CROP WEATHER RELATIONSHIPS IN SUMMER PEARL MILLET (Pennisetum americanum (L.) Leeke) AND TESTING OF CERES MILLET MODEL FOR THE MIDDLE GUJARAT AGROCLIMATIC ZONE
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Date
1993
Journal Title
Journal ISSN
Volume Title
Publisher
AAU, Anand
Abstract
Pearl millet fPennisetum americanum (L.) Leeke) is one of the most important and widely cultivated cereal crop in the arid and semi-arid regions of the world. It is generally, grown as rainfed crop in rainy season in the scanty rainfall area and on poor soils. It is more resistant to drought than sorghum. It can sustain under higher temperature regimes. Under intensive cropping system, it has its own place and being cultivated during summer season, where irrigation facilities are available. Weather variables affect the crop growth differently in different phenophases during its growth cycle. Field experiments during summer season of 1991 and 1992 were conducted with Cv.GHB-30 and were laidout in split plot design, with three dates of sowing as main plot and four irrigation regimes as sub-plot, replicated thrice. The results obtained during the course of investigation revealed that, higher temperatures decreased the duration of the crop with the delay in sowing. Higher relative humidity during flowering stage gave higher grain yields. Higher grain yields were recorded from first date of sowing. However, reduction was lesser in second date of sowing. Late sown crop recorded lowest grain yields. Irrigation scheduled through IW/CPE = 1.0 proved best. However, irrigation scheduled by infrared thermometry could save about 30 to 35% of irrigation water with no much reduction in grain yields. Yield attribute such as earhead weight had positively contributed towards grain yield. Consumptive use of water increased with increase in the frequency of irrigation. However, water use efficiency was higher with lesser irrigation frequencies, indicating a drought resistance trait in summer pearl millet. Stress degree days had significant negative correlation with growth attributes. Decrease in leaf water potential during flowering stage had adversely affected the grain yields. Studies on Intercepted photosynthetic active radiation indicated higher IPAR use efficiencies in D2 treatment (15th Feb.sowing date) during both the years. The extinction coefficient (K) calculated showed a value of 0.89. Correlation studies between grain yield and weather parameters revealed that morning, afternoon and mean relative humidity upto flowering stage played a major role in deciding the final grain yield. During anthesis to dough stage both thermal interception rate (TIR) and intercepted photosynthetic active radiation (IPAR) showed significant positive correlation with grain yield indicating better source sink relationship. Stepwise regression analysis selected a model with mean relative humidity (during emergence to tillering stage) and hours of bright sunshine (during flag leaf to anthesis stage) as parameters for predicting grain yields, 20 to 25 days before maturity. Path analysis of grain yield and weather parameters observed in important phenophases indicated that higher relative humidity during flag leaf to dough stage and higher thermal interception rate (TIR) during anthesis to dough stage are found favourable for higher grain yields. Prediction model obtained for total biomass production selected only accumulated growing degree days (GDD) during emergence to tillering phase (P1). This model could predict the total biomass 50 to 60 days before maturity. CERES millet model corrected for genetic coefficients was found to be good for this region. CERES millet model could predict the anthesis date and maturity date with minimum error. However, grain yields and total biomass production predicted by CERES millet model showed larger percent error compared to that of grain yields and total biomass production predicted by regression models obtained in the study. Secondly, CERES millet model has the limitation of predicting the yield at the end of growing season. However, the prediction models obtained in the study could predict the grain yields and total biomass production well in advance.
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Keywords
AGRICULTURAL METEOROLOGY, AGRICULTURE, A STUDY