• LCA was conducted on ethanol production from sugarcane grown on small-scale farms.• Fossil fuel energy input and GHG emission were assessed using local and regional data.• 6.9-7.2 MJ and 0.62-0.6... Fossil fuel energy consumption and greenhouse gas emissions were estimated in cropping systems of sugarcane (Saccharum officinarum L.) and the subsequent production of ethanol in order to evaluate ...

The Global Yield Gap Atlas (GYGA) is an international project that addresses global food production capacity in the form of yield gaps (Yg). The GYGA project is unique in employing its original Climate Zonation Scheme (CZS) composed of three indexed factors, i.e. Growing Degree Days (GDD) related to temperature, Aridity Index (AI) related to available water and Temperature Seasonality (TS) related to annual temperature range, creating 300 Climate Zones (CZs) theoretically across the globe. In the present study, the GYGA CZs were identified for Japan on a municipality basis and analysis of variance (ANOVA) was performed on irrigated rice yield data sets, equating to actual yields (Ya) in the GYGA context, from long-term government statistics. The ANOVA was conducted for the data sets over two decades between 1994 and 2016 by assigning the GDD score of 6 levels and the TS score of 2 levels as fixed factors. Significant interactions with respect to Ya were observed between GDD score and TS score for 13 years out of 21 years implying the existence of favourable combinations of the GDD score and the TS score for rice cultivation. The implication was also supported by the observation with Yg. The lower values of coefficient of variance obtained from the CZs characterized by medium GDD scores indicated the stability over time of rice yields in these areas. These findings suggest a possibility that the GYGA-CZS can be recognized as a tool suitable to identify favourable CZs for growing crops.

Positive mathematical programming (PMP) has a substantial number of applications in the field of agricultural and resource economics. Their focus has often been placed on the simulation analysis of farmers’ response to drastic changes in exogenous factors especially brought about by policy changes. In the present study, an exploration was made to widen the application area of the PMP approach, targeting farmers’ expectation toward the farm-gate price of rice in comparison with that of wheat under the policy to suppress overproduction. When domestic consumption is mature and the regulation of production by the government is present, farmers’ expectation toward the farm-gate price of a crop can be assumed to fall in response to an increased allocation of land area to produce the crop. The degree of the fall is defined as the expectation fall index (EFI) in the present study. A proposition was made as to the procedure for quantifying EFI using the PMP approach with statistical datasets of multiple years retrieved from the Ministry of Agriculture, Forestry, and Fisheries. The present study is considered to have provided a basis to discuss the formation processes of farmers’ attitudes toward policy measures.