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首页> 外文期刊>Transactions of the ASABE >MODELING RICE PLANT NITROGEN EFFECT ON CANOPY REFLECTANCE WITH PARTIAL LEAST SQUARE REGRESSION (PLSR)
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MODELING RICE PLANT NITROGEN EFFECT ON CANOPY REFLECTANCE WITH PARTIAL LEAST SQUARE REGRESSION (PLSR)

机译:利用部分最小二乘回归(PLSR)模拟水稻植物氮素对冠层反射的影响

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摘要

In Arkansas and other major rice growing states in the U.S., nitrogen fertilizer is commonly applied in a split application. The split application consists of a pre-flood ground application and one or two mid-season applications. Currently there are no fast and accurate methods for estimating mid-season nitrogen requirements of a rice crop. The goal of this research was to test spectral characteristics of a rice canopy to model and predict nitrogen status of a rice crop at the beginning of internodal elongation (BIE). The early part of internodal elongation is a critical period for mid-season nitrogen application due to the increased demand for nitrogen in the reproductive stage. Plot experiments were conducted with two popular rice varieties, Cocodrie and Wells, and six nitrogen levels of 0, 34, 67, 101, 134, 168 kg N/ha (0, 30, 60, 90, 120, and 150 lbs/acre) in a completely randomized block design with four replications. Data on canopy reflectance, biomass, and tissue nitrogen were measured three times at 7-day intervals starting at BIE. A t-test comparison showed no significant difference between the two cultivars in plant nitrogen, tissue nitrogen, or biomass at BIE. Both tissue nitrogen and plant nitrogen showed a parabolic relationship with yield, with yield maximized at 13 g/m 2 plant nitrogen and 3% tissue nitrogen. A partial least square regression (PLSR) model on canopy reflectance could explain 47%, 63%, and 71% of the variation in plant nitrogen for weeks 0, 1, and 2, respectively, from BIE. The cultivar did not affect the sensitivity of the PLSR models. With these models, it is possible to identify rice nitrogen requirements during the internodal elongation with moderate to high accuracy. A nitrogen management regime can be developed based on rice canopy reflectance using the PLSR models. The amount of nitrogen required by the field can be calculated as the difference between the predicted plant nitrogen status and the optimum level of 13 g/m 2 , at which the rice yield was maximized
机译:在美国的阿肯色州和其他主要水稻种植州,氮肥通常分批施用。拆分的应用程序包括一个洪水前的应用程序和一个或两个季中应用程序。当前,没有快速,准确的方法来估算水稻作物的中期氮需求。这项研究的目的是测试水稻冠层的光谱特征,以模拟和预测节间伸长(BIE)开始时水稻作物的氮素状况。由于繁殖期对氮的需求增加,节间伸长的早期是季节中期施氮的关键时期。对两种流行的水稻品种Cocodrie和Wells进行了田间试验,六个氮水平分别为0、34、67、101、134、168 kg N / ha(0、30、60、90、120和150磅/英亩) ),并在完全随机的区块设计中进行四次复制。从BIE开始,以7天的间隔测量了3次冠层反射率,生物量和组织氮的数据。 t检验比较显示,两个品种在BIE的植物氮,组织氮或生物量方面无显着差异。组织氮和植物氮均表现出与产量的抛物线关系,产量最高为13 g / m 2 植物氮和3%组织氮。基于冠层反射率的偏最小二乘回归(PLSR)模型可以分别解释BIE在第0、1和2周时植物氮变化的47%,63%和71%。该品种不会影响PLSR模型的敏感性。使用这些模型,可以以中等到高精度的精度识别节间伸长期间的水稻氮需求。可以使用PLSR模型基于水稻冠层反射率制定氮管理制度。田间所需的氮量可以通过预测的植物氮素水平与水稻最大产量的最佳水平13 g / m 2 之间的差异来计算

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