Abstract
This study was carried out at Marsa Matruh governorate - western north coast Egypt (31° 15´ 35ʺ N, 27° 9´ 43ʺ E) in the 2017/2018 growing season. The experiment was conducted to assess the different heat units or Accumulative of growing degree-days (AGDD) under various factors [sowing dates, tillage operation and different Supplementary irrigation strategies] on biomass and grain yield production for barley. Thus; the factor of sowing date comprise into three treatments (15 th Nov, 30 th Nov and 15 th Dec). Second factor is tillage with two treatments (no tillage”NT” and tillage 20cm”T”) and the third factor is Supplementary irrigation with three treatments (0, 70and 140mm). thus; The results revealed that the (1 Ton.Fed -1 ) for (BY) needs for (585.3, 578.73 and 626.64) heat units (AGDD) as an average under different sowing dates (15 th Nov, 30 th Nov and 15 th Dec.) respectively with tillage treatment “T” . Further; the (1 Ton.Fed -1 ) from grain yield (GY) needs for (1518) heat units if sowing on the (15 th Nov.), for (1531.85) heat units on (30 th Nov.) and for (1468.7) heat units on (15 th Dec.). on the hand; with no tillage (NT) the BY and GY need for more heat unit to get (1 Ton.Fed -1 ) by (683.7,729.7 and 807.6) heat units for BY and (1845.1,1904.1 and 2099.5) heat units for GY under different sowing date (15 th Nov, 30 th Nov and 15 th Dec). Notable; that the highest value for heat uses efficiency (HUE) observed with (140mm) and tillage operation (T) under sowing date 15 th Nov by (2.06 & 0.76 Kg. fed -1 C-1day-1) for both (BY) and (GY) respectively. However; under sowing date 30th Nov there is not any significant differentiation for heat uses efficiency (HUE) value compare with sowing date 15th Nov which recorded (2.03 & 0.73 Kg. fed -1 C-1day-1) for both (BY) and (GY) respectively. On the other hand; The Aqua Crop model adequately simulated the biomass yield (BY), and grain yield (GY) for barely under different treatments. The simulated (BY) agreed well with the measured (BY) across different treatments where (R 2 = 0.98 & E = 0.95 & RMSE = 1.17%) for barely under different treatments of (sowing dates and supplementary irrigation strategies) with tillage process. measured and simulated (GY) were also closely related. The Aqua Crop model calibrated the GY with the prediction statistics error by (R 2 = 0.90 & E = 0.51 & RMSE = 1.18%) with tillage process. Consequently; these results suggest that the good value recorded with tillage (T), (140mm) and 15 th Nov. In addition, AquaCrop model could be used to predict BY and GY of barely with a high degree of reliability at western north coast conditions. Thus; using Aqua Crop helps to determine the plantation day which records a highest efficiency for heat units and water productivity. Keywords : Aqua Crop; Barley production; Heat unit; Sowing date; Supplementary irrigation and Tillage DOI : 10.7176/JNSR/9-14-04 Publication date :July 31 st 2019
Highlights
Scarcity of water and limitation water resource leads to reduction in water available for irrigation crops
Growing degree days (GDD) or heat units was calculated using the single sine curve method (Baskerville & Emin, 1969) during growing season of barely crop. This simple linear method requires only daily minimum and maximum air temperatures, which recorded by the local meteorological weather station in site of experiment, equation (1) give explanation for calculating growing degree days: growing degree-days (GDD) = [(Tmax + Tmin) / 2 ] - Tbase
; these results suggest that the Aqua Crop model is useful for simulating for Biomass yield (BY) and barely grain yield (GY) under different planting dates, and irrigation strategies
Summary
Scarcity of water and limitation water resource leads to reduction in water available for irrigation crops. ; Rainfall is one of the most important climatic variables because of its two sided effects - as a deficient resource, such as droughts and as a catastrophic agent, such as floods It is the primary source of water for agricultural production. Mean daily temperature for optimum growth and tillering is between 15 and 20 C° (Doorenbos & Kassam, 1979).Generally; barely production needs to promote all agricultural system parameters as (climate and water resource management) to get a highest value. The Food and Agricultural Organization (FAO) developed the AquaCrop model in an effort to meet this need in 2009 This model was originated from the ‘‘yield response to water’’ data (Doorenbos & Kassam, 1979)., and evolved to a normalized crop water productivity (NCWP) concept (Steduto et al.,2009). ; using Aqua Crop as assimilation model to get relation between prediction and actual production
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