In recent years, it is required to establish environmentally friendly agricultural production systems. In this study, environmental impacts of dairy production including different types of feed production systems were evaluated by Life Cycle Assessment method according to “Agricultural Production Technology Systems” created by Hokkaido and Iwate Prefecture. Four types of feed production (hay, low moisture herbage roll silage cutting three times annually, pasture, maize silage) in Hokkaido and two types of feed production (herbage roll silage cutting three times annually and maize silage) in Iwate were analyzed according to three types of fertilizer application (chemical fertilizer only, together with manure and together with slurry), respectively. These results were included into environmental impact assessment of dairy productions which consists of four types (40, 60,100 and 400 head size) of production systems in Hokkaido and 2 types (40 and 100 head size) in Iwate. Global warming load (GWL), acidification load (AL) and eutrophication load (EL) were evaluated. The results showed that the environmental impact of dairy production was lower in the types of organic fertilizer use, even though the impact of organic fertilizer use was higher in case of feed production. AL was higher in Iwate and EL was higher in Hokkaido while there was no significant difference in GWL. Large scale production systems had lower environmental impact. The result of integrated environmental impact potential by LIME2 (Life cycle Impact assessment Method based on Endpoint modeling 2) showed that the AL by ammonia had the highest contribution in economic damage amount. As a consequence, the results suggest that the selection of organic fertilizer in feed production in order to contribute to the utilization of animal excrements and the effective production systems by the efficient machinery use will contribute to the reduction of environmental impact in dairy production.
Measures for restoring farmland damaged in the 2016 Kumamoto Earthquake vary according to the degree of damage. Therefore, we investigated the damage caused by the 2016 Kumamoto earthquake to the surface of the farmland using drones. We made three-dimensional models using SfM, MVS processing on drone aerial images and made DSMs by calibrating altitude levels with Geographical Survey Institute and ground surveying results together. As a result, it was possible to measure the quantity of unevenness (difference from a mean altitude level of the farmland ground). After comparing it with the airborne laser surveying, the quantity of unevenness which drones measured had the high precision that a meaningful difference was not recognized. On the other hand, the measurement cost of the drone in this case is about 1/3 of the airborne laser surveying, and there are advantages that drone observation is possible more quickly, more conveniently. Furthermore, we investigated a cause of the wavy surface confirmed by drone observation. Aerial photographs from 1962 showed that the unevenness corresponded with creeks buried by infrastructure maintenance. We reveal that the 2016 Kumamoto earthquake caused the creek part to sink.
Destructive inspection by technical institution is mainstream at the component analysis of crops in Japanese agriculture. However, destructive inspection increases costs as the number of times increases and which may affect the yield. Therefore, it is necessary to establish a nondestructive component analysis method. In this paper, we studied the ingredient analysis method of nondestructive using hyperspectral data. We analyzed the correlation coefficient between the spectrum data obtain from hyper spectrum camera and the components in iceberg lettuce which is gained by destructive inspection. We determined the useful wavelength by the correlation of the spectrum with component contained in iceberg lettuce. However, there is a high correlation between calcium and magnesium component data. Therefore, application of this method has limitations. In the future work, verification of valid two band combinations using the normalized spectral index (NDSI) is necessary.