農業気象
Online ISSN : 1881-0136
Print ISSN : 0021-8588
ISSN-L : 0021-8588
78 巻, 3 号
選択された号の論文の3件中1~3を表示しています
Full Paper
  • Kenichi TATSUMI
    原稿種別: Full Paper
    2022 年 78 巻 3 号 p. 89-100
    発行日: 2022/07/10
    公開日: 2022/07/10
    ジャーナル オープンアクセス
    電子付録
     Ozone (O3) is believed to be the most damaging air pollutant to crops, owing to its ability to decrease physiological functions, including photosynthesis. Accordingly, it has been reported that rice yields have been drastically reduced by O3 exposure. However, previous studies have not assessed the impacts of O3 on rice, nor assessed the fine-scale comprehensive relationships between O3 sensitivity regimes and volatile organic compound (VOC) and NOx emissions throughout Japan. In this study, a combined Weather Research and Forecasting with Chemistry (WRF-Chem) model was used with anthropogenic emission, biomass burning, and biogenic emission data to evaluate the impacts of surface O3 on reduced rice yields in Japan in 2010. The relative yield loss due to O3 damage was evaluated using the accumulated ozone exposure over a threshold of 40 ppb (AOT40) and a mean 7 hour ozone mixing ratio (M7). The differences between the measured and simulated O3 data indicate that the WRF-Chem model simulated the surface O3 concentration adequately. At a national scale, the aggregated average relative yield losses in Japan were estimated to be 4.3% for AOT40 and 2.0% for M7, while aggregated rice production loss was 482 Kt for AOT40 and 218 Kt for M7. In particular, the greatest rice production loss was observed in the Kanto region (126 Kt for AOT40 and 54 Kt for M7). In addition, the model results indicate that isoprene and formaldehyde (CH2O) are critical for the atmospheric oxidation of surface O3 in the Kanto region. Although there are uncertainties associated with the growing period, cultivar, emission inventories, and rice sensitivity to O3 concentrations, the results of this study provide an important scientific basis for attaining more sustainable food production.
  • Kazuhiro FUJIWARA, Shunsuke KUBO, Kensuke EIJIMA, Ryo MATSUDA, Akira Y ...
    2022 年 78 巻 3 号 p. 101-112
    発行日: 2022/07/10
    公開日: 2022/07/10
    ジャーナル オープンアクセス
     We have improved a light-emitting diode artificial sunlight source system that we developed in 2013. The 2013 system can produce light with various spectral distributions for wavelengths of 380-940 nm that approximates those of ground-level sunlight and produce light with arbitrarily modified spectral distributions. Moreover, this system can produce time-varying light with different spectral distributions. However, this system’s utility is limited because the light it produces has low maximum irradiance and low time-stability for sunlight-effect research experiments. Hardware and software improvements to that system allow it to now produce a maximum irradiance of approximately 1.54 kW m-2 for 380-940 nm at a 7.1 cm2 light outlet with greater time stability and make it easier to produce time-varying light having a large number of different spectral distributions. First-step operational tests showed that this improved system can accurately produce single light with spectral irradiance distributions (SIDs) approximating: (1) SIDs of ground-level sunlight measured in Tokyo at two-hour intervals on a clear day; (2) various magnifications (1.33, 1.2, 1, 1/10, 1/100, and 1/1000 times) of a reference terrestrial solar SID, which is defined by the International Electrotechnical Commission; and (3) various geometric-shape SIDs as arbitrarily modified ones, except for a rectangular shape. For the second-step operational test, time-varying light with the three SIDs described above was produced in various sequences at three-second intervals. The third-step operational test verified the 30-min time stability of SID at the light outlet. Operational tests indicate that the improved system can facilitate various sunlight-effect research. Our improved system enables sunlight-effect research experiments that were previously impossible, such as investigations of naturally fluctuating sunlight effects on plant response, growth, and development. Moreover, experiments comparing the effects of ground-level sunlight spectral distribution and conventional artificial lamps on plant growth and development are now possible.
Research Notes
  • Akira HAMA, Minami SATO, Yuta TSUKAMOTO, Nobuhiro MATSUOKA
    2022 年 78 巻 3 号 p. 113-120
    発行日: 2022/07/10
    公開日: 2022/07/10
    ジャーナル オープンアクセス

     Sunlight conditions, such as a clear or cloudy sky, can have an adverse effect on vegetation spectroscopy. Drones with mounted solar irradiation sensors have become available recently. Estimation of sunlight conditions at the observation location by using data from these solar irradiation sensors can help increase the accuracy of spectroscopy measurements. In this study, we estimated sunlight conditions using a drone-mounted solar irradiation sensor by the following two approaches: Method A, in which direct and diffuse solar radiations were separated based on the global solar radiation estimated using the solar irradiation sensor, and Method B, in which direct and diffuse solar radiations were separated using spectroscopic data from the solar irradiation sensor. For Method A, we found that in the near-infrared (NIR) wavelength range, the light was not readily scattered by the atmosphere, allowing for more accurate estimation. The results of the separation of the direct and diffuse solar radiations based on the estimated global solar radiation were compared with the results of actual measurements. The coefficient of determination (R2) and root mean square error (RMSE) were 0.971 and 0.062, respectively; however, the direct component was overestimated. Thus, the use of the empirically determined equation for the separation of the direct and diffuse solar radiations may result in a systematic bias. For Method B, the proportion of diffuse solar radiation was estimated by comparing the blue wavelength range, within which scattering occurs readily, with the red wavelength range. A comparison of the estimated and observed values revealed that R2 and RMSE were 0.868 and 0.127, respectively. Thus, the estimation accuracy of Method B is lower than that of Method A, even though Method B is simpler to use.

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