農業気象
Online ISSN : 1881-0136
Print ISSN : 0021-8588
ISSN-L : 0021-8588
78 巻, 2 号
選択された号の論文の4件中1~4を表示しています
Full Paper
  • Ryotaro KITAJIMA, Osamu MATSUDA, Toshihiro KUMAMARU, Atsushi KUME
    2022 年 78 巻 2 号 p. 47-55
    発行日: 2022年
    公開日: 2022/04/10
    ジャーナル オープンアクセス
    電子付録
     Rice (Oryza sativa L.) quality and yield are degraded by high temperature, especially at the ripening stage after the heading of panicles. The effect is lethal when the panicle temperature (Tp) is excessively high; therefore, maintaining a low Tp is important to avoid deleterious impacts on the grains. Microclimatic factors and plant physiological elements determine the Tp. One determining factor is the color (or reflectance) of spikelets that constitute the panicle because it determines the absorption of shortwave radiation energy. An additional factor is the panicle position because it influences heat exchange by the wind and input energy from downward shortwave radiation. In this study, inter-strain differences in spikelet color and panicle height at heading were assessed. The Tp of strains differing in panicle color and panicle height were measured with thermocouples. In addition, to estimate the effect of each trait, we adopted a micrometeorological model. Panicle color was quantified using a hyperspectral sensor. Combining the spectral reflectance and spectral radiation, we assessed the effect of panicle color on Tp. The differences in panicle color and panicle position significantly affected Tp. The strain with a dark panicle had a maximum measured Tp about 1.8 °C higher than that of the strain with a light-colored panicle. The Tp of a strain with panicles at higher positions was up to 2.0 °C higher than that of a strain with panicles at lower positions. These relationships were consistent with the model estimates. When shortwave radiation was strong, the difference in Tp between strains showed a positive correlation, suggesting that the temperature difference was associated with shortwave radiation. Therefore, we concluded that rice strains with a brighter panicle color and low panicle position are less prone to deleterious impacts of high temperature because net radiation is reduced.
  • Akihiko ITO, Shimpei INOUE, Motoko INATOMI
    2022 年 78 巻 2 号 p. 56-65
    発行日: 2022年
    公開日: 2022/04/10
    ジャーナル オープンアクセス
    電子付録
     Evaluating regional budgets of methane (CH4), a potent greenhouse gas and short-lived climate forcer, is an important task for future climate management. This study estimated historical CH4 emissions from paddy fields in East Asia by using a process-based terrestrial biogeochemical model driven by climate and land-use data. To capture the range of estimation uncertainty, this study used two CH4 emission schemes, four paddy field maps, and two seasonal inundation methods for a total of 16 simulations. The mean CH4 emission rate during 2000-2015 was estimated to be 5.7 Tg CH4 yr-1, which is similar to statistical inventories and other estimates. However, the large standard deviation (± 3.2 Tg CH4 yr-1) among the simulations implies that serious estimation uncertainties remain. Three factors - CH4 emission scheme, paddy field map, and inundation seasonality - were responsible for the disparity of the estimates. Because of the lack of historical management data, the model simulation did not show a decreasing trend in the agricultural CH4 emissions. A sensitivity analysis for temperature indicated that a 1-2 °C temperature rise (typical warming in mitigation-oriented scenarios) would substantially enhance CH4 emissions. However, a sensitivity analysis for water management indicated that a lower water-table depth would largely mitigate the emission increase. Additional studies to improve agricultural datasets and models for better paddy field management are still needed.
  • Yasuhiro DOI, Yonghee SHIN, Wonsik KIM, Jaewon CHOI, Toshichika IIZ ...
    2022 年 78 巻 2 号 p. 66-77
    発行日: 2022年
    公開日: 2022/04/10
    ジャーナル オープンアクセス
    電子付録
     An unstable supply of commodity crops and associated increases in food prices are recent and growing concerns due to increasing temperatures, changing precipitation patterns and increasing frequencies of some extreme climate events. Agricultural monitoring and forecasting can support national food agencies, international organizations and commercial entities in better responding to anticipated production shocks induced by seasonal climate extremes. The global seasonal crop forecasting service jointly developed in 2018 by the National Agriculture and Food Research Organization (NARO), Japan and the Asia-Pacific Economic Cooperation Climate Center (APCC), South Korea is an emerging and unique example of agricultural forecasting tailored to major commodity crops (maize, rice, wheat and soybean). The present study evaluates the skills of the NARO-APCC yield forecasts in five countries located in the Southern Hemisphere (the 2019/20 season in Australia and Uruguay and the 2018/19 season in Argentina, Brazil and Paraguay), following the previous assessment for the 2019 season in Northern Hemisphere countries. The results reveal that the NARO-APCC forecasts can capture the major characteristics of reported state yields even six months before harvesting, with variations by crop (the correlation coefficients calculated between the forecasted and reported state yields within a country in a season of interest were frequently over 0.8 for maize, rice and wheat and approximately 0.3 for soybean). In three-fifths of the 122 crop-state combinations assessed here, the NARO-APCC forecasts showed smaller forecast errors than those of the simple forecasts derived solely based on the reported yields. The findings of this study emphasize the novelty of long-range crop forecasting, such as the NARO-APCC forecasts that provide yield forecast information available even just after planting. Together, the NARO-APCC forecasts and existing regional crop forecasts contribute to making objective yield forecast information more seamlessly available throughout the season from planting to harvesting than what is currently available.
Research Notes
  • Robert Kennedy SMITH, José A. GUIJARRO, Der-Chen CHANG, Yiming CHE ...
    2022 年 78 巻 2 号 p. 78-87
    発行日: 2022年
    公開日: 2022/04/10
    ジャーナル オープンアクセス
     The northern U.S. Gulf Coast is among the wettest regions in the contiguous United States, with a transition zone from humid to semi-arid climates occurring between the western Gulf Coast and the 100th meridian. As anthropogenic warming induces more frequent extreme wetting events of greater magnitude, a larger proportion of rainfall runs off unsaturated soils rather than being absorbed and replenishing vegetative water supply. This study introduced novel methodology reliant on reconstructed hourly precipitation intensity data from locations with comprehensive records from the past four decades, incorporating these records into a recursive algorithm measuring daily soil moisture levels. To account for runoff, curtailment multipliers for three different soil classes at each site were applied to 24-hour precipitation totals. Soil moisture balance was then obtained from daily evapotranspiration and infiltrated precipitation, and trends from the autoregressive time series modeling were compared. When runoff quantified by the methodology was considered, average annual soil moisture scarcity trends accelerated for most sample soils, including 13 of the 15 highly-infiltrative soils showing a change relative to the unrestricted infiltration in the reference case. The findings, however, were generally not statistically significant. These results are suggestive, but not conclusive, of a growing role from intense precipitation in drought development for the selected region. The seasonality of evolving rainfall rates in the case study area may explain the limited impact, as intensity rates are growing most quickly during the wintertime, a period when episodes infrequently exceed maximum soil infiltration capacity. The methods introduced here, achieving superior accuracy at precise locations relative to gridded products, are reproducible for global locations with adequate data coverage.
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