11 research outputs found
Plastocrono e nÚmero final de nÃģs de cultivares de soja em funçÃĢo da ÃĐpoca de semeadura
Estimativa da ÃĄrea de folhas de cultivares antigas e modernas de soja por mÃĐtodo nÃĢo destrutivo
Remote sensing-based information and insurance for crop in emerging economics in Thailand (in Thai)
The Remote Sensing-based Information and Insurance for Crops in Emerging Economics (RIICE) is a project to find ways of helping Asian countries are faced with a natural disaster. Especially floods and droughts caused by the cooperation of the three organizations, namely International Research Institute (IRRI), SARMAP and Rice Department. By the year 2013-2015 in the area of responsibility of Suphan Buri Rice Research Center. Nakhon Ratchasrima Rice Research Center and the objecttive of the project is to reduce vulnerability of smallholders in rice production through better and cheaper information systems on crop growth which will in turn lead to applications such as micro-insurance schemes. On the long run rice production should have increased, thanks to better weather forecast in drought and flood prone areas and therefore better land management by farmers.In the year 2013 in Nakhon Ratchasima, using satellite COSMO Skymed, type stripmap, resolution 3-meter, width of the image 40x40 kilometers. In Suphanburi, using satellite COSMO Skymed, type scansar resolution of 15 meters, the width of the image 100x100 kilometers. In each field survey was conducted, collectting geographic coordinates, Managing of farmers, Environment and weather of 20 plots in each province. Leaf area index, crop cutting. After the end of the growing season, we survey in the fields if it was paddy field or non-paddy, totally of 100 points with the geographic coordinates to assess the accuracy of a program MapSCAPE Performance in 2013 for satellite imagery. The result of 2013 are, getting 7 imageries from Suphanburi, 11 imageries from Nakhon Ratchasima, They could be classified into cultivated area, flooded areas, The start of the growing season.The precision of the program by using Confusion Matrix computation, we found that the accurancy of the program in Suphanburi is 87.7%āđāļāļĢāļāļāļēāļĢ Remote Sensing-based Information and Insurance for Crops in Emerging Economics (RIICE) āđāļāđāļāđāļāļĢāļāļāļēāļĢāļŦāļēāđāļāļ§āļāļēāļāđāļāļāļēāļĢāļāđāļ§āļĒāđāļŦāļĨāļ·āļāļāļĢāļ°āđāļāļĻāļāļēāļāđāļāļāđāļāđāļāļĩāļĒāļāļĩāđāļāļģāļĨāļąāļāļāļĢāļ°āļŠāļāļāļąāļāļāļąāļāļŦāļēāļ āļąāļĒāļāļĢāļĢāļĄāļāļēāļāļī āđāļāļĒāđāļāļāļēāļ°āļāļļāļāļāļ āļąāļĒ āđāļĨāļ°āļ āļąāļĒāđāļĨāđāļ āđāļāļĒāđāļāļīāļāļāļēāļāļāļ§āļēāļĄāļĢāđāļ§āļĄāļĄāļ·āļāļāļāļ 3 āļāļāļāđāļāļĢāļŦāļĨāļąāļ āđāļāđāđāļāđ International Research Institute(IRRI), SARMAP āđāļĨāļ°āļāļĢāļĄāļāļēāļĢāļāđāļēāļ§ āđāļāļĒāļāļģāđāļāļīāļāļāļēāļĢāļāļĩ 2556-2558 āđāļāļāļ·āđāļāļāļĩāđāļĢāļąāļāļāļīāļāļāļāļāļāļāļāļĻāļđāļāļĒāđāļ§āļīāļāļąāļĒāļāđāļēāļ§āļŠāļļāļāļĢāļĢāļāļāļļāļĢāļĩ āđāļĨāļ°āļĻāļđāļāļĒāđāļ§āļīāļāļąāļĒāļāđāļēāļ§āļāļāļĢāļĢāļēāļāļŠāļĩāļĄāļē āđāļāļĒāļĄāļĩāļ§āļąāļāļāļļāļāļĢāļ°āļŠāļāļāđāđāļāļ·āđāļ āļĨāļāļāļ§āļēāļĄāđāļŠāļĩāđāļĒāļāļāļāļāđāļāļĐāļāļĢāļāļĢāļĢāļēāļĒāļĒāđāļāļĒāđāļāļāļēāļĢāļāļĨāļīāļāļāđāļēāļ§āđāļāļĒāđāļŦāđāđāļāđāļĢāļąāļāļāđāļāļĄāļđāļĨāļāđāļēāļāļāļēāļĢāļāļĨāļīāļāļāļ·āļ āļāļ·āđāļāļāļĩāđāļāļĨāļđāļāļāđāļēāļ§āļāļĩāđāļāļĩāļāļ§āđāļēāđāļĨāļ°āđāļĄāđāļāļĒāļģ āļ§āļīāļāļĩāļāļēāļĢāļāļģāđāļāļīāļāļāļēāļāļāļĩ āļ.āļĻ.2556 āļāļąāļāļŦāļ§āļąāļāļāļāļĢāļĢāļēāļāļŠāļĩāļĄāļē āđāļāđāļ āļēāļāļāđāļēāļĒāļāļēāļ§āđāļāļĩāļĒāļĄ COSMO Skymed āļāļĢāļ°āđāļ āļ stripmap āļāļ§āļēāļĄāļĨāļ°āđāļāļĩāļĒāļāļāļāļāļ āļēāļ 3 āđāļĄāļāļĢ āļāļ§āļēāļĄāļāļ§āđāļēāļāļāļāļāļ āļēāļ 40x40 āļāļīāđāļĨāđāļĄāļāļĢ āļāļąāļāļŦāļ§āļąāļāļŠāļļāļāļĢāļĢāļāļāļļāļĢāļĩ āđāļāđāļ āļēāļāļāđāļēāļĒāļāļēāļ§āđāļāļĩāļĒāļĄ COSMO Skymed āļāļĢāļ°āđāļ āļ scansar āļāļ§āļēāļĄāļĨāļ°āđāļāļĩāļĒāļāļāļāļāļ āļēāļ 15 āđāļĄāļāļĢ āļāļ§āļēāļĄāļāļ§āđāļēāļāļāļāļāļ āļēāļ 100x100 āļāļīāđāļĨāđāļĄāļāļĢ āđāļāđāļāđāļĨāļ°āļāļąāļāļŦāļ§āļąāļāđāļāđāļāļģāđāļāļīāļāļāļēāļĢāļŠāļģāļĢāļ§āļ āđāļāđāļāļāļīāļāļąāļāļāļēāļāļ āļđāļĄāļīāļĻāļēāļŠāļāļĢāđ āļāļēāļĢāļāļąāļāļāļēāļĢāđāļāļĨāļāļāļāļāđāļāļĐāļāļĢāļāļĢ āļŠāļ āļēāļāđāļ§āļāļĨāđāļāļĄāđāļĨāļ°āļŠāļ āļēāļāļāļēāļāļēāļĻ āļāļģāļāļ§āļ 20 āđāļāļĨāļāđāļāđāļāđāļĨāļ°āļāļąāļāļŦāļ§āļąāļ āđāļāđāļāļāđāļāļĄāļđāļĨāļāļąāļāļāļĩāļāļ·āđāļāļāļĩāđāđāļāļāđāļēāļ§ āļāļĨāļāļĨāļīāļāļāđāļēāļ§āđāļāđāļāļĨāļāđāļāļĐāļāļĢāļāļĢ āļŦāļĨāļąāļāļāļēāļāļŠāļīāđāļāļŠāļļāļāļĪāļāļđāļāļĨāļđāļāļāļģāļāļēāļĢāļŠāļģāļĢāļ§āļāļāļ·āđāļāļāļĩāđāļāļēāļāđāļēāļ§ āđāļĨāļ°āđāļĄāđāđāļāđāļāļēāļāđāļēāļ§ āļāļģāļāļ§āļ 100 āļāļļāļ āļāļąāļāļāļķāļāļāļīāļāļąāļāļāļēāļāļ āļđāļĄāļīāļĻāļēāļŠāļāļĢāđ āđāļāļ·āđāļāļāļģāđāļāļāļĢāļ°āđāļĄāļīāļāļāļ§āļēāļĄāđāļĄāđāļāļĒāļģāļāļāļāđāļāđāļāļĢāļĄ MapSCAPE āļāļĨāļāļēāļĢāļāļģāđāļāļīāļāļāļēāļāđāļāļāļĩ 2556 āđāļāđāļ āļēāļāļāđāļēāļĒāļāļēāļ§āđāļāļĩāļĒāļĄāļāļāļāļāļąāļāļŦāļ§āļąāļāļŠāļļāļāļĢāļĢāļāļāļļāļĢāļĩ āļāļģāļāļ§āļ 7 āļ āļēāļ āļāļąāļāļŦāļ§āļąāļāļāļāļĢāļĢāļēāļāļŠāļĩāļĄāļē āļāļģāļāļ§āļ 11 āļ āļēāļ āđāļāđāļāļģāļ āļēāļāļāđāļēāļĒāļĄāļēāđāļāļĨāđāļāļ·āđāļāđāļŠāļāļāļāļ·āđāļāļāļĩāđāļāļĨāļđāļāļāđāļēāļ§ āļāļ·āđāļāļāļĩāđāļāļđāļāļāđāļģāļāđāļ§āļĄ āļāļēāļĢāđāļĢāļīāđāļĄāļĪāļāļđāļāļĨāļđāļāļāđāļēāļ§āļāļāļāļāļąāđāļ 2 āļāļąāļāļŦāļ§āļąāļ āđāļāļĒāđāļāđāđāļāļĢāđāļāļĢāļĄ MapSCAPE 5.0 āļāļĢāļ°āļĄāļ§āļĨāđāļĨāļ°āđāļŠāļāļāļāļ·āđāļāļāļĩāđāļāļĨāļđāļāļāđāļēāļ§ āļāļēāļāļāļēāļĢāļ§āļīāđāļāļĢāļēāļ°āļŦāđāļāļ§āļēāļĄāđāļĄāđāļāļĒāļģāļāļēāļāļāļēāļĢāđāļāļĨāļ āļēāļāļāđāļēāļĒāļāļēāļ§āđāļāļĩāļĒāļĄ āđāļāļĒāđāļāđ Confusion Matrix Computation āļāļāļ§āđāļēāļāļēāļĢāđāļāļĨāļ āļēāļāļāļāļāļāļąāļāļŦāļ§āļąāļāļŠāļļāļāļĢāļĢāļāļāļļāļĢāļĩāļĄāļĩāļāļ§āļēāļĄāđāļĄāđāļāļĒāļģ 87.1
CO2-response function of radiation use efficiency in rice for climate change scenarios
The objective of this work was to evaluate a generalized response function to the atmospheric CO2 concentration [f(CO2)] by the radiation use efficiency (RUE) in rice. Experimental data on RUE at different CO2 concentrations were collected from rice trials performed in several locations around the world. RUE data were then normalized, so that all RUE at current CO2 concentration were equal to 1. The response function was obtained by fitting normalized RUE versus CO2 concentration to a Morgan-Mercer-Flodin (MMF) function, and by using Marquardt's method to estimate the model coefficients. Goodness of fit was measured by the standard deviation of the estimated coefficients, the coefficient of determination (RÂē), and the root mean square error (RMSE). The f(CO2) describes a nonlinear sigmoidal response of RUE in rice, in function of the atmospheric CO2 concentration, which has an ecophysiological background, and, therefore, renders a robust function that can be easily coupled to rice simulation models, besides covering the range of CO2 emissions for the next generation of climate scenarios for the 21st century
An operational remote sensing based service for rice production estimation at national scale
Comparing two versions of a non-linear model for simulating leaf number and developmental stages in maize based on air temperature
State of ex situ conservation of landrace groups of 25 major crops
Crop landraces have unique local agroecological and societal functions and offer important genetic resources for plant breeding.
Recognition of the value of landrace diversity and concern about its erosion on farms have led to sustained efforts to establish
ex situ collections worldwide. The degree to which these efforts have succeeded in conserving landraces has not been compre hensively assessed. Here we modelled the potential distributions of eco-geographically distinguishable groups of landraces of
25 cereal, pulse and starchy root/tuber/fruit crops within their geographic regions of diversity. We then analysed the extent
to which these landrace groups are represented in genebank collections, using geographic and ecological coverage metrics as a
proxy for genetic diversity. We find that ex situ conservation of landrace groups is currently moderately comprehensive on aver age, with substantial variation among crops; a mean of 63%âÂąâ12.6% of distributions is currently represented in genebanks.
Breadfruit, bananas and plantains, lentils, common beans, chickpeas, barley and bread wheat landrace groups are among the
most fully represented, whereas the largest conservation gaps persist for pearl millet, yams, finger millet, groundnut, potatoes
and peas. Geographic regions prioritized for further collection of landrace groups for ex situ conservation include South Asia,
the Mediterranean and West Asia, Mesoamerica, sub-Saharan Africa, the Andean mountains of South America and Central to
East Asia. With further progress to fill these gaps, a high degree of representation of landrace group diversity in genebanks is
feasible globally, thus fulfilling international targets for their ex situ conservatio