We constructed a detailed heat balance model for a sparse canopy, which allowed the interaction of heat flux between soil and vegetation, and set the values of various parameters for the model based on observation data, obtained from a wheat field covered sparsely by vegetation (plant height, 0.52 m; leaf area index, 1.2) between 1100 and 1400 h on July 12–14. Using this model, we examined the effect of soil surface wetness (volumetric soil moisture in the top 2 cm layer θ, 13.7 % or 22.3 %) and air temperature (23 °C or 27 °C) on transpiration from vegetation under a given condition (solar radiation, 850 Wm-2; atmospheric radiation, 350 Wm-2; specific humidity, 0.013 kgkg-1). As a result, it was found that transpiration increased 1.41–1.46 times as air temperature rose by 4 °C under the same condition of soil surface wetness, and increased 1.14–1.17 times as soil surface changed from wet (θ, 22.3 %) to dry (θ, 13.7 %) condition at the same air temperature. The ratio of transpiration to evapotranspiration was 0.42–0.49 when the soil surface was wet, and 0.71–0.75 when the soil surface was dry.
Resource cycling in animal production systems is important for promoting home-grown feeds and utilization of animal excreta in the systems. The cycling in the systems is needed to be evaluated as the numerical indicator of the cycling. Recently, Finn's cycling index developed in ecology has been introduced to the animal production systems as the indicator of element cycling in the systems. The index is applicable in the animal production systems and useful tool as an evaluation index. Therefore, the properties of the cycling index were confirmed for interpretation of the index in this study. Cycling index was defined as the ratio of internal cycling flow to the total system flow. It varies from 0 to 1, 0 meaning that there is no cycling and 1 meaning that all flow is cycled. Element cycling in dairy and beef production systems were evaluated using cycling index on the previous reports. The effects of model assumption on the cycling index were discussed. The difference in the indices between two types of input (import and import plus natural supply) was confirmed. Comparison of the cycling index in the two types of input indicated that cycling index was higher in the former type than in the latter type. Furthermore, change in cycling indices was discussed on the different number of components constructing the same system. The cycling index on the 2-5 component systems indicated no difference among the 2-4 component systems including the same flow path. This study provides useful information on the properties for the cycling index and in comparison of the index among case studies.
Continuous rapid economic of China has growth has improved their quality of life which has caused the increasing of food waste in municipal solid waste (MSW), but waste treatment infrastructure has not developed in China. There is no collection system of source separated recyclable materials in China, that make MSW treatment more difficult, due to the nature of organic or biodegradable waste, it generally spoils easily, decomposes rapidly and generates odoriferous gases. Composting curtails environmental pollution, reduces randfilling wastes, and limits greenhouse gas emission. Therefore, composting the organic or biodegradable waste in MSW thought to be the most suitable and effective treatment method. But, now, there is no composting treatment system in China, thus a good quality composting technology is needed.Chinese MSW includes not only domestic waste but also industrial food waste which may contain high percentage of oil which may inhibit soil microorganism growth. For producing safety food waste compost, oil degradability thorough composting process must be clarified.This study aimed to clarify oil degradability in food waste by composting and its effects on plant growth. It was found that food waste could contain 43％(dried weight material) of oil, 85~97％ of which decomposed; final products contained only 0.9％(dried weight material). Moreover, food waste could contain 8％(dried weight material) of salt and 14％(dried weight material) of oil, oil decomposed less than 1.5％.
In this study, we analyzed the relationship between cultivation method of potted cyclamen and duration of the quality maintenance period. The cultivation method is a combination of cultivation technologies and is different from the single cultivation technology. The quality maintenance period is defined as the period when a consumer can enjoy the cyclamen flower. Several potted cyclamens from different producers were placed in the same environment. We determined the quality maintenance period by evaluating the enjoyment value of the cyclamens. The relationship between cultivation method and quality maintenance period was analyzed using the quantification theory typeⅠ. The cultivation methods that influenced the quality maintenance period included the kind of potting soil, the temperature setting one month before shipping, and the covering rate in summer. Moreover, the cultivation methods found to influence the quality maintenance period were different between the period when initial quality was maintained and all the periods when a consumer could enjoy the cyclamen. These results suggest that it is possible for farmers to use certain cultivation methods to produce cyclamens with a typical quality maintenance period for specific purposes such as gifts and family use.
For the high accuracy estimation of rice yield, multiple linear regression is suitable using remote sensing data by weighting data, and the weights may differ between current year and past years. In addition, the weights of past years may vary somewhat. A probabilistic optimization method is attempted to optimize weights. Multiple linear equation is used as regression equation. The result shows that as far as the data at hand is concerned, the different weights for past years data augment predictive error. The same weight for current year data and past years’ data gives the minimum predictive error. This is a typical example of deteriorating predictability by over-fitting responsible for over-parameterization. However, a shrinkage method for the optimal weights can make the predictive error smaller than that given by equal weights.