作物不同生长时段对水分胁迫敏感性分析   总被引：4，自引：2，他引：2  

刘聪  张旭晖 《气象科学》1999,19(2):136-141

本文根据我省1982－1995年的土壤水分实测资料、主要农作物的产量资料及作物生长物候资料,计算得到我省主要旱作物各生长时段作物对水分胁迫的产量响应敏感系数,反映出作物在不同生长期对水分胁迫的敏感程度,结果表明：不同生长时段作物对水分胁迫的敏感度不同,作物干旱程序不能仅凭降水距平确定,需考虑作物对水分胁迫敏感性来修正干旱指标,才能有效对作物干旱实施监测,从而为人工增雨作业时间安排提供更为科学的依据。  相似文献   

Distribution of surface ozone concentration in the clean areas of china and its possible impact on crop yields     

Li Xingsheng  He Zhuanshi  Fang Xiumei  Zhou Xiuji 《大气科学进展》1999,16(1):154-158

１．ＩｎｔｒｏｄｕｃｔｉｏｎＩｎｒｅｃｅｎｔｙｅａｒｓｍａｎｙｓｔｕｄｉｅｓｓｈｏｗｔｈａｔｏｚｏｎｅｉｎｔｈｅｓｕｒｆａｃｅｌａｙｅｒｉｓａｎｉｍｐｏｒｔａｎｔｆａｃｔｏｒｆｏｒｃｏｎｔｒｏｌｉｎｇａｔｍｏｓｐｈｅｒｉｃｃｈｅｍｉｓｔｒｙｒｅａｃｔ...  相似文献   

Crop Residues Mulch as Organic Weed Management Strategy in Maize          下载免费PDF全文

Azhar Mahmood  Muhammad Zahid Ihsan  Abdul Khaliq  Saddam Hussain  Zahid Ata Cheema  Muhammad Naeem  Ihsanullah Daur  Hafiz Athar Hussain  Fahad Alghabari 《洁净——土壤、空气、水》2016,44(3):317-324

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Estimation of maize yield by using a process-based model and remote sensing data in the Northeast China Plain     

《Physics and Chemistry of the Earth》2015

Climate change significantly impact on agriculture in recent year, the accurate estimation of crop yield is of great importance for the food security. In this study, a process-based mechanism model was modified to estimate yield of C₄ crop by modifying the carbon metabolic pathway in the photosynthesis sub-module of the RS–P–YEC (Remote-Sensing–Photosynthesis–Yield estimation for Crops) model. The yield was calculated by multiplying net primary productivity (NPP) and the harvest index (HI) derived from the ratio of grain to stalk yield. The modified RS–P–YEC model was used to simulate maize yield in the Northeast China Plain during the period 2002–2011. The 111 statistical data of maize yield from study area was used to validate the simulated results at county-level. The results showed that the Pearson correlation coefficient (R) was 0.827 (p < 0.01) between the simulated yield and the statistical data, and the root mean square error (RMSE) was 712 kg/ha with a relative error (RE) of 9.3%. From 2002 to 2011, the yield of maize planting zone in the Northeast China Plain was increasing with smaller coefficient of variation (CV). The spatial pattern of simulated maize yield was consistent with the actual distribution in the Northeast China Plain, with an increasing trend from the northeast to the southwest. Hence the results demonstrated that the modified process-based model coupled with remote sensing data was suitable for yield prediction of maize in the Northeast China Plain at the spatial scale.  相似文献   

ENSO–climate fluctuation–crop yield early warning system—A case study in Jilin and Liaoning Province in Northeast China     

《Physics and Chemistry of the Earth》2015

Crop yield is very sensitive to climate variability. The El Niño–Southern Oscillation (ENSO) is one of the most important contributors to global climate fluctuation, and therefore has a major impact on agricultural production. In this study, we structure an ENSO–climate fluctuation–crop yield early warning system to model the maize yield in Jilin and Liaoning Provinces in Northeast China. The system, which consists of a weather generator and a Model to capture the Crop Weather relationship over a Large Area (MCWLA), is not only capable of simulating the maize yield both at the provincial (regional) scale and the grid scale, but can also provide the exceedance probability of yield. Simulation results show maize yields in El Niño years to be higher on average than those in neutral years, while yields in La Niña years are the lowest. Spatially, the central part of the study area always shows a higher yield than other parts of the study, while yields in the northeast and northwest parts are relatively lower, no matter how high or low the exceedance probability and whatever the ENSO phase. Our study strongly implies that such a warning system shows considerable potential for application in other areas of China.  相似文献   

A novel combined spectral index for estimating the ratio of carotenoid to chlorophyll content to monitor crop physiological and phenological status     

《International Journal of Applied Earth Observation and Geoinformation》2019

Accurate estimation of the ratio of carotenoid (Car) to chlorophyll (Chl) content is crucial to provide valuable insight into diagnoses of plant physiological and phenological status in crop fields. Studies for assessing the ratio of Car to Chl content have been extensively conducted with semi-empirical approaches using spectral indices. However, spectral indices established in previous studies generally relied on site- or species-specific measured data and these indices typically lacked sufficient estimation accuracy for the ratio of Car to Chl content to be used across various species and under different physiological conditions. In this study, we propose a novel combined carotenoid/chlorophyll ratio index (CCRI) in the form of the carotenoid index (CARI) divided by the red-edge chlorophyll index (CI_red-edge): The value of the index is illustrated using synthetic data simulated from the leaf radiative transfer model PROSPECT-5 and with extensive measured datasets at both the leaf and canopy level from the ANGERS dataset and winter wheat and maize field experiments. Results show that CCRI was the index with the highest correlation with the ratio of Car to Chl content in PROSPECT-5 simulations (R² = 0.99, RRMSE = 8.65%) compared to other spectral indices. Calibration and validation results using the ANGERS and winter wheat leaf level data showed that CCRI achieved accurate estimation of the ratio of Car to Chl content (R² = 0.52, RRMSE = 14.10%). CCRI also showed a good performance (R² = 0.54, RRMSE = 17.08%) for estimation of the ratio of Car to Chl content in both calibration and validation with the winter wheat and maize canopy spectra measured in field experiments. Further investigation of the effect of the correlation between leaf Chl and Car content on the performance of CCRI indicated that variation of the correlation affected the retrieval accuracy of CCRI, and CCRI might not be very sensitive to changes of the ratio of Car to Chl content with low values (<0.10).  相似文献   

Full year crop monitoring and separability assessment with fully-polarimetric L-band UAVSAR: A case study in the Sacramento Valley,California     

《International Journal of Applied Earth Observation and Geoinformation》2019

Spatial and temporal information on plant and soil conditions is needed urgently for monitoring of crop productivity. Remote sensing has been considered as an effective means for crop growth monitoring due to its timely updating and complete coverage. In this paper, we explored the potential of L-band fully-polarimetric Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) data for crop monitoring and classification. The study site was located in the Sacramento Valley, in California where the cropping system is relatively diverse. Full season polarimetric signatures, as well as scattering mechanisms, for several crops, including almond, walnut, alfalfa, winter wheat, corn, sunflower, and tomato, were analyzed with linear polarizations (HH, HV, and VV) and polarimetric decomposition (Cloude–Pottier and Freeman–Durden) parameters, respectively. The separability amongst crop types was assessed across a full calendar year based on both linear polarizations and decomposition parameters. The unique structure-related polarimetric signature of each crop was provided by multitemporal UAVSAR data with a fine temporal resolution. Permanent tree crops (almond and walnut) and alfalfa demonstrated stable radar backscattering values across the growing season, whereas winter wheat and summer crops (corn, sunflower, and tomato) presented drastically different patterns, with rapid increase from the emergence stage to the peak biomass stage, followed by a significant decrease during the senescence stage. In general, the polarimetric signature was heterogeneous during June and October, while homogeneous during March-to-May and July-to-August. The scattering mechanisms depend heavily upon crop type and phenological stage. The primary scattering mechanism for tree crops was volume scattering (>40%), while surface scattering (>40%) dominated for alfalfa and winter wheat, although double-bounce scattering (>30%) was notable for alfalfa during March-to-September. Surface scattering was also dominant (>40%) for summer crops across the growing season except for sunflower and tomato during June and corn during July-to-October when volume scattering (>40%) was the primary scattering mechanism. Crops were better discriminated with decomposition parameters than with linear polarizations, and the greatest separability occurred during the peak biomass stage (July-August). All crop types were completely separable from the others when simultaneously using UAVSAR data spanning the whole growing season. The results demonstrate the feasibility of L-band SAR for crop monitoring and classification, without the need for optical data, and should serve as a guideline for future research.  相似文献   

稻田轮作系统的减灾效应研究   总被引：3，自引：3，他引：0  

黄国勤  黄禄星 《气象与减灾研究》2006,29(3):25-29

1998年冬～2003年秋,在江西农业大学科技园水稻田进行了轮作系统的减灾效应试验.试验结果表明,稻田轮作系统能较好地减少病、虫、草害.其中轮作处理B(紫云英“接茬“玉米“间作“大豆“接茬“晚稻)、处理C(黑麦草“接茬“中稻)、处理D(黑麦草“接茬“早稻“接茬“晚稻)比连作处理A(紫云英“接茬“早稻“接茬“晚稻),在病、虫、草害方面都有不同程度地减少.对比分析折产后作物的生物产量可以发现,轮作处理D最高,达13 686 kg/hm,比连作处理A高6.7%.  相似文献   

中国黄土高原地区4～10月雨量时空变化特征分析   总被引：17，自引：6，他引：11  

王毅荣  王锡稳 《高原气象》2006,25(4):737-743

利用黄土高原区域40年的实测降水资料,研究了该区作物生长期(4~10月)降水量的时空变化特征,并对干年和湿年的降水进行了分析和比较。结果表明:黄土高原作物生长期降水在1985年左右发生突变,由历史上的多雨转为少雨;降水异常变化存在3~5年、8年左右和11~16年左右的振荡周期,3~5年的振荡周期更明显;干湿年降水存在明显差异,湿年比干年多40%以上;存在降水异常响应的敏感区,干旱在高原的东北部响应变幅大于其它地方,湿涝响应在高原的北部最为明显。  相似文献   

Delineation of management zones in agricultural fields using cover–crop biomass estimates from PlanetScope data     

《International Journal of Applied Earth Observation and Geoinformation》2020

Several methods have been proposed to delineate management zones in agricultural fields, which can guide interventions of the farmers to increase crop yield. In this study, we propose a new approach using remote sensing data to delineate management zones at three farm sites located in southern Brazil. The approach is based on the hypothesis that the measured aboveground biomass (AGB) of the cover crops is correlated with the measured cash-crop yield and can be estimated from surface reflectance and/or vegetation indices (VIs). Therefore, we used seven different statistical models to estimate AGB of three cover crops (forage turnip, white oats, and rye) in the season prior to cash-crop planting. Surface reflectance and VIs were used as predictors to test the performance of the models. They were obtained from high spatial and temporal resolution data of the PlanetScope (PS) constellation of satellites. From the time series of 30 images acquired in 2017, we used the PS data that matched the dates of the field campaigns to build the models. The results showed that the satellite AGB estimates of the cover crops at the date of maximum VI response at the beginning of the flowering stage were useful to delineate the management zones. The cover-crop AGB models that presented the highest coefficient of determination (R²) and the lowest root mean square (RMSE) in the validation and test datasets were Support Vector Machine (SVM), Cubist (CUB) and Stochastic Gradient Boosting (SGB). For most models and cover crops, the Enhanced Vegetation Index (EVI) and the Normalized Difference Vegetation Index (NDVI) were the two most important AGB predictors. At the date of maximum VI at the beginning of the flowering stage, the correlation coefficients (r) between the cover-crop AGB and the cash-crop yield (soybean and maize) ranged from +0.70 for forage turnip to +0.78 for rye. The fuzzy unsupervised classification of the cover-crop AGB estimates delineated two management zones, which were spatially consistent with those obtained from cash-crop yield. The comparison between both maps produced overall accuracies that ranged from 61.20% to 68.25% with zone 2 having higher cover-crop AGB and cash-crop yield than zone 1 over the three sites. We conclude that satellite AGB estimates of cover crops can be used as a proxy for generating management zone maps in agricultural fields. These maps can be further refined in the field with any other type of method and data, whenever necessary.  相似文献