Estimation of Net Primary Production of Rice Crop using CASA model in Nankana Sahib.

Ayesha Behzad, Usman Rafique
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引用次数: 3

Abstract

Estimation of Net Primary Production (NPP) is crucial for the supply of food/wood. Precise estimates of NPP are important for sustainable development. We used Light Use Efficiency (LUE) model to appraise various growth-related processes e.g., photosynthesis, respiration and transpiration, in the rice plant. The study site received 1213 actual sunshine hours in comparison to total possible sunshine hours which were 1595 during the complete Rice Growth Period (RGP). Water stress was estimated throughout the RGP which resulted in surplus of water in early growth stages (W=53) and deficiency in the final ripening stage with W=0.14. Careful results indicate that about 5128 kg/ha of wet biomass was generated during the complete RGP. We applied a harvest index of 0.50 to estimate the dry biomass that was 2564 kg/ha which is about (2.82 ton/ha). These estimates seem to be in exaggeration according to real time field estimates collected by Crop Reporting Service (CRS) department which were (1.83 ton/ha). To manage this exaggeration, we applied the Soil Suitability Constant (ħα) which resulted as 1.99 ton/ha in suitable zone, 1.21 ton/ha in less suitable, 1.76 ton/ha in moderately suitable and 0.73 ton/ha in not suitable zones. The average yield was estimated as 1.62 ton/ha. According to CRS department, the rice area in the study site was reported as 107000 ha and the net rice production was estimated as 1,73,340 tons in the study site. The LUE model is reliable to estimate NPP of rice crop which is useful for decision makers to determine the contribution of rice in Gross Domestic Product (GDP) at regional scales in term of surplus or shortfall.
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利用CASA模型估算南卡那地区水稻净初级产量
净初级生产量(NPP)的估算对于食物/木材的供应至关重要。对NPP的精确估计对可持续发展非常重要。我们使用光利用效率(LUE)模型来评估水稻植株的各种生长相关过程,如光合作用、呼吸作用和蒸腾作用。研究地点的实际日照时数为1213小时,而水稻全生育期的总可能日照时数为1595小时。在整个RGP中估计水分胁迫,导致生长早期水分过剩(W=53),成熟后期水分不足(W= 0.14)。仔细的结果表明,在整个RGP过程中产生了大约5128公斤/公顷的湿生物质。我们采用0.50的收获指数估计干生物量为2564 kg/ha,约为(2.82吨/ha)。根据作物报告服务(CRS)部门收集的实时田间估计数据(1.83吨/公顷),这些估计似乎有些夸张。为了控制这种夸张,我们应用了土壤适宜性常数(ħα),结果是适宜区为1.99吨/公顷,不太适宜区为1.21吨/公顷,中等适宜区为1.76吨/公顷,不适宜区为0.73吨/公顷。平均产量估计为1.62吨/公顷。根据CRS部门的报告,研究地点的水稻面积为107000公顷,水稻净产量估计为173340吨。LUE模型对水稻作物的NPP估算是可靠的,这有助于决策者在区域尺度上确定水稻对国内生产总值(GDP)的贡献。
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