the traits. Relevant associations between the investigated SNPs and carcass weight, carcass daily gain and carcass conformation were detected, whereas associations of SNPs with meat quality were moderate. Results confirmed some of previously reported associations, but diverged for others. Validation in other cattle breeds is required to use these SNPs in gene-assisted selection programs for enhancement of carcass traits and meat quality

    Association of polymorphisms in calpain 1, (mu/I) large subunit, calpastatin, and cathepsin D genes with meat quality traits in double-muscled Piemontese cattle.

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    Five single-nucleotide polymorphisms (SNPs) located in the calpain 1, (mu/I) large subunit (CAPN1), calpastatin (CAST), and cathepsin D (CTSD) genes were analyzed in a large sample of Piemontese cattle. The aim of this study was to evaluate allele and genotype frequencies of these SNPs and to investigate associations of CAPN1, CAST, and CTSD gene variants with meat quality traits. Minor allele frequencies ranged from 30 to 48%. The presence of the A allele at CAPN530 increased yellowness and drip loss. The CAST282 G allele was associated with an increased drip loss compared to the C allele, and the CAST2959 A allele decreased redness compared to the G allele

    The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data

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    Abstract The FLUXNET2015 dataset provides ecosystem-scale data on CO2, water, and energy exchange between the biosphere and the atmosphere, and other meteorological and biological measurements, from 212 sites around the globe (over 1500 site-years, up to and including year 2014). These sites, independently managed and operated, voluntarily contributed their data to create global datasets. Data were quality controlled and processed using uniform methods, to improve consistency and intercomparability across sites. The dataset is already being used in a number of applications, including ecophysiology studies, remote sensing studies, and development of ecosystem and Earth system models. FLUXNET2015 includes derived-data products, such as gap-filled time series, ecosystem respiration and photosynthetic uptake estimates, estimation of uncertainties, and metadata about the measurements, presented for the first time in this paper. In addition, 206 of these sites are for the first time distributed under a Creative Commons (CC-BY 4.0) license. This paper details this enhanced dataset and the processing methods, now made available as open-source codes, making the dataset more accessible, transparent, and reproducible

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