282 research outputs found
Interseeding Plans for SDSU\u27s New Machine . . . For Better Pasture Production
This bulletin deals with the merits of interseeding, its practice in South Dakota, and the development and use of interseeders by South Dakota State University
Beef cows and calves, 1979: a summary of research
Response of fall-born calves to monensin on orchardgrass / alfalfa or tall fescue / alfalfa pastures / F. M. Byers, C. F. Parker, and R. W. Van Keuren -- Effects of forage system and breed type on the performance of fall calving cows / C. F. Parker and R. W. Van Keuren -- Forage management for beef production / R. W. Van Keuren, C. F. Parker, and E. W. Klosterman -- Breeding and management systems to optimize beef breeding herd productivity / E. W. Klosterman, R. W. Van Keuren, C. F. Parker, and F. M. Byers -- Voluntary feed intake of mature cows as related to breed type, condition, and forage quality / E. W. Klosterman, F. M. Byers, and C. F. Parker -- Weight and condition changes of pregnant beef cows wintered on corn stover stacks / G. R. Wilson, J. G. Gordon, J. H. Cline, K. M. Irvin, and E. W. Klosterman -- Estrus synchronization of beef cows and heifers with prostaglandin F2a under field conditions / G. R. Wilson, T. L. Benecke, K. M. Irvin, T. M. Ludwick, C. E. Marshall, and R. A. Wallac
Tracking forest phenology and seasonal physiology using digital repeat photography: a critical assessment
A single-nucleotide mutation in GLUTAMATE RECEPTOR-LIKE protein gene confers resistance to Fusarium wilt in Gossypium hirsutum
Fusarium wilt (FW) disease of cotton, caused by the fungus Fusarium oxysporum f. sp. vasinfectum (Fov), causes severe losses in cotton production worldwide. Though significant advancements have been made in development of FW‐resistant Upland cotton (Gossypium hirsutum) in resistance screening programs, the precise resistance genes and the corresponding molecular mechanisms for resistance to Fov remain unclear. Herein it is reported that Fov7, a gene unlike canonical plant disease‐resistance (R) genes, putatively encoding a GLUTAMATE RECEPTOR‐LIKE (GLR) protein, confers resistance to Fov race 7 in Upland cotton. A single nucleotide polymorphism (SNP) (C/A) in GhGLR4.8, resulting in an amino acid change (L/I), is associated with Fov resistance. A PCR‐based DNA marker (GhGLR4.8SNP(A/C)) is developed and shown to cosegregate with the Fov resistance. CRISPR/Cas9‐mediated knockout of Fov7 results in cotton lines extremely susceptible to Fov race 7 with a loss of the ability to induce calcium influx in response to total secreted proteins (SEPs) of Fov. Furthermore, coinfiltration of SEPs with GhGLR4.8A results in a hypersensitive response. This first report of a GLR‐encoding gene that functions as an R gene provides a new insight into plant–pathogen interactions and a new handle to develop cotton cultivars with resistance to Fov race 7
Deriving the number of jobs in proximity services from the number of inhabitants in French rural municipalities
We use a minimum requirement approach to derive the number of jobs in
proximity services per inhabitant in French rural municipalities. We first
classify the municipalities according to their time distance to the
municipality where the inhabitants go the most frequently to get services
(called MFM). For each set corresponding to a range of time distance to MFM, we
perform a quantile regression estimating the minimum number of service jobs per
inhabitant, that we interpret as an estimation of the number of proximity jobs
per inhabitant. We observe that the minimum number of service jobs per
inhabitant is smaller in small municipalities. Moreover, for municipalities of
similar sizes, when the distance to the MFM increases, we find that the number
of jobs of proximity services per inhabitant increases.Comment: 6 pages, 5 figure
Earth observation for sustainable urban planning in developing countries: needs, trends, and future directions
Abstract: Cities are constantly changing and authorities face immense challenges in obtaining accurate and timely data to effectively manage urban areas. This is particularly problematic in the developing world where municipal records are often unavailable or not updated. Spaceborne earth observation (EO) has great potential for providing up-to-date spatial information about urban areas. This article reviews the application of EO for supporting urban planning. In particular, the article overviews case studies where EO was used to derive products and indicators required by urban planners. The review concludes that EO has sufficiently matured in recent years but that a shift from the current focus on purely science-driven EO applications to the provision of useful information for day-to-day decision-making and urban sustainability monitoring is clearly needed
Tracking vegetation phenology across diverse North American biomes using PhenoCam imagery
Vegetation phenology controls the seasonality of many ecosystem processes, as well as numerous biosphere-atmosphere feedbacks. Phenology is also highly sensitive to climate change and variability. Here we present a series of datasets, together consisting of almost 750 years of observations, characterizing vegetation phenology in diverse ecosystems across North America. Our data are derived from conventional, visible-wavelength, automated digital camera imagery collected through the PhenoCam network. For each archived image, we extracted RGB (red, green, blue) colour channel information, with means and other statistics calculated across a region-of-interest (ROI) delineating a specific vegetation type. From the high-frequency (typically, 30 min) imagery, we derived time series characterizing vegetation colour, including “canopy greenness”, processed to 1- and 3-day intervals. For ecosystems with one or more annual cycles of vegetation activity, we provide estimates, with uncertainties, for the start of the “greenness rising” and end of the “greenness falling” stages. The database can be used for phenological model validation and development, evaluation of satellite remote sensing data products, benchmarking earth system models, and studies of climate change impacts on terrestrial ecosystems
Evolutionary Modeling and Prediction of Non-Coding RNAs in Drosophila
We performed benchmarks of phylogenetic grammar-based ncRNA gene prediction, experimenting with eight different models of structural evolution and two different programs for genome alignment. We evaluated our models using alignments of twelve Drosophila genomes. We find that ncRNA prediction performance can vary greatly between different gene predictors and subfamilies of ncRNA gene. Our estimates for false positive rates are based on simulations which preserve local islands of conservation; using these simulations, we predict a higher rate of false positives than previous computational ncRNA screens have reported. Using one of the tested prediction grammars, we provide an updated set of ncRNA predictions for D. melanogaster and compare them to previously-published predictions and experimental data. Many of our predictions show correlations with protein-coding genes. We found significant depletion of intergenic predictions near the 3′ end of coding regions and furthermore depletion of predictions in the first intron of protein-coding genes. Some of our predictions are colocated with larger putative unannotated genes: for example, 17 of our predictions showing homology to the RFAM family snoR28 appear in a tandem array on the X chromosome; the 4.5 Kbp spanned by the predicted tandem array is contained within a FlyBase-annotated cDNA
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