共查询到20条相似文献，搜索用时 46 毫秒
1.
AquaCrop模型在西北胡麻生物量及产量模拟中的应用和验证 总被引：2，自引：0，他引：2
为了预测水分和养分对胡麻籽粒产量、生物量与水分生产率的影响,使用FAO研发的水分驱动作物模型AquaCrop对胡麻在不同灌溉与氮磷水平下的生长情况进行模拟和验证。试验分别于2011年、2012年在甘肃省榆中县良种场进行,试验设置4个灌溉水平,3个氮水平,3个磷水平。模型性能的评价采用模型效率(E)、决定系数(R2)、均方根误差(RMSE)和平均绝对误差(MAE)等统计指标。分析结果表明:AquaCrop模型校正的籽粒产量和生物量在不同灌溉与氮磷水平处理下的预测误差统计值为:0.97E0.99,0.11RMSE0.33,0.11 t·hm 2MAE0.42 t·hm 2,与2012年的试验观察数据(0.96E0.99,0.11RMSE0.42,0.11 t·hm 2MAE0.39 t·hm 2)基本一致;同时,群体覆盖(CC)与生物量的模拟结果与测定值也非常拟合。AquaCrop模型在充分灌溉处理下预测胡麻产量,比非充分灌溉处理下具更高的准确性。因而,水分驱动模型AquaCrop在西北胡麻区不同的灌溉与田间管理措施下有较高的模拟精确性,具有广阔的应用前景和价值。 相似文献
2.
《Communications in Soil Science and Plant Analysis》2012,43(20):2459-2477
The model ORYZA2000 simulates the growth and development of rice under conditions of potential production and water and nitrogen (N) limitations. Crop simulation models could provide an alternative, less time-consuming, and inexpensive means of determining the optimum crop N and irrigation requirements under varied irrigation and nitrogen conditions. Water productivity (WP) is a concept of partial productivity and denotes the amount or value of product over volume or value of water used. For the evaluated ORYZA2000 model in Iran, a study was carried out in a randomized complete block design between 2005 and 2007, with three replications at the Rice Research Institute of Iran, Rasht. Irrigation management (three regimes) was the main plot and N application (four levels) was the subplot. In this study, simulation modeling was used to quantify water productivity and water balance components of water and nitrogen interactions in rice. Evaluation simulated and measured total aboveground biomass and yield, by adjusted coefficient of correlation, T test of means, and absolute and normalized root mean square errors (RMSE). Results showed that with normalized root mean square errors (RMSEn) of 5–28%, ORYZA2000 satisfactorily simulated crop biomass and yield that strongly varied among irrigation and nitrogen fertilizer conditions. Yield was simulated with an RMSE of 237–443 kg ha?1 and a normalized RMSE of 5–11%. Results showed that the significant (28–56%) share of evaporation into evapotranspiration, using the actual yield (measured) and simulated water balance (ORYZA2000), the calculated average WPET was significantly lower than the average WPT: 37%. The average WPI, WPI+R, WPET, WPT, and WPETQ were 1.4, 1.07, 1.07, 1.57, and 0.82 kg m?3. Results also showed that irrigation with 8-day intervals and 60 kg N ha?1, nitrogen level was the optimum irrigation regime and nitrogen level. 相似文献
3.
水稻吸氮量和干物质积累的模拟试验研究 总被引：10，自引：0，他引：10
本文描述了土壤氮和肥料氮素对水稻不同时期生长的影响及水稻对氮素吸收和在各组织器官的分布模式 ,借助水稻生长模型ORYZA - 0 ,通过田间和水槽的氮肥试验结果对水稻模型和氮素动态模块进行了验证。结果表明 ,模型模拟的水稻生物量、产量、叶片吸氮量和地上部吸氮量与实测值呈明显的正相关 ,其相关系数分别为 :生物量r=0.9889;产量r =0.9992 ;叶片吸氮量r =0.9597;地上部吸氮量r =0.9234。模拟生物量、产量和实测的生物及产量的相关性较高 ;而对叶片吸氮量、地上部吸氮量的模拟值与实测值的相关性稍低一些。但总体来看 ,该模型不仅能较准确地模拟水稻生长动态 ,而且可以模拟水稻氮吸收和积累的行为动态 相似文献
4.
Ali vahdati Ebrahim Amiri Ali Akbar Ebadi Ali Faramarzi 《Communications in Soil Science and Plant Analysis》2020,51(16):2137-2146
ABSTRACT The present study was conducted to assess the ability of AquaCrop model in predicting of grain and biological yield of rice genotypes in water management. A two-year field experiment was conducted at the experimental farm of the Iranian Rice Research Institute in Rasht, Iran from 2016 to 2017. The experiment was established in a split-plot design with two irrigation management (continuous submergence and end season water stress) as the main plot, fourth rice genotypes as the sub-plot and three replications. The goodness-of-fit between observed and simulated grain yield and final biomass was assessed by means of the coefficient of determination (R 2), the absolute and normalized root mean square errors (RMSE). The RMSEn of predicting grain yield at calibration and evaluation stages was in the range of 6–12% and 6–8% for biological yield. The results indicated that AquaCrop model is suitable to predict grain yield and biological yield of rice genotypes in northern Iran. AquaCrop model can be used to determine optimization strategies to improve the water consumption of rice genotypes. 相似文献
5.
《Communications in Soil Science and Plant Analysis》2012,43(12):1814-1830
The objective of this study was the evaluation of the CERES rice model under different nitrogen- and water-management conditions in northern Iran. A 3-year field experiment was conducted at the experimental farm of the Iranian Rice Research Institute in Rasht, Iran, from 2005 to 2007. The experiment was established in a split-plot design with three irrigation regimes (continuous submergence, irrigation at 5-day intervals, and irrigation at 8-day intervals) as the main plot, four nitrogen levels (0, 45, 60, and 75 kg N ha?1) as the subplot, and three replications. Evaluation simulated and measured grain yield, total crop biomass, N content of grain, and crop biomass by adjusted coefficient of correlation and by absolute and normalized root mean square errors (RMSE). Results showed that predicted grain yields agreed well with observed yields (RMSEa = 297 and RMSEn = 8%). Simulated and observed total dry-matter yields were also in reasonable agreement (RMSEn = 862 and RMSEn = 10%). Observed and predicted N uptake by rice showed good agreement. The CERES rice model can be applied to research purposes (irrigation and nitrogen) under northern Iranian conditions. 相似文献
6.
Ebrahim Amiri 《Communications in Soil Science and Plant Analysis》2016,47(3):387-403
The objective of this study was to adapt and test the ability of the AquaCrop model under different nitrogen and irrigation management conditions in northern Iran. A three-year field experiment was conducted at the experimental farm of the Iranian Rice Research Institute in Rasht, Iran, from 2005 to 2007. Irrigation treatments comprised continuous submergence, irrigation at 5-day intervals, and irrigation at 8-day intervals. Nitrogen (N) application levels were 0, 45, 60, and 75 kg N ha?1. The goodness of fit between observed and simulated canopy cover, total and panicle biomass, grain yield, and final biomass was assessed by means of the coefficient of determination (R2) and the absolute and normalized root mean square errors (RMSEn). Results of the statistical test of the model for total and panicle biomass showed moderately high R2 (≥0.90) and moderate RMSEn (6–36%) values, confirming that the model simulated the total and panicle biomass accurately. The model was simulated for CC with RMSEn and R2 of 28 and 0.82, respectively. The agreement between predicted and observed rice grain yield and final biomass were with R2 of 0.81 and 0.82 and RMSEn of 13 and 10% respectively. 相似文献
7.
结合遥感技术与水稻生长模型来预算水稻产量 总被引：10，自引：0，他引：10
Since remote sensing can provide information on the actual status of an agricultural crop, the integration betwee nremote sensing data and crop growth simulation models has become an important trend for yield estimation and prediction. The main objective of this research was to combine a rice growth simulation model with remote sensing data to estimate rice grain yield for different growing seasons leading to an assessment of rice yield at regional levels. Integration between NOAA (National Oceanic and Atmospheric Administration) AVHRR (Advanced Very High Resolution Radiometer) data and the rice growth simulation model ORYZA1 to develop a new software, which was named as Rice-SRS Model, resulted in accurate estimates for rice yield in Shaoxing, China, with an estimation error reduced to 1.03% and 0.79% over-estimation and 0.79% under-estimation for early, single and late season rice, respectively. Selecting suitable dates for remote sensing images was an important factor which could influence estimation accuracy. Thus, given the different growing periods for each rice season, four images were needed for early and late rice, while five images were preferable for single season rice. Estimating rice yield using two or three images was possible, however, if images were obtained during the panicle initiation and heading stages. 相似文献
8.
Davood Barari Tari Jahanfar Daneshian 《Communications in Soil Science and Plant Analysis》2017,48(2):201-213
This paper considers the implications of ORYZA2000 model in simulating physiological traits of rice at different nitrogen concentrations. The experiment was conducted over the course of the growing season in 2012 and 2013 in Rice Research Institute, Deputy of Mazandaran, Iran. The variety used was Shiroudi as a high yielding variety. The considered factors were the amount of nitrogen at four levels (40, 80, 120, 160 kg N ha?1 and control) and nitrogen splitting in four levels. We compared simulated and measured grain yield, biomass, grain nitrogen, total plant nitrogen uptake, and leaf area index (LAI) by Student’s t-test of means and by absolute and normalized root mean square errors (RMSE). Results showed that grain yield was simulated with an RMSE of 411–423 kg ha?1 and a normalized RMSE of 6%. RMSE was 671–910 kg ha?1 for biomass on harvesting date. RMSE were 7–11 for grain nitrogen, and 10–13 for total plant nitrogen uptake. LAI was simulated with a normalized RMSE of 17–23%. Generally the model simulated LAI, an exceeded measured value for different nitrogen treatments. The most obvious finding that emerged from this study was that ORYZA2000 model can be applied as a supportive research tool for selecting the most appropriate strategies for rice yield improvement at various nitrogen fertilization concentrations. 相似文献
9.
R. Moosavizadeh-Mojarad 《Archives of Agronomy and Soil Science》2013,59(11):1271-1282
It is important to model water and nitrogen requirements for rice yield in order to improve production. In this study, an artificial neural network (ANN) was used to predict rice grain yield under different water and nitrogen application. Grain yield was predicted based on five variables: nitrogen application rate, seasonal amount of applied irrigation water, plant population, and mean daily solar input before and after flowering. Furthermore, the ANN method was compared with a very simple model (VSM) for prediction of rice grain yield. Two approaches were considered for ANNs. In the first (local partitioning), rice grain yield and variable data from the south of Iran were used for training, and the network was then tested using independent data from the north of Iran. In another approach, the data for both experiments were mixed and randomized dividing was applied (stochastic partitioning). The results showed that stochastic partitioning networks are more accurate than local partitioning networks. Comparison between ANN and VSM results showed that using ANNs gives a more accurate prediction of grain yield. Therefore, ANNs with stochastic partitioning of data is an accurate method to predict rice grain yield using readily available inputs. 相似文献
10.
[目的]研究寒地稻田不同水肥管理模式下的土壤供氮特征,为筛选环境友好型寒地稻作灌溉施肥模式提供支撑。[方法]在大田试验条件下,设置间歇灌溉、淹灌2种水分管理模式及4个供氮水平(0,75,105,135kg/hm~2),以龙庆稻2号为材料,研究水肥互作模式对水稻产量、土壤供氮特征及氮素利用率的影响。[结果]灌溉模式和供氮水平对水稻产量、地上部氮素积累量、水稻氮素利用率均有显著(p0.05)或极显著影响(p0.01)。间歇灌溉模式下,增加氮肥施用量有利于提高单位面积水稻有效穗数、籽粒产量、生物产量、籽粒氮素累积量,均以施氮105kg/hm~2处理最高;水肥互作对氮素利用率影响明显,水稻的氮肥利用率在21.4%~59.1%;氮肥生理利用率、氮肥农学效率及氮肥偏生产力均随着施氮量的提高而降低,施氮量75kg/hm~2处理的氮素吸收利用各项指标均高于其他处理。相关分析表明,水肥因素是影响氮素积累及氮素吸收利用效率的重要因子。[结论]综合考虑水稻产量及氮素利用率的矛盾,间歇灌溉配合适宜减氮模式应予以高度重视。 相似文献
11.
基于ORYZA2000模型的旱稻生长模拟及氮肥管理研究 总被引：6，自引：2，他引：4
以旱稻田间试验资料为基础,对水稻生长模拟模型ORYZA2000模拟旱稻生长进行参数校正和验证,图解和回归分析结果显示ORYZA2000模拟旱稻生物量、产量、作物吸氮量的模拟值与观测值基本呈线性关系,模拟效果良好,但对土壤水分的模拟效果欠佳,需做进一步研究。应用校正和验证的结果,结合肥料效应函数原理,对旱稻不同灌溉方式和密度管理下的氮肥经济最佳施肥量做了探讨,初步得出了该地区旱稻栽培氮肥经济最佳施肥量,丰富了作物模拟和节水农业的理论和实践,对以后旱稻发展及栽培管理有一定的参考价值。 相似文献
12.
水稻灌溉需水量对气候变化响应的模拟 总被引：11，自引：7，他引：4
气候变化会导致作物耗水过程改变,从而影响灌溉需水。研究水稻灌溉需水对气候变化的响应规律,有助于合理制定应对气候变化的灌溉策略,保障水资源可持续利用和粮食安全。该文基于1961-2010年气象数据和HadCM3大气环流模式A2和B2两种情景下的统计降尺度模拟结果,利用经田间试验资料验证后的水稻模型ORYZA2000,模拟淹水灌溉和间歇灌溉两种灌溉处理下、历史和未来情景下水稻灌溉需水对气候变化的响应规律。结果表明:过去50年,间歇灌溉和淹水灌溉模式下水稻耗水量呈现显著上升趋势,而水稻灌溉需水量和产量都呈现下降趋势,分别由降水增加和气温升高、辐射下降导致的生育期缩短引起;未来气候情景下,间歇灌溉和淹水灌溉模式下水稻耗水量在未来3个时期(2020s,2050s和2080s)均呈现不同程度的增加;耗水量的显著增加和降水的减少导致了未来3个时期水稻灌溉需水量的明显增加;受持续增温的减产效应影响,水稻产量在未来3个时期呈现减少趋势,且降幅逐渐变大。 相似文献
13.
河套灌区不同育苗期和大棚温度对水稻生长的影响模拟 总被引：1，自引：0，他引：1
为确定宁夏河套灌区水稻适宜育秧和移栽期的综合气象指标,利用中卫市1996-2003年对宁粳16号水稻品种观测的资料,采用CERES-Rice模型对遗传参数进行本地化调试。模拟水稻产量、结实粒数、播种-开花和全生育期日数,并利用宁夏灌区10个市(县)资料验证模型的区域模拟能力。设置不同育秧日数和棚内气温,模拟二者对水稻产量、单位面积结实粒数和生育进程的单独和综合影响,以确定适宜移栽期的综合气象指标。结果表明:模型对水稻产量、结实粒数、播种-开花和全生育期日数模拟能力较好,产量和结实粒数的模拟最大误差分别为2.93%和3.47%,一致性指数分别达0.98和0.92;播种-开花日数模拟误差大多在3d以内,一致性指数为0.77。假定本田期的气象条件、施肥、灌溉等措施均不变,设置不同育秧温度和育秧日数,模拟发现育秧日数26~30d比18~24d时水稻产量高,结实粒数多。32℃下育秧的水稻产量和结实粒数最高,播种-开花和全生育期日数相对较短。同时改变育秧日数和育秧棚内气温,在育秧期较短时育秧温度升高将提高产量,增加结实粒数。而在育秧期较长时,育秧温度升高造成产量下降,结实粒数减少。32℃下育秧20d时水稻产量最高,结实最多,播种-开花和全生育期日数相对较短。育秧日数相同时,播种-开花和全生育期日数随育秧温度的升高而缩短;育秧温度相同时,播种-开花和全生育期日数随育秧期的延长而缩短。不同育秧温度下的最适育秧日数可作为预测河套灌区各地水稻适宜移栽期的综合农业气象指标,为细化水稻适宜移栽期的农业气象指标提供了新途径。 相似文献
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15.
P. Roychoudhury G.R. Pillai S.L. Pandey G.S.R. Krishna Murti G.S. Venkataraman 《Soil & Tillage Research》1983,3(1):61-65
The application of blue-green algae improved the aggregation status of rice field soils under different levels of irrigation and nitrogen fertilizer (urea) and increased the grain yield of rice significantly. 相似文献
16.
干湿交替灌溉与施氮量对水稻叶片光合性状的耦合效应 总被引：6，自引：2，他引：4
17.
利用四川单季稻区7个农业气象观测站5个主栽品种的田间观测数据,结合当地栽培管理措施、土壤条件及逐日气象资料对ORYZA2000模型进行参数调试,并确定四川单季稻区5个主栽品种的作物参数值;利用4～5a各主栽品种的观测数据对单季稻生育期、叶面积指数、生物量和产量等指标的模拟结果进行验证和评价。结果表明,合系39营养生长期发育速率最大,而生殖生长期发育速率最小,Ⅱ优838营养生长期发育速率最小,而D优63和汕优2生殖生长期发育速率最大;模型对5个单季稻主栽品种的生育期模拟效果较好,各品种开花期与成熟期的相对模拟误差均在1～2d,归一化均方根误差（NRMSE）均小于1%;各品种产量的NRMSE在5.26%～10.01%,叶面积指数的NRMSE为10.37%～19.19%,地上部总生物量、茎生物量、绿叶生物量及穗生物量的NRMSE分别为13.17%～18.69%、14.31%～20.41%、18.95%～24.74%和20.85%～25.39%。由此可见,ORYZA2000模型能够较为准确地模拟四川单季稻区5个主栽品种的发育及产量形成过程,适应能力较强,可以应用于四川单季稻生产。 相似文献
18.
利用四川单季稻区7个农业气象观测站5个主栽品种的田间观测数据,结合当地栽培管理措施、土壤条件及逐日气象资料对ORYZA2000模型进行参数调试,并确定四川单季稻区5个主栽品种的作物参数值;利用4～5a各主栽品种的观测数据对单季稻生育期、叶面积指数、生物量和产量等指标的模拟结果进行验证和评价。结果表明,合系39营养生长期发育速率最大,而生殖生长期发育速率最小,Ⅱ优838营养生长期发育速率最小,而D优63和汕优2生殖生长期发育速率最大;模型对5个单季稻主栽品种的生育期模拟效果较好,各品种开花期与成熟期的相对模拟误差均在1～2d,归一化均方根误差（NRMSE）均小于1%;各品种产量的NRMSE在5.26%～10.01%,叶面积指数的NRMSE为10.37%～19.19%,地上部总生物量、茎生物量、绿叶生物量及穗生物量的 NRMSE 分别为13.17%～18.69%、14.31%～20.41%、18.95%～24.74%和20.85%～25.39%。由此可见,ORYZA2000模型能够较为准确地模拟四川单季稻区5个主栽品种的发育及产量形成过程,适应能力较强,可以应用于四川单季稻生产。 相似文献
19.
减施氮肥和增氧灌溉对水稻氮代谢关键酶活性及氮素利用的影响 总被引：3，自引：3，他引：0
该研究旨在分析减施氮肥和增氧灌溉对水稻氮代谢关键酶活性及氮素利用的影响。2020年以中旱221（旱稻）、中浙优8号（水稻）和IR45765-3B（深水稻）共3个品种为材料,设常规淹水灌溉（Conventional Flood Irrigation, WL）、微纳米气泡水增氧灌溉（Micro-nano Bubble Water Oxygenation Irrigation, MBWI）2个灌溉模式和常规施氮（195.0 kg/hm2）、减施氮肥（157.5 kg/hm2）2个氮水平,研究了减施氮肥和增氧灌溉对水稻关键生育时期氮代谢相关酶活性、植株含氮量、氮素积累量以及产量和氮肥利用率的影响。结果表明,与常规施氮处理相比,减施氮肥降低了氮代谢酶活性,而增氧灌溉有助于提高硝酸还原酶、谷氨酰胺合成酶、谷氨酸合酶、谷丙转氨酶活性。增氧灌溉和氮肥一定程度上有助于水稻氮素积累,增氧灌溉下减施氮肥处理比淹水灌溉常规施氮量的当季氮肥利用率分别提高15.6%、36.2%、21.5%（P<0.05）。增氧灌溉和增施氮肥显著增加水稻产量,中旱221增氧灌溉下减施氮肥比淹水灌溉常规施氮量处理增产3.5%（P<0.05）,而中浙优8号和IR45765-3B增氧灌溉下减施氮肥与淹水灌溉常规施氮量差异不显著（P>0.05）。相关分析表明,氮代谢酶活性与同时期叶片含氮量及氮素积累量大多呈显著或极显著的正相关。可见,增氧灌溉可以显著提高水稻氮素代谢相关酶活性,从而显著提高水稻氮素积累量、产量和当季氮肥利用效率,水稻氮肥减施条件下采用增氧灌溉有助于水稻维持较高氮肥吸收和利用效率,而谷氨酰胺合成酶活性可以用于预测水稻各时期氮素积累量。研究结果可为水稻氮肥减施和提高水稻氮肥利用效率提供理论和技术支持。 相似文献
20.
M. R. Pahlavan-Rad S. A. R. Movahedi-Naeini Mohammad Pessarakli 《Journal of plant nutrition》2013,36(8):1133-1143
The effects of seed bed shaping on nutrient variation in soil and plant under two different irrigation intervals were investigated on wheat (Triticum asetivum L.) plants with a split plot design in a field plot in Zahak Agricultural Research Station in Sistan province in 2005. Irrigations after 80 and 160 mm evaporation from class A evaporation pan were used as main plots. Flat surface irrigation, single, triple, and 6-row beds with four replications were subplots. Total soil nitrogen (N), available phosphorus (P), potassium (K), calcium (Ca), magnesium (Mg), and sodium (Na) were measured in a 30 cm depth top layer at five sampling times. Shoot samples were analyzed for N, P, K, Ca, Mg and Na. Results showed that the 3-row and the 6-row beds with more frequent irrigation (shorter irrigation interval) increased soil solution sodium content in beds resulting in increased plant sodium absorption. With the 3-row and the 6-row beds, increased solution sodium concentration in soil increased solution ionic strength, dissolution of lime and hence soluble Ca and Mg. With the more frequent irrigation (shorter irrigation interval), only grain nitrogen and sodium contents were increased with no change in the absorption of other nutrients. The shoot N, P, and K uptake with more frequent irrigation (shorter irrigation interval) was greater, however the grain P and K uptakes were similar with the less frequent irrigation (longer irrigation interval), suggesting a lack of transfer from other tissues to grain. The transfer of nitrogen and all other major elements from other tissues to grain was greatest with single row bed with both irrigation intervals, suggesting grain yield might not have been affected by a greater N, P and K fertilizer application. A key to grain yield increase with a more frequent irrigation (shorter irrigation interval) might be using a limiting micronutrient, effective in major nutrients transfer to grain from the other plant tissues or a bed shaping method enhancing its uptake. 相似文献