Boll positioning and seed ageing effects on seed quality of cotton in Busia County, Kenya

La graine de coton ( Gossypium hirsutum ) est un produit agricole susceptible de se d\ue9t\ue9riorer pendant le stockage. L\u2019objectif de cette \ue9tude \ue9tait de d\ue9terminer l\u2019effet de la position de la capsule sur les graines de la plante et la p\ue9riode de stockage sur la qualit\ue9 des graines de coton. La vari\ue9t\ue9 de coton KSA 81M a \ue9t\ue9 plant\ue9e au Centre de Formation Agricole de Busia (ATC) et les capsules ont \ue9t\ue9 r\ue9colt\ue9es dans les branches basale, centrale et sup\ue9rieure. Les graines ont \ue9t\ue9 stock\ue9es puis test\ue9es pour d\ue9terminer la qualit\ue9 des graines. En g\ue9n\ue9ral, le pourcentage de germination des graines a diminu\ue9 pendant la p\ue9riode de stockage; tandis que la conductivit\ue9 \ue9lectrique et le temps moyen de germination augmentaient. Remarquablement, la capacit\ue9 germinative des graines provenant des tiges basales est tomb\ue9e en dessous de la capacit\ue9 germinative des graines des branches m\ue9dianes et sup\ue9rieures, apr\ue8s six mois malgr\ue9 un pourcentage de germination initial plus \ue9lev\ue9. En revanche, la conductivit\ue9 \ue9lectrique et le temps moyen de germination des graines des branches basales ont montr\ue9 une augmentation significative apr\ue8s six mois par rapport aux branches moyennes et sup\ue9rieures. Nos r\ue9sultats sugg\ue8rent que la qualit\ue9 des graines de coton des branches basales \ue0 la r\ue9colte est sup\ue9rieure \ue0 la qualit\ue9 des graines des branches m\ue9dianes et sup\ue9rieures. Cependant, lorsqu\u2019elles sont soumises au stockage, les graines des branches basales pr\ue9sentent des changements de d\ue9t\ue9rioration plus \ue9lev\ue9s que ceux obtenus des branches moyenne et sup\ue9rieure. Cela pourrait \ueatre li\ue9 \ue0 la dur\ue9e du d\ue9veloppement des graines et \ue0 l\u2019augmentation des fuites de solut\ue9 apr\ue8s l\u2019imbibition, qui s\u2019accompagne g\ue9n\ue9ralement d\u2019une fuite in\ue9vitable des m\ue9tabolites n\ue9cessaires \ue0 la germination et \ue0 la croissance normale des semis

Comparing a standardized to a product-specific emoji list for evaluating food products by children

submittedVersio

Data for: Development of a land use regression model for black carbon using mobile monitoring data and its application to pollution-avoiding routing

The file land_use_features_BC.csv is csv-file containing the features used for building the land use regression model at each Point Of Interest (POI), as well as the alpha-trimmed mean (background corrected) black carbon concentrations at that POI. Note that the background has been subtracted, so if an estimate of the 'true' mean BC concentration is needed, 2.3 µg/m³ should be added to these values.** Import data into R-software using the following instruction:theData = read.table("land_use_features_BC.csv", sep=",", header=TRUE)** description of variables: - each row represents one point of interest (POI) - description of variables: - POI_number: reference number - BC_concentration_background_corrected: background corrected black carbon concentration at that POI. Reported values are alpha-trimmed means that are backgrond-corrected (see paper) - geometry_lambert_coordinates: Geospatial coordinates of the POIs (using the Lambert 72 coordinate system) - distance_motorway: distance (m) of POI to nearest motorway - nr_houses_100m: number of houses within a radius of 100m around the POI - .

Data for: Development of a land use regression model for black carbon using mobile monitoring data and its application to pollution-avoiding routing

The file land_use_features_BC.csv is csv-file containing the features used for building the land use regression model at each Point Of Interest (POI), as well as the alpha-trimmed mean (background corrected) black carbon concentrations at that POI. Note that the background has been subtracted, so if an estimate of the 'true' mean BC concentration is needed, 2.3 µg/m³ should be added to these values.** Import data into R-software using the following instruction:theData = read.table("land_use_features_BC.csv", sep=",", header=TRUE)** description of variables: - each row represents one point of interest (POI) - description of variables: - POI_number: reference number - BC_concentration_background_corrected: background corrected black carbon concentration at that POI. Reported values are alpha-trimmed means that are backgrond-corrected (see paper) - geometry_lambert_coordinates: Geospatial coordinates of the POIs (using the Lambert 72 coordinate system) - distance_motorway: distance (m) of POI to nearest motorway - nr_houses_100m: number of houses within a radius of 100m around the POI - ..THIS DATASET IS ARCHIVED AT DANS/EASY, BUT NOT ACCESSIBLE HERE. TO VIEW A LIST OF FILES AND ACCESS THE FILES IN THIS DATASET CLICK ON THE DOI-LINK ABOV

Milk fatty acids as possible biomarkers to early diagnose elevated concentrations of blood plasma nonesterified fatty acids in dairy cows

Most cows encounter a state of negative energy balance during the periparturient period, which may lead to metabolic disorders and impaired fertility. The aim of this study was to assess the potential of milk fatty acids as diagnostic tools of detrimental levels of blood plasma nonesterified fatty acids (NEFA), defined as NEFA concentrations beyond 0.6 mmol/L, in a data set of 92 early lactating cows fed a glucogenic or lipogenic diet and subjected to 0-, 30-, or 60-d dry period before parturition. Milk was collected in wk 2, 3, 4, and 8 (n = 368) and blood was sampled weekly from wk 2 to 8 after parturition. Milk was analyzed for milk fatty acids and blood plasma for NEFA. Data were classified as “at risk of detrimental blood plasma NEFA” (NEFA =0.6 mmol/L) and “not at risk of detrimental blood plasma NEFA” (NEF

Milk fatty acids as possible biomarkers to diagnose hyperketonemia in early lactation

The aim of this study was to assess the potential of milk fatty acids as diagnostic tool for hyperketonemia of 93 dairy cows in a 3 × 2 factorial arrangement. Cows were fed a glucogenic or lipogenic diet and originally were intended to be subjected to a 0-, 30-, or 60-d dry period. Nevertheless, some of the cows, which were intended for inclusion in the 0-d dry period group, dried off spontaneously. Milk was collected in wk 2, 3, 4, and 8 of lactation for milk fat analysis. Blood was sampled from wk 2 to 8 after parturition for ß-hydroxybutyrate (BHBA) analysis. Cases were classified into 2 groups: hyperketonemia (BHBA =1.2 mmol/L) and nonhyperketonemia (BHB