This study estimated the supplementary water capacity for paddy fields by estimating the water supply in each province during the dry season. Northeast Thailand was selected for this analysis because of the availability of agricultural statistical data distinguishing irrigated rice fields and non-irrigated rice fields during the dry season. This region is in Monsoon Asia, and so the climate has two seasons: the dry season and the wet season. Since about 70% of the annual rainfall is concentrated in the wet season, rice cannot be produced using only the dry season precipitation. In other words, farmers must obtain water from some other source to supply water to their paddy fields when growing rice in the dry season. Water is supplied from dam reservoirs in the irrigated rice fields, and water is supplied to the non-irrigated rice fields by gravity and small pumps from small ponds and canals. Thus, it was assumed that the amount of water supplied to paddy fields during the dry season can be calculated by subtracting rainwater during the dry season from the amount of water used in paddy fields. Based on rice production data, the values of water resources required to produce a unit weight of rice and rainwater, attempts were made to estimate the supplementary water capacities to paddy fields from the estimated supplied water and its maximum values in each province. Because there is no data for small ponds and canals for non-irrigated paddy fields in each province, the validity of the values estimated from the agricultural statistics was examined by comparing the supply water capacities for irrigated paddy fields estimated from the statistical data with those calculated from the Royal Irrigation Department data for large- and medium-scale reservoirs in each province. As a result, both differences tended to be less than 1 mm in the provinces whose harvested area of irrigated rice was small. It was therefore considered that supplementary water capacities to the non-irrigated paddy fields in each province can be estimated by the same method as for the irrigated paddy fields because it was assumed that the actual situation was similar to the non-irrigated paddy fields even if the classification of the rice fields was “irrigated”. As a result, the supplementary water capacity tended to be high in the provinces through which the Chi River flows and the province upstream of the Mun River.
Indices and procedures for identifying market trends about any fruit or vegetable are provided in this paper. This system is quite simple and easy for planners of any marketing organization of fruits-and-vegetables producers to operate it and make use of its result when they discuss their strategies. It also has a high degree of availability because it requires just only transaction data at any wholesale market of fruits and vegetables. This system deals with the demand change as the shift of demand curve, the change of the marketing brand power as the shift of certain curve derived from (Yoshino 1997), and the competitive power in cost as the supply response of each producers' organization. When any change of demand curve or brand-power curve would shift too rapidly to be estimate significantly, this system provides a simplified method and enhance the availability with it, which could identify the change of demand or marketing-brand power through observed change of prices and supplies. An example of this system embodied with Microsoft Excel and some analyses using it are mentioned.
This paper aims at evaluating the agricultural land use changes occurring during a 14 year-period (1987 to 2001) in Comayagua County, Honduras, through the use of Remote Sensing and field survey data. Since lack of statistical data constitutes the main constraint to perform such evaluation in Honduras, remote sensed data of Landsat TM (Thematic Mapper) and ETM+(Enhanced Thematic Mapper Plus) were used to perform imagery analysis on land use change for the periods 1987, 1994 and 2001. Moreover, paying attention to the detected land use change patterns, a field survey was conducted to study the agricultural policies implemented and farmers’ characteristics, and based on those results an analysis regarding the factors influencing land use change was carried out. Results indicate that during the study period, changes in agricultural policies led to cropland expansion and conversion from traditional crops such as maize, beans and livestock farming to high value crops centered on vegetables for export. Parallel to this process, concerns such as immigration from less developed areas, forest clearing, increasing shifting agriculture and land abandonment also took place. The evaluation suggests that when policies are implemented to promote agricultural production and exports, there should be at the same time strengthening of policies on resource management to prevent deforestation and land abandonment, and ensure agricultural sustainability.
A GIS database was developed to evaluate land and water resources in a rainfed agricultural area in northeast Thailand using high resolution satellite data. In a small watershed, buffer analysis on the layout of a small-scale on-farm pond in paddy field area own by farming households was performed. By quantifying the pond capacity and the distribution degree, the potential water availability concerning the relationship between pond and paddy field layout was examined. Indices for evaluating the pond distribution (Dp) and the capacity (Cp) were proposed; these indices were integrated aswater use availability (Awu). The methodologies were applied to 10 farming households in the small watershed. The result shows that there is enough room for the improvement of water use availability by arranging ponds or ensuring greater pond capacity. The active usage of ponds was recognized among farming households for which the ponds had high availability.
In recent years, Differential Evolution (DE) algorithm has been proposed as a technique for optimizing large and complex models. In this study, an energy consumption model for integration between beef cattle and feed production was optimized using DE. The optimum levels of 5 variables (roughage-concentrate ratio, stocking rate (animals/ha), daily body weight gain, final weight for fattening and TDN content of roughage) were determined by maximizing fossil energy efficiency. The result confirmed that fossil energy efficiency can be enhanced by supplying more high quality roughage and slaughtering high growth animals at younger age. Furthermore, the effects of DE control variables (crossover probability (CR) and weighting factor (F) applied to the mutation process) were examined under two strategies (DE/best/1/exp and DE/rand/1/bin) in Storn and Price's strategies. The criteria for evaluation were the speed of convergence and stability of solutions. As a result, it was suggested that the good choices of the control variables were 0.75 and 0.5 in DE/best/1/exp and 0.5 and 0.5 in DE/rand/1/bin, respectively.