ナイジェリアのキャバにおける気候要素とソルガム収量との単相関と重相関分析が生育期別に試みられた。播種前の降雨量と登熟期の温度はソルガムの収量を増加する傾向にあったが, 播種後94日間の気温と降雨量の変動は, ソルガムの収量を減少させた。また, ソルガム収量の変動の79.8%は, 4気候要素の複合効果として説明しうるものであることが明らかとなった。

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大豆畑からの蒸発散量(ET)を蒸散量(T)と蒸発量(E)に分離して評価するために, ETをボーエン比熱収支法により, Tを茎熱収支法により求めた。EはETとTとの差で与えられた。測定は1981年と1983年にそれぞれ0.105h及び0.64haの畑(品種エンレイ)で行った。得られた結果は次のように要約される。
1) 圃場蒸散量は茎熱収支法から求められる測定個体の平均蒸散量(T₀)から(2)式を用いて外挿されたが, T0の個体による差が比較的小さいため, 4本の測定個体から個々に推定したTには大差がなかった(Fig. 1)。TとETとの経時変化の間には若干のタイムラグが認められたが, 準定常状態の下での値または日平均値を用いることによってこの影響は消去できるものと考えた。
2) 早朝にはTが抑制された日があったが, これは露によるものと考えられた。このような日にはEは双頂型の日変化を示した(Fig. 2)。T/ET比は一般に正午を最小とする月変化曲線で表わされ, この日変化は植被層の見掛けの日射吸収率の日変化とほぼ平行関係にあった(Fig. 3)。
3) 生育初期の前半は土壌面が湿潤状態であったためETは生育最盛期のそれに匹敵し, Eは生育初期から最盛期にかけて減少する傾向にあった。T/ET比は土壌水分と天候の影響を大きく受け土壌面の乾燥時には大きな値を, 曇雨天日には小さい値を示す傾向にあった(Fig. 4)。
4) 湿面からの蒸発散量推定のための日射法の係数aの季節による変動は, Priestley-Taylor 法の係数αより小さく, 大豆畑における日射法の有効性が確かめられた(Fig. 5)。
5) 日射法が植被下の湿潤土壌面からの蒸発量推定にも利用できるものとして日蒸散量を推定するための簡易な半経験式を導いた。この式から, LAIに対するTの増加はおおむねLAI=2.6で鈍化すること(Fig. 7), Tは見掛けの吸収日射量に比例することが分かった。

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The effects of the duration and intensity of artificial rainfall (mist) treatment on the growth of the kidney bean plants were investigated. Seedlings of the plants were exposed to four levels of mist treatment (Precipitation: 1-5mm/h) in a growth chamber (20°C, artificial short-wave radiation was regulated at 2.8MJ/m²·day) for several days (1-5days). The growth and injury of plants were examined immediately after the mist treatments, and when the plants were kept at 20°C in a phytotron for 2 weeks when the mean natural short-wave radiation amounted to 9.4MJ/m²·day after the treatments.
1) The growth measured immediately after a 1- to 2-day exposure to mist showed hardly any influence from the different mist treatments. However, at the end of five-day exposure at the heavy mist treatments (2 and 5mm/h), the dry weight of the shoot and leaf area decreased in comparison with those at the light treatments (0 and 1mm/h mist): there was no significant difference between the 2 and 5mm/h mist treatments. The degree of wilting after misting increased with increases in the duration and intensity of the treatment.
2) With a misting duration of 1 day, the weight and leaf area of the plants grown in a phytotron for about 2 weeks after the mist treatment were larger than those of plants grown in the phytotron throughout the experimental periods, but were markedly smaller when the misting was continued for 3 days or more. The three-day exposure to 1mm/h mist had no effect on subsequent growth, but a 2 or 5mm/h mist reduced the subsequent growth in fresh weight, dry weight and leaf area: the differences in the growth between the two treatments were small.
3) The promotive effect of short-term exposure to the mist treatment on growth was mainly attributed to an effect of weak light during the treatment rather than an effect of shoot wetting. However, the inhibitory effect of long-term exposure to mist was attributed to both effects of weak light and shoot wetting by the mist treatment.
4) These results suggest that the effect of shoot wetting by rain on growth mainly depends on the duration rather than intensity (amount) of rainfall.

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タイ国東北部地区における耕地蒸発散による水損失量を明らかにするため, 主要な作物の蒸散量と気孔抵抗をポロメータで実測するとともに, 耕地面でのポテンシャル蒸発散量(PET)および実蒸発散量(AET)を一般気象観測データが利用できる Morton (1983) モデルを用いて求めた。
PETとAETによって表わされた気候の乾燥度(DI)は純放射量と相対湿度を変数としたより簡易な経験式で推定できた。DIは雨期(9月)の終りの0.1から直線的に増加し, 最乾期(2月)においては0.7～0.9の値になった。また主要な作物の葉面蒸散量と気孔抵抗値は乾期において土壌水分条件に強く影響を受けていることが認められた。更にDIとPETを用いて, 東北タイ地区におけるかんがい要求度(IR)の時期別および地域的分布を明らかにした。

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埋設管型熱交換器を用いる方法は, 堆肥そうからの熱抽出において典型的で簡単な方法であるが, 混合素材の切返しを行う際に埋設管の取り外し, 再配管などの煩雑な作業を必要とする。このような煩雑な作業を簡単にするためにマルチ・ヒートパイプ熱交換器を用いたユニークな熱抽出方法を提示し, 熱抽出過程における堆肥そう内温度及び熱交換器出口における熱媒体の温度の解析解を導いた。これらの解は埋設管型熱交換器に対する解と数学的に同一であった。そして, 解析解に基づき, マルチ・ヒートパイプ熱交換器の熱抽出能力を計算した。

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組織培養苗の順化過程における活着率の向上と順化期間の短縮を目的に, 順化環境調節装置(順化装置)を開発した(Fig. 1)。この装置の概要は以下の通りである。
(1) 順化装置は地上部の気温, 湿度, 光量, 炭酸ガス濃度および気流速度, 地下部の養液温度等を調節することができる(Fig. 2)。
(2) 順化装置は, 汎用マイクロコンピュータによる計測, 制御, 記録, 解析, 通信ソフトウェアを備えており, 順化過程の好適環境を逐次探索するための研究用装置として利用できる。
(3) 本装置の環境プログラムは, BASIC言語で書かれている。本プログラムでは, 制御式をデータとして与えることで環境制御方式の変更が行える。
(4) 培養苗の順化環境を設定するために, 各環境要因に関する, 順化曲線を考案した(Fig. 3)。
(5) 順化装置の試運転の結果では, 各環境要因ともに, ほぼ設定通りに制御できた(Fig. 4)。
(6) 順化装置を利用することによって, 順化過程における各環境を徐々に経日変化させることができた(Fig. 7)。
更に, この装置を利用した順化(順化装置利用区)と従来の順化(慣行法区)による栽培比較試験を, サトイモおよびイチゴを供試して行った。試験結果の概要は以下のようになる。
(1) 順化装置利用区および慣行区の枯死率は, サトイモの場合が8%および23%, イチゴの場合が4%および20%となり, 順化環境の違いにより枯死率に有意な差が認められた。
(2) 慣行法区に比べ, 順化装置利用区ではサトイモ, イチゴともに生体重, 乾物重, 草丈および葉数について優位であった(Fig. 5, Fig. 8)。
(3) 順化開始後に, 生体重および乾物重が減少し, 生育抑制を呈した(Fig. 5, Fig. 8)。
以上のことから, 順化環境の違いによって, 枯死率および生育にかなりの差がみられることがわかった。今後, 各作物について順化過程の好適環境の探索が必要である。
また, 順化直後の生育抑制を阻止するための研究が重要であると考える。

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To research regional difference of frost damage, meteorological observations were made at Hayakita, located in the south-east of the Ishikari-Yuhutsu plain in Hokkaido. Hayakita has crops that are the most easily damaged by frost in the plain. In particular paddy rice plants are damaged by the first frost when their growth is retarded by a cool summer. The first frost in Hayakita occurs 1 week earlier than in other parts of the plain. To research this problem, Chitose that has different topography from Hayakita, was selected as a control area and some meteorological factors such as air temperature, wind speed, solar radiation, net radiation and downward radiation were compared between Hayakita and Chitose. These areas are at the same altitude and share similar surface features. Although Hayakita is surrounded by hills, Chitose is in the center of the plain and is located 12 kilometers away from Hayakita.
In this paper, the daily minimum air temperatures and 4-hour mean values of the meteorological factors in the springs and falls of 1983 and 1984 were compared between Hayakita and Chitose. Also the variations of these factors on clear nights were compared.
Daily minimum air temperatures in both seasons were not significantly different between Hayakita and Chitose. This means that the advection and accumulation of air mass cooled on surrounding slopes are not significant as causes of the frost damage in Hayakita.
The 4-hour mean value of wind speed at Chitose was always greater than that at Hayakita. However, there were no significant differences for the other factors, such as solar radiation, net radiation and downward radiation between Hayakita and Chitose. The air temperature in Hayakita was often lower than that in Chitose, especially in the lower range of temperatures. This tendency was more remarkable in fall than in spring. Sometimes the temperature difference between the two regions reached approximately 5K in fall, accompanied with a large difference of wind speed.
This large difference of air temperature tended to be observed from 20:00 to 4:00 of clear nights. It was caused by temperatures in Chitose often being rapidly increased by raising wind speed during that time, but both temperature and wind speed in Hayakita remained low and unchanged. When comparing temperature profiles to 80 meters above ground level of both regions, it was noted that the stable layer formed by radiative cooling was destroyed from upper portion to near ground surface at Chitose, while, on the other hand, only the upper portion of the layer was destroyed at Hayakita. However, both stable layers remained during the nights when no temperature difference occurred between the regions. Therefore, the occurrence of temperature differences between the regions is due to the difference in the destruction ratio of the stable layer.
The phenomena mentioned above, often appeared in the center of the plain when the upper wind (geostrophic wind) speed and/or direction changed. The upper wind data were obtained from radiosonde data at the 900mb isobaric surface above Sapporo. The changes of wind were classified by following two patterns: i) upper wind speed very small at first, becoming stronger later, and ii) upper wind direction changing from a direction in which WSR (Wind Speed Ratio: the ratio of surface wind speed to upper wind speed at a direction) is small to other one in which WSR is greater. Greater WSR means greater wind speed at ground level for a given upper wind speed; WSR is influenced by surrounding geographic features. Therefore, the WSR values at the center of the plain, lying between the high mountains to the east and west, were large for the north-south direction and small for the east-west direction. On the other hand, WSR values were relatively small for all directions in Hayakita. Thus wind speed in Hayakita was always smaller than that in the center of the plain.
It can thus be recognized that low temperatures conti

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In this paper, the simulation model for microclimatic environment in a rice field described in a previous paper (Inoue, 1985) was improved to extend its applicability. Improved conversational model allowed a variety of output products such as graphic display and line printer of simulated results. The simulation of microclimatic environment by this improved model was made using the observation data of microclimate during the period July 27 to August 31 in 1986. The results obtained by simulation of microclimatic environment in a rice field were compared with the measurements. The results obtained in this paper can be summarized as follows:
(1) An on-line data acquisition and microclimate simulation system (see Fig. 1) was developed for acquisition and analysis of observation data of microclimate, and for simulation of microclimatic environment using the improved model (see Fig. 2). The transmission of data from a data logger in an experimental field to a mini-computer in a laboratory was made through an optical fiber. This system also enabled us to study evapotranspiration and heat balance of the rice field.
(2) Figure 4 shows the diurnal changes in microclimatic environment of the rice field simulated by the model using the external input data as shown in the bottom of this figure 4(D). The diurnal changes in water temperature under the rice canopy and evapotranspiration rate simulated by the model agreed well with those measured at the experimental field with acceptable error (see Fig. 4).
(3) The simulation model was used to examine effects of deep flooding water on the temperature environment in the rice canopy. Simulation results showed that the deep flooding water can protect young rice panicles before the heading time from low air temperature (Fig. 5).
(4) This simulation model was used to predict the change in daily means of microclimatic environment in the rice field, which are needed to predict dynamics of crop growth and fertility elements (Fig. 6). The model was also used to make clear the microclimate characteristics for the dew formation on rice leaves during night time. Simulation results showed that dew occurred on the rice leaves in the canopy under conditions that the leaf temperature falls below the dew point in the surrounding air (see Fig. 7).
The above results showed that the improved simulation model and the developed system for acquisition and analysis of data of rice microclimate could be applied to predict the microclimatic environment in a rice field on line.

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In order to obtain the method to predict the developmental stage of soybean crop, relationships among a developmental rate, daylength and daily mean air temperature were investigated during the period from seeding to flowering. Three plots with respective daylength of 13.3, 14.3 and 15.3 hours were set under field conditions. In each plot 6 cultivars of soybean were seeded on 6 different dates (from May 10 to July 19 with 2-week intervals in 1985). Results obtained were as follows.
(1) The mean developmental rate from seeding to flowering was linearly related to air temperature for each cultivar of each controlled daylength level. Linear regression equations for the relationships between the developmental rate and air temperature were obtained for 6 cultivars and shown in Table 1.
(2) The regression lines shifted with the decrease of daylength, and consequently revealed the increase of the developmental rate (Fig. 2). The differences in their slopes were very little among the cultivars and/or the daylengths examined. The differences in a seeding-to-flowering period among cultivars were analysed in terms of the changes in regression lines, and we confirmed that they were due to difference in sensitivity to daylength.
(3) Our results show that the developmental rate method proposed here predict accurately the flowering stage of soybean crop (Fig. 3).
(4) Within a limited region and season, where the close correlation between daylength and daily mean air temperature is observed, the developmental rate of soybean can be calculated as a unique function of temperature. However, this simplified method, hitherto used, should not be applied to the case out of the range of the observed data.

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