农田养分空间变异特征及精准/分区管理技术研究
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摘要
土壤养分供应与作物养分需求在空间上的不协调是限制作物高产和养分高效利用的关键因素之一,但目前结合不同网格取样尺度、土壤养分、作物产量和养分吸收,探讨农田养分空间变异特征及精准/分区平衡施肥技术的报道甚少。本文应用GPS、GIS等有关信息技术和地统计学方法,研究了规模经营的黑龙江江川农场水稻、分散经营的河北衡水冬小麦-夏玉米和分散经营的吉林陶家春玉米三个试区三种网格(50 m×50 m、100 m×100 m和150 m×150 m)取样尺度下农田土壤养分空间变异特征及其与作物产量的空间关系和精准/分区平衡施肥技术的应用效应,为发展适合我国国情的农田土壤养分精准/分区管理技术提供理论基础,主要研究结果如下:
1.农田土壤养分空间变异特征
采用传统统计和地统计相结合的方法,对江川农场水稻试区、衡水冬小麦-夏玉米试区和陶家春玉米试区农田土壤养分空间变异特征进行了研究。规模经营的江川农场水稻试区土壤养分主要限制因子是N、P、K和Zn;三种网格(50 m×50 m、100 m×100 m和150 m×150 m)取样尺度下试区9个水稻田块间土壤主要养分含量差异总体上均显著,但同一田块三种网格取样尺度下土壤主要养分含量差异总体上均不显著;三种网格取样尺度的同一土壤速效养分在空间分布上具有较明显的空间相似性。表明按150 m×150 m网格进行土壤取样,能对规模经营稻田不同田块土壤主要养分状况进行正确评价;对规模经营的江川农场试区稻田可按田块(6.3-12.9 hm2/田块)为管理单元进行土壤养分分区管理。
分散经营的衡水冬小麦-夏玉米试区土壤养分管理的重点是N、P和K,对土壤Zn也要引起一定重视。在50 m×50 m、100 m×100 m和150 m×150 m三种网格取样尺度下,试区同一土壤养分含量概况基本无差异,同一土壤养分在空间分布上具有较明显的空间相似性。显示按150 m×150 m网格进行土壤取样,能对分散经营冬小麦-夏玉米试区农田土壤主要养分状况进行比较正确的评价,大大降低成本和工作量。
分散经营的陶家春玉米试区土壤养分主要限制因子为N、P、K和Zn;试区同一生产小组三种网格(50 m×50 m、100 m×100 m和150 m×150 m)取样尺度间土壤主要养分含量差异总体上不显著;生产小组间50 m×50 m和100 m×100 m两种取样尺度的土壤速效P和Zn含量差异显著;三种网格取样尺度的同一土壤速效养分在空间分布上具有较明显的空间相似性。表明按150 m×150 m网格进行土壤取样,能对试区不同生产小组土壤OM和速效K状况进行正确评价,而对土壤速效P状况的评价被低估,对土壤速效Zn状况的评价被高估;对分散经营的陶家试区土壤OM和速效K可按生产小组(18.1-34.8 hm2/生产小组)为管理单元、土壤速效P和Zn可将生产小组分成2个区域进行土壤养分分区管理。
在“十二”期间及以后,在东北平原、华北平原等粮食主产区发展适度规模经营前景广阔。上述结果显示,对分散经营的吉林陶家和河北衡水试区进行适度规模经营养分管理基本可行(对土壤主要养分可将生产小组分成1-2个区域,适度规模经营面积一般100亩以上),也易于指导平衡施肥和有利于提高生产效益。
2.土壤养分空间变异性与作物产量的关系
在上述三个试区按100 m×100 m网格测定作物籽粒和秸秆产量,并采集籽粒和秸秆样品,初步探讨了作物产量空间变异特征及其与养分吸收和土壤养分的空间关系。结果表明,不同经营体制和生产条件下作物籽粒产量和养分吸收总量的空间变异均较大,变异系数分别在9.7%- 15.8%和8.2%-21.1%之间。作物籽粒产量空间变异与作物整个生育期N、P2O5和K2O吸收总量空间变异之间密切相关,相关系数分别在0.76-0.87、0.68-0.90和0.35-0.65之间。
土壤速效养分是作物吸收养分的最主要来源之一,水稻、冬小麦、夏玉米和春玉米整个生育期间氮和磷吸收总量空间变异与种植前土壤OM或相应土壤速效氮或磷的空间变异之间呈显著或一定的正相关,而冬小麦钾吸收量与种植前土壤速效钾含量之间呈极显著的正相关。
土壤养分供应状况是作物产量潜力发挥最为重要的因素之一,作物籽粒产量的空间变异与土壤OM和速效养分的空间变异之间有显著的或一定的相关性。江川农场试区水稻籽粒产量与土壤OM和速效N含量之间呈显著或极显著的正相关;河北衡水试区冬小麦籽粒产量与土壤OM含量之间呈极显著的正相关,与土壤速效磷与锌含量之间均呈一定的正相关,而夏玉米籽粒产量与土壤NH4+-N含量之间呈极显著的正相关;吉林陶家试区春玉米籽粒产量与土壤OM、NO3--N和速效Zn含量之间呈显著或极显著的正相关。
3.作物适宜氮磷用量及精准/分区平衡施肥技术
针对衡水和陶家两试区氮磷不合理施用、肥料利用率低等问题,对两试区中等土壤肥力区域氮和磷的适宜用量进行了探讨。结果表明,在河北衡水试区中等土壤肥力区域,冬小麦适宜N和P2O5用量范围分别为220-260和90-110 kg/hm2,夏玉米适宜N和P2O5用量范围分别为220-280和95-115 kg/hm2;在吉林陶家试区中等肥力区域,春玉米适宜N和P2O5用量范围分别为170-190和60-75 kg/hm2。
在明确上述试区土壤养分空间变异特征、养分合理施用技术等的基础上,应用土壤养分信息化管理和高产高效推荐平衡施肥咨询服务系统,提出了作物高产高效精准/分区平衡施肥技术。田间校验试验表明,精准/分区平衡施肥技术能显著提高作物产量、经济效益和氮肥利用率。与习惯施肥相比,江川农场试区水稻分区平衡施肥技术增产4.3%-11.2%,增收778.70-1532.00元/hm2,提高氮肥利用率12.6-14.0个百分点;河北衡水试区冬小麦分区平衡施肥技术增产6.7%,增收992.5元/hm2,提高氮肥利用率15.2个百分点;夏玉米分区平衡施肥技术增产5.3%-9.0%,增收454.19-464.92元/hm2,提高氮肥利用率8.4-10.7个百分点;吉林陶家春玉米分区平衡施肥技术增产7.3%-8.9%,增收1280.94-1647.78元/hm2。
Spatial unsynchronization of nutrient supply and demand was one of the most important factors influencing high yield of crops and efficient use of nutrients. At present, little information is available on spatial variability and site-specific management of soil nutrients in main grain production areas from the viewpoint of grid-sampling scales, soil nutrients, crop yield and nutrient uptake being systematically considered. In this research, a rice production area (collective contract management system) of Jiangchuan farm in Heilongjiang province, a winter wheat - summer corn production area (family responsibility management system) of Hengshui in Hebei province, and a spring corn production area (family responsibility management system, rain-fed condition) of Taojia in Jilin province were selected as three experimental areas. Soil nutrient spatial variability characteristics under three grid-sampling scales (50 m×50 m, 100 m×100 m and 150 m×150 m ) in the three study areas, spatial relationship among soil nutrient contents, total nutrient uptake rates and crop yields, and crop response to site-specific balanced fertilization were studied using information technology, such as GIS and GPS, and geo-statistics. This will give scientific bases to develop site-specific nutrient management techniques within fields suitable to Chinese status of collective contract and family responsibility management systems. The main results obtained are summarized as follows:
1. Spatial variability of soil nutrients
Spatial variability of soil nutrients in the three study areas were evaluated using traditional statistics and geo-statistics. In the rice production area of Jiangchuan farm under the collective contract management system, soil nutrient limiting factors were N, P, K and Zn. Significant differences in contents of soil nutrients among 9 fields were found in the study area under three grid-sampling scales. Whereas insignificant differences in contents of each nutrient in soils were observed under the three grid-sampling scales. Distinct spatial distribution similarity for each soil nutrient under the three grid-sampling scales was found with relatively high contents in some areas of the study area and relatively low contents in other areas. These showed that status of main soil nutrients under the collective contract management system can be evaluated on 150×150-m grid-sampling scale, and it was technically feasible to develop regionalized N, P, K and Zn nutrient management at the level of the field in the study area.
In the winter wheat - summer corn production area of Hengshui under family responsibility management system, the emphasis on soil nutrient management was focused on N, P and K, and the management of Zn should also be given some attention. Insignificant differences in status (average content and C.V.) of each nutrient in soils were found in the study area under three grid-sampling scales. Distinct spatial distribution similarity for each soil nutrient under the three grid-sampling scales was observed with relatively high contents in some areas of the study area and relatively low contents in other areas. These indicated that status of main soil nutrients under family responsibility management system can be evaluated on 150×150-m grid-sampling scale, with the costs of soil sampling, soil testing, etc. decreasing significantly as sampling density decreasing.
In the spring corn production area of Taojia under family responsibility management system, soil nutrient limiting factors were N, P, K and Zn. Insignificant differences of each nutrient in soils were generally found in the study area under three grid-sampling scales. Whereas significant differences in contents of soil P and Zn among three production groups were observed under 50×50-m and 100×100-m grid-sampling scales. Distinct spatial distribution similarity for each soil nutrient under the three grid-sampling scales were found, with relatively high contents in some areas of the study area and relatively low contents in other areas. These showed that the status of soil OM and K under family responsibility management system can be evaluated on 150×150-m grid-sampling scales, but the status of soil available P was undervalued and the status of soil available K was overvalued. It was technically feasible to develop regionalized OM and K management at the level of production group, and for soil available P and Zn, each production group could be regionalized into 2 management units, with each unit consisted of connected farmer plots.
The moderate collective contract production management in main grain production regions of Northeastern Plain and North-central Plain has a broad prospect from 12th five-year plan. The results indicated that it was technically feasible to develop moderate collective production management of soil nutrients in Taojia of Jinlin study area and Hengshui of Hebei study area under family responsibility management system (Each production group could be regionalized into 1-2 management units for the main soil nutrients, with each unit consisted of connected farmer plots. The area of moderate collective production management is generally more than 6.7 ha ), which is helpful for extending balanced fertilization and enhancing economic income.
2. Spatial relationship between soil nutrient contents and crop yields
Based on the determined yields of crop grain and straw and the collected samples on a 100 m×100 m grid in the three study areas, spatial variability of crop grain yields and the spatial relationship among grain yields, total nutrient uptake rates and soil nutrient contents were analyzed. The results showed that significant spatial variability of crop grain yields and total nutrient uptake rates was found under different management systems (the collective contract management system and the family responsibility management system), and different conditions of agricultural production, with respective C.V. of crop grain yields and total nutrient uptake rates ranging from 9.7% to 15.8% and from 8.2% to 21.1%. Spatial variability of crop grain yields was closely correlated with total uptake rates of nitrogen, phosphorus (P2O5) and potassium (K2O) during growth period of crop, with respective correlation coefficients being 0.76-0.87, 0.68-0.90 and 0.35-0.65.
Soil available nutrient was identified as significant sources of crop nutrient uptake. Spatial variability of total uptake rates of nitrogen and phosphorus during growth period of rice, winter wheat, summer corn and spring corn was closely and positively correlated with soil OM contents or corresponding available N or P contents in soils prior to crop seeding. Whereas spatial variability of total potassium uptake rates during growth period of winter wheat was significantly and positively correlated with soil available K contents.
Soil nutrient status was one of the most important factors affecting crop yield potentials. Spatial variability of crop grain yields was positively correlated with contents of soil OM and available nutrients. Rice grain yields in Jiangchuan farm study area was closely and positively correlated with contents of OM and available N in soils. Grain yields of winter wheat in Hengshui study area was closely and positively correlated with soil OM contents, and a positive correlation relationship between grain yields and contents of soil available P and Zn was not significant at p < 0.05, respectively. Whereas grain yields of summer corn was closely and positively correlated with soil NH4+-N contents in Hengshui study area. Grain yields of spring corn in Taojia study area was closely and positively correlated with contents of OM, NO3--N and available Zn in soils.
3. Proper nitrogen and phosphorus application rates and crop response to the site-specific balanced fertilization
Field experiments were conducted to determined proper nitrogen and phosphorus application rates under medium soil fertility in Hengshui and Taojia study areas. The results showed that respective proper N and P2O5 application rates under medium soil fertility in Hengshui study area ranged from 220 to 260 and from 90 to 110 kg/ha for winter wheat, and from 220 to 280 and from 95 to 115 kg/ha for summer corn. Proper N and P2O5 application rates of spring corn under medium soil fertility in Taojia study area ranged from 170 to190 and from 60 to 75 kg/ha, respectively.
Site-specific balanced fertilization techniques for high yield and high quality crop production in the three study areas were developed based on the regionalized soil nutrient GIS maps and a computerized fertilizer recommendation system. The results from field experiments showed that significant increase of grain yield, economic income and recovery rate of applied N were observed for the site-specific balanced fertilization. In Jiangchuan farm study area of Heilongjiang, site-specific balanced fertilization techniques increased rice yield, income and nitrogen recovery rate by 4.3%-11.2%, 778.70-1532.00 RMB Yuan/ha and 12.6-14.0 percentage point, respectively. In Hengshui study area of Hebei, yield, income and nitrogen recovery rate by site-specific balanced fertilization techniques respectively increased by 6.7%, 992.5 RMB Yuan/ha and 15.2 percentage point for winter wheat, and by 5.3%-9.0%, 454.19-464.92 RMB Yuan/ha and 8.4-10.7 percentage point for summer corn. In Taojia study area of Jilin, site-specific balanced fertilization techniques increased spring corn yield and income by 7.3%-8.9% and 1280.94-1647.78 RMB Yuan/ha, respectively.
1.农田土壤养分空间变异特征
采用传统统计和地统计相结合的方法,对江川农场水稻试区、衡水冬小麦-夏玉米试区和陶家春玉米试区农田土壤养分空间变异特征进行了研究。规模经营的江川农场水稻试区土壤养分主要限制因子是N、P、K和Zn;三种网格(50 m×50 m、100 m×100 m和150 m×150 m)取样尺度下试区9个水稻田块间土壤主要养分含量差异总体上均显著,但同一田块三种网格取样尺度下土壤主要养分含量差异总体上均不显著;三种网格取样尺度的同一土壤速效养分在空间分布上具有较明显的空间相似性。表明按150 m×150 m网格进行土壤取样,能对规模经营稻田不同田块土壤主要养分状况进行正确评价;对规模经营的江川农场试区稻田可按田块(6.3-12.9 hm2/田块)为管理单元进行土壤养分分区管理。
分散经营的衡水冬小麦-夏玉米试区土壤养分管理的重点是N、P和K,对土壤Zn也要引起一定重视。在50 m×50 m、100 m×100 m和150 m×150 m三种网格取样尺度下,试区同一土壤养分含量概况基本无差异,同一土壤养分在空间分布上具有较明显的空间相似性。显示按150 m×150 m网格进行土壤取样,能对分散经营冬小麦-夏玉米试区农田土壤主要养分状况进行比较正确的评价,大大降低成本和工作量。
分散经营的陶家春玉米试区土壤养分主要限制因子为N、P、K和Zn;试区同一生产小组三种网格(50 m×50 m、100 m×100 m和150 m×150 m)取样尺度间土壤主要养分含量差异总体上不显著;生产小组间50 m×50 m和100 m×100 m两种取样尺度的土壤速效P和Zn含量差异显著;三种网格取样尺度的同一土壤速效养分在空间分布上具有较明显的空间相似性。表明按150 m×150 m网格进行土壤取样,能对试区不同生产小组土壤OM和速效K状况进行正确评价,而对土壤速效P状况的评价被低估,对土壤速效Zn状况的评价被高估;对分散经营的陶家试区土壤OM和速效K可按生产小组(18.1-34.8 hm2/生产小组)为管理单元、土壤速效P和Zn可将生产小组分成2个区域进行土壤养分分区管理。
在“十二”期间及以后,在东北平原、华北平原等粮食主产区发展适度规模经营前景广阔。上述结果显示,对分散经营的吉林陶家和河北衡水试区进行适度规模经营养分管理基本可行(对土壤主要养分可将生产小组分成1-2个区域,适度规模经营面积一般100亩以上),也易于指导平衡施肥和有利于提高生产效益。
2.土壤养分空间变异性与作物产量的关系
在上述三个试区按100 m×100 m网格测定作物籽粒和秸秆产量,并采集籽粒和秸秆样品,初步探讨了作物产量空间变异特征及其与养分吸收和土壤养分的空间关系。结果表明,不同经营体制和生产条件下作物籽粒产量和养分吸收总量的空间变异均较大,变异系数分别在9.7%- 15.8%和8.2%-21.1%之间。作物籽粒产量空间变异与作物整个生育期N、P2O5和K2O吸收总量空间变异之间密切相关,相关系数分别在0.76-0.87、0.68-0.90和0.35-0.65之间。
土壤速效养分是作物吸收养分的最主要来源之一,水稻、冬小麦、夏玉米和春玉米整个生育期间氮和磷吸收总量空间变异与种植前土壤OM或相应土壤速效氮或磷的空间变异之间呈显著或一定的正相关,而冬小麦钾吸收量与种植前土壤速效钾含量之间呈极显著的正相关。
土壤养分供应状况是作物产量潜力发挥最为重要的因素之一,作物籽粒产量的空间变异与土壤OM和速效养分的空间变异之间有显著的或一定的相关性。江川农场试区水稻籽粒产量与土壤OM和速效N含量之间呈显著或极显著的正相关;河北衡水试区冬小麦籽粒产量与土壤OM含量之间呈极显著的正相关,与土壤速效磷与锌含量之间均呈一定的正相关,而夏玉米籽粒产量与土壤NH4+-N含量之间呈极显著的正相关;吉林陶家试区春玉米籽粒产量与土壤OM、NO3--N和速效Zn含量之间呈显著或极显著的正相关。
3.作物适宜氮磷用量及精准/分区平衡施肥技术
针对衡水和陶家两试区氮磷不合理施用、肥料利用率低等问题,对两试区中等土壤肥力区域氮和磷的适宜用量进行了探讨。结果表明,在河北衡水试区中等土壤肥力区域,冬小麦适宜N和P2O5用量范围分别为220-260和90-110 kg/hm2,夏玉米适宜N和P2O5用量范围分别为220-280和95-115 kg/hm2;在吉林陶家试区中等肥力区域,春玉米适宜N和P2O5用量范围分别为170-190和60-75 kg/hm2。
在明确上述试区土壤养分空间变异特征、养分合理施用技术等的基础上,应用土壤养分信息化管理和高产高效推荐平衡施肥咨询服务系统,提出了作物高产高效精准/分区平衡施肥技术。田间校验试验表明,精准/分区平衡施肥技术能显著提高作物产量、经济效益和氮肥利用率。与习惯施肥相比,江川农场试区水稻分区平衡施肥技术增产4.3%-11.2%,增收778.70-1532.00元/hm2,提高氮肥利用率12.6-14.0个百分点;河北衡水试区冬小麦分区平衡施肥技术增产6.7%,增收992.5元/hm2,提高氮肥利用率15.2个百分点;夏玉米分区平衡施肥技术增产5.3%-9.0%,增收454.19-464.92元/hm2,提高氮肥利用率8.4-10.7个百分点;吉林陶家春玉米分区平衡施肥技术增产7.3%-8.9%,增收1280.94-1647.78元/hm2。
Spatial unsynchronization of nutrient supply and demand was one of the most important factors influencing high yield of crops and efficient use of nutrients. At present, little information is available on spatial variability and site-specific management of soil nutrients in main grain production areas from the viewpoint of grid-sampling scales, soil nutrients, crop yield and nutrient uptake being systematically considered. In this research, a rice production area (collective contract management system) of Jiangchuan farm in Heilongjiang province, a winter wheat - summer corn production area (family responsibility management system) of Hengshui in Hebei province, and a spring corn production area (family responsibility management system, rain-fed condition) of Taojia in Jilin province were selected as three experimental areas. Soil nutrient spatial variability characteristics under three grid-sampling scales (50 m×50 m, 100 m×100 m and 150 m×150 m ) in the three study areas, spatial relationship among soil nutrient contents, total nutrient uptake rates and crop yields, and crop response to site-specific balanced fertilization were studied using information technology, such as GIS and GPS, and geo-statistics. This will give scientific bases to develop site-specific nutrient management techniques within fields suitable to Chinese status of collective contract and family responsibility management systems. The main results obtained are summarized as follows:
1. Spatial variability of soil nutrients
Spatial variability of soil nutrients in the three study areas were evaluated using traditional statistics and geo-statistics. In the rice production area of Jiangchuan farm under the collective contract management system, soil nutrient limiting factors were N, P, K and Zn. Significant differences in contents of soil nutrients among 9 fields were found in the study area under three grid-sampling scales. Whereas insignificant differences in contents of each nutrient in soils were observed under the three grid-sampling scales. Distinct spatial distribution similarity for each soil nutrient under the three grid-sampling scales was found with relatively high contents in some areas of the study area and relatively low contents in other areas. These showed that status of main soil nutrients under the collective contract management system can be evaluated on 150×150-m grid-sampling scale, and it was technically feasible to develop regionalized N, P, K and Zn nutrient management at the level of the field in the study area.
In the winter wheat - summer corn production area of Hengshui under family responsibility management system, the emphasis on soil nutrient management was focused on N, P and K, and the management of Zn should also be given some attention. Insignificant differences in status (average content and C.V.) of each nutrient in soils were found in the study area under three grid-sampling scales. Distinct spatial distribution similarity for each soil nutrient under the three grid-sampling scales was observed with relatively high contents in some areas of the study area and relatively low contents in other areas. These indicated that status of main soil nutrients under family responsibility management system can be evaluated on 150×150-m grid-sampling scale, with the costs of soil sampling, soil testing, etc. decreasing significantly as sampling density decreasing.
In the spring corn production area of Taojia under family responsibility management system, soil nutrient limiting factors were N, P, K and Zn. Insignificant differences of each nutrient in soils were generally found in the study area under three grid-sampling scales. Whereas significant differences in contents of soil P and Zn among three production groups were observed under 50×50-m and 100×100-m grid-sampling scales. Distinct spatial distribution similarity for each soil nutrient under the three grid-sampling scales were found, with relatively high contents in some areas of the study area and relatively low contents in other areas. These showed that the status of soil OM and K under family responsibility management system can be evaluated on 150×150-m grid-sampling scales, but the status of soil available P was undervalued and the status of soil available K was overvalued. It was technically feasible to develop regionalized OM and K management at the level of production group, and for soil available P and Zn, each production group could be regionalized into 2 management units, with each unit consisted of connected farmer plots.
The moderate collective contract production management in main grain production regions of Northeastern Plain and North-central Plain has a broad prospect from 12th five-year plan. The results indicated that it was technically feasible to develop moderate collective production management of soil nutrients in Taojia of Jinlin study area and Hengshui of Hebei study area under family responsibility management system (Each production group could be regionalized into 1-2 management units for the main soil nutrients, with each unit consisted of connected farmer plots. The area of moderate collective production management is generally more than 6.7 ha ), which is helpful for extending balanced fertilization and enhancing economic income.
2. Spatial relationship between soil nutrient contents and crop yields
Based on the determined yields of crop grain and straw and the collected samples on a 100 m×100 m grid in the three study areas, spatial variability of crop grain yields and the spatial relationship among grain yields, total nutrient uptake rates and soil nutrient contents were analyzed. The results showed that significant spatial variability of crop grain yields and total nutrient uptake rates was found under different management systems (the collective contract management system and the family responsibility management system), and different conditions of agricultural production, with respective C.V. of crop grain yields and total nutrient uptake rates ranging from 9.7% to 15.8% and from 8.2% to 21.1%. Spatial variability of crop grain yields was closely correlated with total uptake rates of nitrogen, phosphorus (P2O5) and potassium (K2O) during growth period of crop, with respective correlation coefficients being 0.76-0.87, 0.68-0.90 and 0.35-0.65.
Soil available nutrient was identified as significant sources of crop nutrient uptake. Spatial variability of total uptake rates of nitrogen and phosphorus during growth period of rice, winter wheat, summer corn and spring corn was closely and positively correlated with soil OM contents or corresponding available N or P contents in soils prior to crop seeding. Whereas spatial variability of total potassium uptake rates during growth period of winter wheat was significantly and positively correlated with soil available K contents.
Soil nutrient status was one of the most important factors affecting crop yield potentials. Spatial variability of crop grain yields was positively correlated with contents of soil OM and available nutrients. Rice grain yields in Jiangchuan farm study area was closely and positively correlated with contents of OM and available N in soils. Grain yields of winter wheat in Hengshui study area was closely and positively correlated with soil OM contents, and a positive correlation relationship between grain yields and contents of soil available P and Zn was not significant at p < 0.05, respectively. Whereas grain yields of summer corn was closely and positively correlated with soil NH4+-N contents in Hengshui study area. Grain yields of spring corn in Taojia study area was closely and positively correlated with contents of OM, NO3--N and available Zn in soils.
3. Proper nitrogen and phosphorus application rates and crop response to the site-specific balanced fertilization
Field experiments were conducted to determined proper nitrogen and phosphorus application rates under medium soil fertility in Hengshui and Taojia study areas. The results showed that respective proper N and P2O5 application rates under medium soil fertility in Hengshui study area ranged from 220 to 260 and from 90 to 110 kg/ha for winter wheat, and from 220 to 280 and from 95 to 115 kg/ha for summer corn. Proper N and P2O5 application rates of spring corn under medium soil fertility in Taojia study area ranged from 170 to190 and from 60 to 75 kg/ha, respectively.
Site-specific balanced fertilization techniques for high yield and high quality crop production in the three study areas were developed based on the regionalized soil nutrient GIS maps and a computerized fertilizer recommendation system. The results from field experiments showed that significant increase of grain yield, economic income and recovery rate of applied N were observed for the site-specific balanced fertilization. In Jiangchuan farm study area of Heilongjiang, site-specific balanced fertilization techniques increased rice yield, income and nitrogen recovery rate by 4.3%-11.2%, 778.70-1532.00 RMB Yuan/ha and 12.6-14.0 percentage point, respectively. In Hengshui study area of Hebei, yield, income and nitrogen recovery rate by site-specific balanced fertilization techniques respectively increased by 6.7%, 992.5 RMB Yuan/ha and 15.2 percentage point for winter wheat, and by 5.3%-9.0%, 454.19-464.92 RMB Yuan/ha and 8.4-10.7 percentage point for summer corn. In Taojia study area of Jilin, site-specific balanced fertilization techniques increased spring corn yield and income by 7.3%-8.9% and 1280.94-1647.78 RMB Yuan/ha, respectively.
引文
1.白由路,金继运,杨俐苹,2001.农田土壤养分变异与施肥推荐[J].植物营养与肥料学报,7(2):129-133.
2.白由路,金继运,杨俐苹,2001.基于GIS的土壤养分分区管理模型研究[J].中国农业科学,34(1):46-50.
3.白由路,金继运,2001.我国精准农业发展模式探讨[G]//精准农业与土壤养分管理,中国大地出版社,北京:17-22.
4.曹慧,杨浩,赵其国等,2002.太湖流域丘陵地区土壤养分的空间变异[J].土壤,(4):201-205.
5.曹志洪,1998.科学施肥与我国粮食安全保障[J].土壤,2:57-63.
6.陈恩凤,1990.土壤肥力物质基础及其调控[M].北京:科学出舨社,338-378.
7.陈光,贺立源,2008.耕地养分空间插值技术与合理采样密度的比较研究[J].土壤通报,39(5):1007-1011.
8.陈蓉蓉,周治国,曹卫星等,2004.基于GIS的农田土壤、作物特征空间变异性及其相互关系[J].应用生态学报,15(9):1678-1680.
9.封志明,李香莲,2000.耕地耕地与粮食安全战略:藏粮于土,提高中国土地资源的综合生产能力[J].地理学与国土研究,16(3):1-5.
10.高强,李德忠,黄立华等,2008.吉林玉米带玉米一次性施肥现状调查分析[J].吉林农业大学学报, 30(3):301-305.
11.高祥照,胡克林,郭焱,2002.土壤养分与作物产量的空间变异特征与精确施肥[J].中国农业科学,35(6):660-666.
12.高义民,同延安,胡正义,2006.黄土区村级农田土壤养分空间变异特征研究[J].土壤通报, 37(1):1-6.
13.国家环境保护总局,2001. 2000年中国环境状况公报[J].环境保护,(7):3-9.
14.国家粮食局.中国粮食年鉴[M].北京:经济管理出版社,2006:586.
15.国家粮食局.中国粮食年鉴[M].北京:经济管理出版社,2007:542
16.郭旭东,傅伯杰,2000.基于GIS和地统计学的土壤养分空间变异特征研究[J].应用生态学报,11(4):555-563.
17.韩金玲,李雁鸣,马春英等,2006.施锌对小麦开花后氮、磷、钾、锌积累和运转的影响[J].植物营养与肥料学报,12(3):313-320.
18.何文寿,2004.植物营养学通论[M].宁夏人民出版社,银川:313-330.
19.胡田田,刘翠英,李岗等,2001.施肥对土壤供肥和冬小麦养分吸收及其产量的影响[J].干旱地区农业研究,19(3):36-41.
20.华孟,王坚,1992.土壤物理学[M].北京农业大学出版社,北京:214-243.
21.黄昌勇,2000.土壤学[M].中国农业出版社,北京:221-223.
22.黄绍文,金继运,杨俐苹,2002.乡(镇)级区域土壤养分空间变异与分区管理技术研究[J].资源科学,24(2):76-82.
23.黄绍文,金继运,杨俐苹,2003.县级区域粮田土壤养分空间变异与分区管理技术研究[J].土壤学报,40(1):79-88.
24.扈立家,李天来,2005.我国发展精准农业的问题及对策[J].沈阳农业大学学报(社会科学版),7(4):400-402.
25.胡克林,李保国,林启美等,1999.农田土壤养分的空间变异性特征[J].农业工程学报,15(3):33-38.
26.候景儒,郭光裕,1993.矿床统计预测及地质统计学的理论与应用[M].北京:冶金工业出版社.
27.雷咏雯,危常州,李俊华,2004.不同尺度下土壤养分空间变异特征的研究[J].土壤,36(4):376-381.
28.冷玲,刘双全,魏颖,2007.双城土壤养分空间变异与玉米分区施肥技术研究[J].黑龙江农业科学,(4):38-40.
29.李瑞,白由路,2007.上海市规模经营农场的土壤养分与水稻产量空间变异特征[J].中国土壤与肥料,(3):40-76.
30.李翔,潘瑜春,赵春江等,2005.基于多年产量数据的精准农业管理分区提取与尺度效应评价[J].中国农业科学,38(9):1825-1833.
31.李玉影,刘双全,迟宏伟,2005.土壤养分空间变异与大豆分区施肥技术研究[J].中国农学通报,21(11):238-240.
32.廖桂堂,李廷轩,王永东等,2008.不同尺度下低山茶园土壤主要微量元素的空间变异性[J].土壤,40(2):257-263.
33.姜城,2000.不同经营体制下土壤养分空间变异规律以及管理技术的研究[D].中国农业科学院研究生院.
34.金继运,1998.“精准农业”及其在我国的应用前景[J].植物营养与肥料学报,4(l):1-7.
35.金继运,李家康,李书田,2006.化肥与粮食安全[J].植物营养与肥料学报,12(5):601-609.
36.巨晓棠,张福锁.中国北方土壤硝态氮的累积及其对环境的影响.生态环境,2003,12,(1):24-28.
37.李哈滨,王政权,王庆成,1998.空间异质性研究理论与方法[J].应用生态学报,9(6):651-657.
38.李庆逵,朱兆良,于天仁,1998.中国农业持续发展中的肥料问题[M].南昌:江西科学技术出版社.
39.李世清,高亚军,李生秀,2000.土壤养分的空间变异性及确定样本容量的研究[J].土壤与环境,9(l):56-59.
40.李小昱,雷廷武,王为,2000.农田土壤特性的空间变异性及Kriging估值法[J].西北农业大学学报,28(6):30-35.
41.李子忠,龚元石,2001.不同尺度下田间土壤水分和混合电导率空间变异性与套合结构模型[J].植物营养与肥料学报,7(3):255-261.
42.雷志栋,杨诗秀等,1985.土壤特性时空变异性初步研究[J].水利学报,(9):10-21.
43.宁茂岐,刘洪斌,武伟,2007.两种取样尺度下土壤重金属空间变异特征研究[J].中国生态农业学报,15(3):86-91.
44.米丽娜,王芳,李友宏等,2009.宁夏平原淤灌土土壤养分与作物产量的空间变异性[J].干旱区研究,26(4):508-513.
45.秦松,樊燕,刘洪斌,2007.地形因子与土壤养分空间分布的相关性研究[J].水土保持研究,14(4):276-279.
46.秦耀东,1992.土壤空间变异研究中的定量分析[M].地球科学进展,7(l):44-49.
47.沈思渊,1989.地统计学在土壤空间变异研究中的应用及其展望[J].土壤学进展,17(3):11-25.
48.盛建东,肖华,武红旗等,2005.不同取样尺度农田土壤速效养分空间变异特征初步研究[J].干旱地区农业研究,23(2):64-67.
49.盛建东,肖华,武红旗等,2006.不同取样间距农田土壤全量养分空间变异特征研究[J].土壤通报,37(6):1062-1065.
50.宋晓宇,王纪华,刘良云,2007.基于Quickbird遥感影像的农田管理分区划分研究[J].中国农业科学,40(9):1996-2006.
51.宋永林,唐华俊,李小平等,2007.长期施肥对作物产量及褐潮土有机质变化的影响研究[J].华北农学报,22(增刊):100-105.
52.汤勇华,黄耀,2008.中国大陆主要粮食作物地力贡献率及其影响因素的统计分析[J].农业环境科学学报,27(4):1283-1289.
53.王同朝,李凤民,王俊等,1999.分层供水施磷对春小麦光合性能、同化产物流向和水分利用效率的影响[J].植物生态学报,23(2):177-185.
54.王兴仁,陈新平,张福锁等,1998.施肥模型在我国推荐施肥中的应用[J].植物营养与肥料学报,4(1):67-73.
55.王学锋,1993.土壤特性时空变异性研究的评述与展望[J].土壤学进展,21(4):42-49.
56.王宗明,张柏,宋开山,2007.东北平原典型农业县农田土壤养分空间分布影响因素分析[J].水土保持学报,121(12):73-77.
57.王政权,1999.地统计学及在生态学中的应用[M].科学出版社,北京:150-156.
58.谢高地,陈沈斌等,2005.环境的空间连续变异与精准农业[M].气象出版社,北京:65-66.
59.徐尚平,陶澎,徐福留,2000.内蒙土壤微量元素含量的空间结构特征[J].地理学报,55(3):337-345.
60.徐英,陈亚新,史海滨等,2004.土壤水盐空间变异尺度效应的研究[J].农业工程学报,20(2):l-5.
61.薛正平,杨星卫,段项锁,2002.土壤养分空间变异及合理取样数研究[J].农业工程学报,18(4):6-9.
62.薛正平,杨星卫,段项锁等,2004.土壤养分与春小麦产量关系及最佳施肥量研究[J].中国生态农业学报,12(4):110-112.
63.杨俐苹,姜城,金继运等,2000.棉田土壤养分精准管理初探[J].中国农业科学,33(6):67-72.
64.杨建锋,邓伟,章光新,2006.田块尺度苏打盐渍土盐化和碱化空间变异特征[J].土壤学报(3):500-505.
65.杨忠生,赵丽岩,刘君阁,2005.桦川县土壤肥力现状及有机肥、化肥施用调查与思考[J].黑龙江农业科学,(4):39-49.
66.姚丽贤,周修冲,蔡永发,2004.不同采样密度下土壤特性的空间变异特征及其推估精度研究[J].土壤,36(5):538-542.
67.张爱君,张明普,张洪源,1999.土壤基础肥力对夏玉米养分吸收和产量的影响[J].玉米科学,7(2):71-74.
68.张有山,林启美,秦耀东,1998.大比例尺区域土壤养分空间变异定量分析[J].华北农学报,13(1):122-128.
69.张灵,王绪芳,2007.兰州市南北两山土壤养分空间分布及其影响因子[J].兰州大学学报(自然科学版),43(3):53-57.
70.赵荣芳,陈新平,张福锁,2009.华北地区冬小麦-夏玉米轮作体系的氮素循环与平衡[J].土壤学报,46(4):684-697.
71.中国农业科学院土壤肥料研究所,1986.中国化肥区划[M].中国农业科技出版社,北京:15-28.
72.中国农业年鉴编辑委员会编,2006.中国农业年鉴[M].北京:农业出版社.
73.中华人民共和国国家统计局,2008.中国统计年鉴[M].北京:中国统计局出版
74.周惠珍,1991. 1:100万土壤-土地图数据库及土壤退化信息解释[J].土壤学报,8(4):355-371.
75.周惠珍,龚子同,1996.土壤空间变异性研究[J].土壤学报,33(3):232-241.
76.赵春江,薛绪掌,王秀,2003.精准农业技术体系的研究进展与展望[J].农业工程学报,19(4):7-12.
77.朱兆良,1999.施肥与农业和环境[J].科学中国人,6:2-4.
78. Arvind K., Shukla V.K., Singh B.S., et al.., 2004. Site- specific Nutrient Management for Maximum Economic Yield of the Rice-Wheat Cropping System[J]. Better Crops, 88(4): 18-21.
79. Barriga C.S., Menjivar J.C., Mite F., 2006. Validation of a site specific management for plant nutrition in the cocoa crop in the province of Guayas, Ecuador[J]. Acta Agronomical, 55(3): 15-22.
80. Baxter S.J., Oliver M.A., et al., 2003. A Geostatistical Analysis of the Spatial Variation of Soil Mineral Nitrogen and Potentially Available Nitrogen Within an Arable Field[J]. Precision Agriculture, 4(2): 213-226.
81. Bekele A, Hudnall W.H., Daigle J.J., et al., 2005. Scale dependent variability of soil electrical conductivity by indirect measures of soil properties[J]. Journal of Terramechanics, 42(3-4): 339-351.
82. Bellehumeur C., Legendre P., Marcotte D., et al., 1997. Variance and spatial scales in a tropical rain forest: changing the size of sampling units[J]. Plant Ecology, 130(1): 89-98.
83. Bellehumeur, C., Legendre P., 1998. Multiscale sources of variation in ecological variables: modeling spatial dispersion, elaborating sampling designs[J]. Landscape Ecology, 13:15-25.
84. Benayas J., Sánchez-Colomer M., Escudero A., et al., 2004. Landscape- and field-scale control of spatial variation of soil properties in Mediterranean montane meadows[J]. Biogeochemistry,69(2): 207-225.
85. Bemdtsson R., Bahri A., Jinno K., 1993. Spatial dependence of geochemical elements in a semiarid agricultural field:ⅡGeostatistical Properties[J]. Soil Sci, 57: 1323 -1329.
86. Benjamin J.G., Porter L.K., Duke H.R., et al., 1997. Corn growth and nitrogen up take with furrow irrigation and fertilizer bands[J]. Agron J, 89: 609-612.
87. Blackmore B.S., 1994. Precision Farming: An Introduction. Outlook on Agriculture[J]. CABI, 23(4): 275-280.
88. Bl?schl G., Sivapalan M., 1995. Scale issues in hydrological modelling - a review[J]. Hydrol. Processes, 9: 251-290.
89. Boyer D.G., Wright R.J., Feldhake C.M., et al., 1991. Soil spatial variability in steeply sloping acid soil environment[J]. Soil Science, 161: 278-287.
90. Brian Slater, 2006. Spatial Variability[J]. Encyclopedia of Soil Science, 1(1): 1670-1674.
91. Burrough P.A., 2001. GIS and geostatistics: Essential partners for spatial analysis[J]. Environmental and Ecological Statistics, 8(4): 361-377.
92. Burgess T.M., Webster R., 1980. Optimal interpolation and isarithmic mapping of soil properties. Ⅰ. The semi-variogram and punctual kriging[J]. Soil Sci, 31: 315-331.
93. Cahn M.D., Hummel J.W., Brouer B.H., 1994. Spatial analysis of soil fertility for site-specific crop management[J]. Soil Society of America Journal, 58: 1240-1248.
94. Cambardella C.A., Moorman T.B., Novak J.M., et al., 1994. Field-scale variability of soil properties in central lowa soil[J]. Soil Sci Soc Am J, 58: 1501-1511.
95. Cambardella C.A., Karlen D.L., 1999. Spatial Analysis of Soil Fertility Parameters[J]. Precision Agriculture, 1(1): 5-14.
96. Campbell J.B., 1978. Spatial variation of sand content and pH with in single contiguous delineation of two soil mapping units[J]. Soil Sci. Am. J., 42: 460-464.
97. Cassel D.K., Wendroth O., Nielsen D.R., 2000. Assessing Spatial Variability in an Agricultural Experiment Station Field: Opportunities Arising from Spatial Dependence[J]. Agron, 92: 706-714.
98. Castrignano A., Maiorana M., Fornaro F., 2003. Using regionalised variables to assess field-scale spatiotemporal variability of soil impedance for different tillage management[J]. Biosystems Engineering, 85(3): 381-392.
99. Chien Y.J., DarY.L., Hong-Y.G., et al., 1997. Geostatistical analysis of mid-west TaiWan soil[J]. Soil Science, 162(4): 151-162.
100. Cohen M.J., Dunne E.J., Bruland G.L., 2008. Spatial variability of soil properties in cypress domes surrounded by different land uses[J]. Wetlands, 28(2): 411-422.
101. Da-Gang Yuan, Gan-Lin Zhang, Zi-Tong Gong, et al., 2007. Variations of soil phosphorus accumulation in Nanjing China as affected by urban development[J] Journal of Plant Nutrition and Soil Science[J]. 170(2): 244-249.
102. Dludlu D.L., 1990. Variable fertilizer rate trials based on spatial variability of soil characteristics and yield goal[J]. Dissertation Abstracts International. B, Sciences and Engineering, 51(4): 15-57B.
103. Earl R., Wheeler P.N., Blaekmore B., et al., 1996. Precision farming: the Management of variability[J]. Landwards, 51(4): 18-23.
104. Emmerling C., Udelhoven T., 2002. Discriminating factors of the spatial variability of soil qualityparameters at landscape-scale[J]. Journal of Plant Nutrition and Soil Science, 165(6): 706-712.
105. FAO, 2004. Statistical databases[S]. Food and Agriculture Organization (FAO) of the United Nations.
106. Farina A., 2006. Principles and methods in landscape ecology[M]. Chapman & Hall: London.
107. Fleming K.L., Westfall D.G.., Wiens D.W., et al., 2000. Evaluating farmer defined management zone maps for variable rate fertilizer application[J]. Precis. Agric.2: 201-215.
108. Franklin R.B., Mills A.L.M., 2003. Multi-scale variation in spatial heterogeneity for microbial community structure in an eastern Virginia agricultural field[J]. FEMS Microbiology Ecology, 44(3): 335-346.
109. Franzen, D.W., Peck T.R., 1995. Field soil sampling density for variable rate fertilization[J]. Prod. Agric, 8: 568-574.
110. Franzen D.W., Hofman V.L., Halvorson A.D., et al., 1996. Sampling for site specitic farming: Topograghy and nutrient considerations[J]. Better Crops, 80(3): 14-18.
111. Francisca L.G., Montserrat J.E., Silvia A., 2002. Spatial variability of agricultural oil parameters in southern Spain[J]. Plant and Soil, 246(1): 97-105.
112. Francisco, S.M., Birgitta B., Henrik E., et al., 2007. Aboveground nitrogen in relation to estimated total plant uptake in maize and bean[J]. Nutr.Cycl.Agro., 79:125-129.
113. Garten, C.T., Kang S., Brice D.J., 2007. Variability in soil properties at different spatial scales(1 m -1 km)in a deciduous forest ecosystem[J]. Soil biology & biochemistry, 39(10): 2621-2627.
114. Gilbert C., Sigua, Wayne, et al., 2008. Kriging analysis of soil properties[J]. Soils Sediments, 8: 193-202.
115. Goos R.J., Schimelfenig J.A., Bock B.R., et al., 1999. Response of spring wheat to nitrogen fertilizers of different nitrification rates[J]. Agron J, 91: 287-293.
116. Goovaerts P., 1999. Geostatisties insoil seience:state-of-the-art and perspectives[J]. Geoderm, 89: l-45.
117. Goovaerts P., 2001. Geostatistical modeling of uncertainty in soil science[J]. Geoderma, 103: 3-26.
118. Gupta R.K, Motaghimi S., Mcclellan P.W, et al., 1997. Spatial variability and sampling strategies for NO3--N, P, K determinations for site-specific farming[J]. Trans. ASAE, 40: 337-343.
119. Gupta R.K., Mostaghimi S., McClellan P.W., et al., 1999. Modeling Spatial Variability of Soil Chemical Parameters for Site-Specific Farming Using Stochastic Methods[J]. Water, Air & Soil Pollution, 10(1-2): 17-34.
120. Hallett P.D., Nunan N., Douglas J.T., 2004. Millimeter-Scale Spatial Variability in Soil Water Sorptivity: Scale, Surface Elevation and Subcritical Repellency Effects[J]. Soil Science Society of America, 68: 352-358.
121. Han S., Hummel J.W., Goering C.E., et al., 1994. Cell size selection for site-specific crop management[J]. Trans, ASAE, 37: 19-26.
122. Heuvelink G.B.M., Webster R., 2001. Modelling soil variation: Past, Present and future[J]. Geoderma, 100(3-4): 269-301.
123. Itaru Okuda, Masanori Okazaki, Takusei Hashitani, 1995. Spatial and temporal variations in the chemical weathering of Basaltic Pyroclastic materials[J]. Soil. Sci. Soc.Am. J. 59: 887-894.
124. Jiang P., Thelen K. D., 2004. Effect of Soil and Topographic Properties on Crop Yield in a North- Central Corn-Soybean Cropping System[J]. Agron. J. 96: 252-258.
125. Jose E., Francisco M., Sergio C., et al., 2006. GIS-based Site-Specific Management of Cocoa[J]. Better Crops, 90(1): 36-39.
126. Kamgar A., Hopmans J.W., Wallender W.W., et al., 1993. On plot size and sample number of neutron probe measurements in small field trials[J]. Soil Sci, 156: 213-224.
127. Junta Y., Keun L C., Mikio U., et al., 2002. Spatial variability of soil properties and rice yield in paddies: IS Precision agriculture worth practicing?[J]. World Congress of Soil Science(WCSS), 17: 14-21.
128. Khosla R., Fleming K., Delgado J.A., et al., 2002. Use of Site-specific management zones to improve nitrogen management for precision agriculture[J]. Journal of Soil and Water Conservation, 57: 5l3-5l8.
129. Kim D., Keun B., Park S., 2008. Identification and visualization of complex spatial pattern of coastal dune soil properties using gis-based terrain analysis and geostatistics[J]. Journal of Coastal Research, 24(4C): 50-60.
130. Koch B., Khosla R., Frasier W.M., et al., 2004. Economic Feasibility of Variable-Rate Nitrogen Application Utilizing Site-Specific Management Zones[J]. American Society of Agronomy, 98: 1572-1580.
131. Kravchenko A.N., Bullock D.G., 2000. Correlation of corn and soybean grain yield with topography and soil properties[J]. Agron.J, 92: 75-83.
132. Lin H.S, Wheeler D., Bell J., et al 2005. Assessment of soil spatial variability at multiple scales[J]. Ecological Modeling, 182: 271-290.
133. Liu X.M., Xu J.M., Zhang M.K., et al., 2004. Application of geostatistics and GIS technique to characterize spatial variabilities of available micronutrients in paddy soils[J]. Environmental Geology, 46: 189-194.
134. Liu X.M., Zhao K.L., Xu J.M., et al., 2008. Spatial variability of soil organic matter and nutrients in paddy fields at various scales in southeast China[J]. Environmental geology, 53(5): 1139-1147.
135. Lucy O.D., Deborah L., Gregory S.O., 2007. Changes in the spatial variation of soil properties following shifting cultivation in a Mexican tropical dry forest[J]. Biogeochemistry, 84(1): 99-113.
136. Malo D.D., Worcester B.K., 1975. Soil fertility and crop responses at selected landscape positions[J]. Agron.J., 67: 379-401.
137. Miao Y., Mulla D.J., Robert, P.C., 2006. Spatial Variability of Soil Properties, Corn Quality and Yield in Two Illinois, USA Fields: Implications for Precision Corn Management[J]. Precision Agriculture, 7(1): 5-20.
138. Mulla D.J., 1989. Soil spatial variability and methods of analysis. In Retard C.M. et al.(ed). Soil, crop and water management systems of rained agriculture in the Sudan-Sahelian zone[J]. Proc. Int.Workshop. Niamey, Niger. 7-11 Jan.1987. ICRSAT, Patancheru, Andhra Pradesh, India: 241-252.
139. Mulla D.J., 1993. Mapping and managing spatial patterns in soil fertility and crop yield[M]. In: Robert PC, Rust RH and L arson W E, eds. Soil specific crop management. ASA, CSSA, SSSA, Madison, W I: 15-26.
140. Neill R.V., Krummel J.R., Gardner R.H., 1988. Indices of landscape pattern[J]. Landscape Ecology, 1: 153-162.
141. Ovalles F.A., Collins M.E., 1986, Soil-landscape relationships and soil variability in north central Florida[J]. Soil Sci Soc, 50: 401-408.
142. Parkin T.B., 1993. Spatial variability of microbial process in soil-a review[J]. Emviron. Qual. 22: 409-417.
143. Pierce F.J., et al., 1995. Yield and nutrient variability in glacial soils of Michigan [J]. Site-Specific Management for Agricultural Systems[J]. ASA-CSSA-SSSA: 133-152.
144. Ping J.L., Green C.J., Zartman R.E., 2008. Spatial Variability of Soil Properties, Cotton Yield and Quality in a Production Field[J]. Communications in soil science and plant analysis, 39(1-2) : 1-16.
145. Robert P.C., 2002. Precision agriculture: a challenge for crop nutrition management[J]. Plant and Soil, 247: 143-149.
146. Rodrigo A.O., Oscar A.S., 2007. Determination of management zonesin corn (Zea mays L.) based on soil fertility[J]. Computers and Electronics in Agriculture, 58(1): 49-59.
147. Ritters K.H., Neill R.V., Hunsaker C.T., et al., 1995. A factor analysis of landscape and structure metrics[J]. Landscape Ecology, 10: 23-39.
148. Ryan J., Singh M., Yau S.K., 1998. Spatial variability of soluble boron in Syrian soils[J]. Soil & Tillage Research, 45: 407-417.
149. Samake O, Smaling E.M.A, Kropff M.J., et al., 2005. Effects of cultivation practies on spatial variabition of soil fertility and millet yields in the Sahel of Mail[J]. Agriculture,Ecosystems & Environment, 109(3-4): 335-345.
150. Santos D., Murphy S.L.S., Taubner H., 1997. Uniform separation of Concentric surface layers from soil aggregates[J]. Soil Sci.Soc.Am.J. 61: 720-724.
151. Huang S.W., Jin J.Y., Yang L.P., et al., 2006. Spatial variability of soil nutrients and influencing factors in a vegetable production area of Hebei Province in China[J]. Nutr Cycl Agroecosyst, 75: 201-212.
152. Sidorova V.A., Krasilnikov P.V., 2007. Soil-Geographic Interpretation of Spatial Variability in the Chemical and Physical Properties of Topsoil Horizons in the Steppe Zone[J]. Eurasian Soil Science, 40(10): 1042-1051.
153. Sigua G.C., Hudnall W.H., 2008. Kriging analysis of soil properties[J]. Journal of Soils and Sediments, 8(3): 193-202.
154. Solie J.B., Raun W.R., Stone M.L., 1999. Submeter spatial variability of selected soil and bermudagrass production variables[J]. Soil Sci Soc Am J, 63: 1724-1733.
155. Souza L.S., Cogo N.P., Vieira S.R., 1998. Soil spatial variability of phosphorus, potassium andorganic matter, in relation to management systems[J]. Revista Brasileira de Ciencia do Solo, 22(1): 77-86.
156. Stolt M.H., Baker J.C., Simpson T.W, 1993. Soil-landscape relationships in Virginia Soil variability and parent material uniformity[J]. Soil Sci, 57: 414-421.
157. Stafford J.V., 2000. Implementing Precision Agriculture in the 21st Century[J]. Journal of Agricultural Engineering Research, 76(3): 267-275.
158. Stenger R., Priesack E., Beese F., 2002. Spatial variation of nitrate-N and related soil properties at the plot-scale[J]. Geoderma, 105(3-4): 259-275.
159. Sylla M., Steln A., Breemen N., et al., 1995. Spatial variability of soil salinity at different scales in the mangrove rice agro-ecosystem in West Africa[J]. Agriculture Ecosystem & Environment, 54: 1-15.
160. Tatsuya I., Kei G., Michihisa I., et al., 2004. Geostatistical analysis of yield, soil properties and crop management practices in paddy rice fields[J]. Plant Prod. Sci., 7(2): 230-239.
161. Taylor J.C., Wood G.A., Earl R., 2003. Soil factors and their influence on within-field crop variability,Part II: Spatial analysis and determination of management zones. (Special issue: Precision agriculture - managing soil and crop variability for cereals)[J]. Biosystems Engineering, 84(4): 441-453.
162. Tsegaye T., Hill R.L., 1998. Intensive tillage effects on spatial variability of soil test, plant growth, and nutrient uptake measurements[J], Soil Science, 163(2): 155-165.
163. Tening A.S., Omueti J.I., 1995. Potassium status of some selected soils under different land-use systems in the subhumid zone of Nigerial[J]. Commun.Sol.Sci.Plant Anal, 26(5&6): 657-672.
164. Timsina J., Connor D.J., 2001. Productivity and management of rice-wheat cropping systems: issues and challenges[J]. Field Crops Res, 69: 93-132.
165. Trangmar B.B., Yost R.S., Uehara G., 1985. Application of geostatistics to spatial studies of soil properties[J]. Advance in Agronomy, Academic Press, 38: 45-94.
166. Tsegaye T., Hill R.L., 1998. Intensive tillage effects on spatial variability of soil test,plant growth, and nutrient uptake measurements[J]. Soil Science, 163(2): 155-165.
167. Udoyara S.T., Robert J., 1994. Evaluating Agricultural Nonpoint-Source Pollution Using Integrated Geographic Information Systems and Hydrologic/Water Quality Model[J]. J. Environ Qual, 23: 25-35.
168. Wang X.Z., Liu G.S., Hu H.C., 2009. Determination of management zones for a tobacco field based on soil fertility[J]. Computers and Electronics in Agriculture, 65(2): 168-175.
169. Wagenet R.J., 1998. Scale issues in agroecological research chains[J]. Nutrient Cycling in Agroecosystems, 50: 23-34.
170. Webster R., 1985. Quantitative spatial analysis of soil in the field[J]. Advances in Soi1 Seience, 3: 1-70.
171. Webster R., 2000. Is soil variation random?[J]. Geoderma, 97: 149-163.
172. Wei J., Wu G., Deng H.B., et al., 2004. Spatial pattern of soil carbon and nutrient storage at theAlpine tundra ecosystem of Changbai Mountain, China[J]. Journal of Forestry Research, 15(4): 249-254.
173. White J.G., Welch R.M., Novell W.A., 1997. Soil Zn map of the USA using Geostatistics and Geographic information systems[J]. Soil Sci.Soc.Am.J, 61: 185-194.
174. Wild A., 1971. The potassium status of soils in the savanna zone of Nigeria[J]. Expl. Agric., 7: 257-270.
175. Wilcke W., 2000. Small-scale variability of metal concentrations in soil leachates[J]. Soil Sci. Soc. Am. J., 64: 138-143.
176. Wollenhaupt N.C., Wolkowski R.P., Clayton M.K., 1994. Mapping soil test phosphorus and potassium for variable-rate fertilizer application[J]. Prod. Agric, 7: 441-448.
177. Yang C., Anderson G.L., King J.H., et al., 1999. Comparison of uniform and variable rate fertilization strategies using grid soil sampling, variable rate technology, and yield moni-toring: 675-686. In P.C. Robert, R.H. Rust, and W.E. Larson (ed.) Precision agriculture. Proc. Int. Conf., 4th, St. Paul, MN. 19-22 July 1998. ASA, CSSA, and SSSA, Madison, WI.
178. Yanai J., Lee C.K., Umeda M., et al., 2000. Spatial variability of soil chemical properties in a paddy field[J]. Japanese Journal of Soil Science and Plant Nutrition, 71(4): 520-529.
179. Yuan X.Y., Chai X.R., Gao R., et al., 2007. Temporal and spatial variability of soil organic matter in a county scale agricultural ecosystem[J]. New Zealand Journal of Agricultural Research, 50(5): 1157-1168.
2.白由路,金继运,杨俐苹,2001.基于GIS的土壤养分分区管理模型研究[J].中国农业科学,34(1):46-50.
3.白由路,金继运,2001.我国精准农业发展模式探讨[G]//精准农业与土壤养分管理,中国大地出版社,北京:17-22.
4.曹慧,杨浩,赵其国等,2002.太湖流域丘陵地区土壤养分的空间变异[J].土壤,(4):201-205.
5.曹志洪,1998.科学施肥与我国粮食安全保障[J].土壤,2:57-63.
6.陈恩凤,1990.土壤肥力物质基础及其调控[M].北京:科学出舨社,338-378.
7.陈光,贺立源,2008.耕地养分空间插值技术与合理采样密度的比较研究[J].土壤通报,39(5):1007-1011.
8.陈蓉蓉,周治国,曹卫星等,2004.基于GIS的农田土壤、作物特征空间变异性及其相互关系[J].应用生态学报,15(9):1678-1680.
9.封志明,李香莲,2000.耕地耕地与粮食安全战略:藏粮于土,提高中国土地资源的综合生产能力[J].地理学与国土研究,16(3):1-5.
10.高强,李德忠,黄立华等,2008.吉林玉米带玉米一次性施肥现状调查分析[J].吉林农业大学学报, 30(3):301-305.
11.高祥照,胡克林,郭焱,2002.土壤养分与作物产量的空间变异特征与精确施肥[J].中国农业科学,35(6):660-666.
12.高义民,同延安,胡正义,2006.黄土区村级农田土壤养分空间变异特征研究[J].土壤通报, 37(1):1-6.
13.国家环境保护总局,2001. 2000年中国环境状况公报[J].环境保护,(7):3-9.
14.国家粮食局.中国粮食年鉴[M].北京:经济管理出版社,2006:586.
15.国家粮食局.中国粮食年鉴[M].北京:经济管理出版社,2007:542
16.郭旭东,傅伯杰,2000.基于GIS和地统计学的土壤养分空间变异特征研究[J].应用生态学报,11(4):555-563.
17.韩金玲,李雁鸣,马春英等,2006.施锌对小麦开花后氮、磷、钾、锌积累和运转的影响[J].植物营养与肥料学报,12(3):313-320.
18.何文寿,2004.植物营养学通论[M].宁夏人民出版社,银川:313-330.
19.胡田田,刘翠英,李岗等,2001.施肥对土壤供肥和冬小麦养分吸收及其产量的影响[J].干旱地区农业研究,19(3):36-41.
20.华孟,王坚,1992.土壤物理学[M].北京农业大学出版社,北京:214-243.
21.黄昌勇,2000.土壤学[M].中国农业出版社,北京:221-223.
22.黄绍文,金继运,杨俐苹,2002.乡(镇)级区域土壤养分空间变异与分区管理技术研究[J].资源科学,24(2):76-82.
23.黄绍文,金继运,杨俐苹,2003.县级区域粮田土壤养分空间变异与分区管理技术研究[J].土壤学报,40(1):79-88.
24.扈立家,李天来,2005.我国发展精准农业的问题及对策[J].沈阳农业大学学报(社会科学版),7(4):400-402.
25.胡克林,李保国,林启美等,1999.农田土壤养分的空间变异性特征[J].农业工程学报,15(3):33-38.
26.候景儒,郭光裕,1993.矿床统计预测及地质统计学的理论与应用[M].北京:冶金工业出版社.
27.雷咏雯,危常州,李俊华,2004.不同尺度下土壤养分空间变异特征的研究[J].土壤,36(4):376-381.
28.冷玲,刘双全,魏颖,2007.双城土壤养分空间变异与玉米分区施肥技术研究[J].黑龙江农业科学,(4):38-40.
29.李瑞,白由路,2007.上海市规模经营农场的土壤养分与水稻产量空间变异特征[J].中国土壤与肥料,(3):40-76.
30.李翔,潘瑜春,赵春江等,2005.基于多年产量数据的精准农业管理分区提取与尺度效应评价[J].中国农业科学,38(9):1825-1833.
31.李玉影,刘双全,迟宏伟,2005.土壤养分空间变异与大豆分区施肥技术研究[J].中国农学通报,21(11):238-240.
32.廖桂堂,李廷轩,王永东等,2008.不同尺度下低山茶园土壤主要微量元素的空间变异性[J].土壤,40(2):257-263.
33.姜城,2000.不同经营体制下土壤养分空间变异规律以及管理技术的研究[D].中国农业科学院研究生院.
34.金继运,1998.“精准农业”及其在我国的应用前景[J].植物营养与肥料学报,4(l):1-7.
35.金继运,李家康,李书田,2006.化肥与粮食安全[J].植物营养与肥料学报,12(5):601-609.
36.巨晓棠,张福锁.中国北方土壤硝态氮的累积及其对环境的影响.生态环境,2003,12,(1):24-28.
37.李哈滨,王政权,王庆成,1998.空间异质性研究理论与方法[J].应用生态学报,9(6):651-657.
38.李庆逵,朱兆良,于天仁,1998.中国农业持续发展中的肥料问题[M].南昌:江西科学技术出版社.
39.李世清,高亚军,李生秀,2000.土壤养分的空间变异性及确定样本容量的研究[J].土壤与环境,9(l):56-59.
40.李小昱,雷廷武,王为,2000.农田土壤特性的空间变异性及Kriging估值法[J].西北农业大学学报,28(6):30-35.
41.李子忠,龚元石,2001.不同尺度下田间土壤水分和混合电导率空间变异性与套合结构模型[J].植物营养与肥料学报,7(3):255-261.
42.雷志栋,杨诗秀等,1985.土壤特性时空变异性初步研究[J].水利学报,(9):10-21.
43.宁茂岐,刘洪斌,武伟,2007.两种取样尺度下土壤重金属空间变异特征研究[J].中国生态农业学报,15(3):86-91.
44.米丽娜,王芳,李友宏等,2009.宁夏平原淤灌土土壤养分与作物产量的空间变异性[J].干旱区研究,26(4):508-513.
45.秦松,樊燕,刘洪斌,2007.地形因子与土壤养分空间分布的相关性研究[J].水土保持研究,14(4):276-279.
46.秦耀东,1992.土壤空间变异研究中的定量分析[M].地球科学进展,7(l):44-49.
47.沈思渊,1989.地统计学在土壤空间变异研究中的应用及其展望[J].土壤学进展,17(3):11-25.
48.盛建东,肖华,武红旗等,2005.不同取样尺度农田土壤速效养分空间变异特征初步研究[J].干旱地区农业研究,23(2):64-67.
49.盛建东,肖华,武红旗等,2006.不同取样间距农田土壤全量养分空间变异特征研究[J].土壤通报,37(6):1062-1065.
50.宋晓宇,王纪华,刘良云,2007.基于Quickbird遥感影像的农田管理分区划分研究[J].中国农业科学,40(9):1996-2006.
51.宋永林,唐华俊,李小平等,2007.长期施肥对作物产量及褐潮土有机质变化的影响研究[J].华北农学报,22(增刊):100-105.
52.汤勇华,黄耀,2008.中国大陆主要粮食作物地力贡献率及其影响因素的统计分析[J].农业环境科学学报,27(4):1283-1289.
53.王同朝,李凤民,王俊等,1999.分层供水施磷对春小麦光合性能、同化产物流向和水分利用效率的影响[J].植物生态学报,23(2):177-185.
54.王兴仁,陈新平,张福锁等,1998.施肥模型在我国推荐施肥中的应用[J].植物营养与肥料学报,4(1):67-73.
55.王学锋,1993.土壤特性时空变异性研究的评述与展望[J].土壤学进展,21(4):42-49.
56.王宗明,张柏,宋开山,2007.东北平原典型农业县农田土壤养分空间分布影响因素分析[J].水土保持学报,121(12):73-77.
57.王政权,1999.地统计学及在生态学中的应用[M].科学出版社,北京:150-156.
58.谢高地,陈沈斌等,2005.环境的空间连续变异与精准农业[M].气象出版社,北京:65-66.
59.徐尚平,陶澎,徐福留,2000.内蒙土壤微量元素含量的空间结构特征[J].地理学报,55(3):337-345.
60.徐英,陈亚新,史海滨等,2004.土壤水盐空间变异尺度效应的研究[J].农业工程学报,20(2):l-5.
61.薛正平,杨星卫,段项锁,2002.土壤养分空间变异及合理取样数研究[J].农业工程学报,18(4):6-9.
62.薛正平,杨星卫,段项锁等,2004.土壤养分与春小麦产量关系及最佳施肥量研究[J].中国生态农业学报,12(4):110-112.
63.杨俐苹,姜城,金继运等,2000.棉田土壤养分精准管理初探[J].中国农业科学,33(6):67-72.
64.杨建锋,邓伟,章光新,2006.田块尺度苏打盐渍土盐化和碱化空间变异特征[J].土壤学报(3):500-505.
65.杨忠生,赵丽岩,刘君阁,2005.桦川县土壤肥力现状及有机肥、化肥施用调查与思考[J].黑龙江农业科学,(4):39-49.
66.姚丽贤,周修冲,蔡永发,2004.不同采样密度下土壤特性的空间变异特征及其推估精度研究[J].土壤,36(5):538-542.
67.张爱君,张明普,张洪源,1999.土壤基础肥力对夏玉米养分吸收和产量的影响[J].玉米科学,7(2):71-74.
68.张有山,林启美,秦耀东,1998.大比例尺区域土壤养分空间变异定量分析[J].华北农学报,13(1):122-128.
69.张灵,王绪芳,2007.兰州市南北两山土壤养分空间分布及其影响因子[J].兰州大学学报(自然科学版),43(3):53-57.
70.赵荣芳,陈新平,张福锁,2009.华北地区冬小麦-夏玉米轮作体系的氮素循环与平衡[J].土壤学报,46(4):684-697.
71.中国农业科学院土壤肥料研究所,1986.中国化肥区划[M].中国农业科技出版社,北京:15-28.
72.中国农业年鉴编辑委员会编,2006.中国农业年鉴[M].北京:农业出版社.
73.中华人民共和国国家统计局,2008.中国统计年鉴[M].北京:中国统计局出版
74.周惠珍,1991. 1:100万土壤-土地图数据库及土壤退化信息解释[J].土壤学报,8(4):355-371.
75.周惠珍,龚子同,1996.土壤空间变异性研究[J].土壤学报,33(3):232-241.
76.赵春江,薛绪掌,王秀,2003.精准农业技术体系的研究进展与展望[J].农业工程学报,19(4):7-12.
77.朱兆良,1999.施肥与农业和环境[J].科学中国人,6:2-4.
78. Arvind K., Shukla V.K., Singh B.S., et al.., 2004. Site- specific Nutrient Management for Maximum Economic Yield of the Rice-Wheat Cropping System[J]. Better Crops, 88(4): 18-21.
79. Barriga C.S., Menjivar J.C., Mite F., 2006. Validation of a site specific management for plant nutrition in the cocoa crop in the province of Guayas, Ecuador[J]. Acta Agronomical, 55(3): 15-22.
80. Baxter S.J., Oliver M.A., et al., 2003. A Geostatistical Analysis of the Spatial Variation of Soil Mineral Nitrogen and Potentially Available Nitrogen Within an Arable Field[J]. Precision Agriculture, 4(2): 213-226.
81. Bekele A, Hudnall W.H., Daigle J.J., et al., 2005. Scale dependent variability of soil electrical conductivity by indirect measures of soil properties[J]. Journal of Terramechanics, 42(3-4): 339-351.
82. Bellehumeur C., Legendre P., Marcotte D., et al., 1997. Variance and spatial scales in a tropical rain forest: changing the size of sampling units[J]. Plant Ecology, 130(1): 89-98.
83. Bellehumeur, C., Legendre P., 1998. Multiscale sources of variation in ecological variables: modeling spatial dispersion, elaborating sampling designs[J]. Landscape Ecology, 13:15-25.
84. Benayas J., Sánchez-Colomer M., Escudero A., et al., 2004. Landscape- and field-scale control of spatial variation of soil properties in Mediterranean montane meadows[J]. Biogeochemistry,69(2): 207-225.
85. Bemdtsson R., Bahri A., Jinno K., 1993. Spatial dependence of geochemical elements in a semiarid agricultural field:ⅡGeostatistical Properties[J]. Soil Sci, 57: 1323 -1329.
86. Benjamin J.G., Porter L.K., Duke H.R., et al., 1997. Corn growth and nitrogen up take with furrow irrigation and fertilizer bands[J]. Agron J, 89: 609-612.
87. Blackmore B.S., 1994. Precision Farming: An Introduction. Outlook on Agriculture[J]. CABI, 23(4): 275-280.
88. Bl?schl G., Sivapalan M., 1995. Scale issues in hydrological modelling - a review[J]. Hydrol. Processes, 9: 251-290.
89. Boyer D.G., Wright R.J., Feldhake C.M., et al., 1991. Soil spatial variability in steeply sloping acid soil environment[J]. Soil Science, 161: 278-287.
90. Brian Slater, 2006. Spatial Variability[J]. Encyclopedia of Soil Science, 1(1): 1670-1674.
91. Burrough P.A., 2001. GIS and geostatistics: Essential partners for spatial analysis[J]. Environmental and Ecological Statistics, 8(4): 361-377.
92. Burgess T.M., Webster R., 1980. Optimal interpolation and isarithmic mapping of soil properties. Ⅰ. The semi-variogram and punctual kriging[J]. Soil Sci, 31: 315-331.
93. Cahn M.D., Hummel J.W., Brouer B.H., 1994. Spatial analysis of soil fertility for site-specific crop management[J]. Soil Society of America Journal, 58: 1240-1248.
94. Cambardella C.A., Moorman T.B., Novak J.M., et al., 1994. Field-scale variability of soil properties in central lowa soil[J]. Soil Sci Soc Am J, 58: 1501-1511.
95. Cambardella C.A., Karlen D.L., 1999. Spatial Analysis of Soil Fertility Parameters[J]. Precision Agriculture, 1(1): 5-14.
96. Campbell J.B., 1978. Spatial variation of sand content and pH with in single contiguous delineation of two soil mapping units[J]. Soil Sci. Am. J., 42: 460-464.
97. Cassel D.K., Wendroth O., Nielsen D.R., 2000. Assessing Spatial Variability in an Agricultural Experiment Station Field: Opportunities Arising from Spatial Dependence[J]. Agron, 92: 706-714.
98. Castrignano A., Maiorana M., Fornaro F., 2003. Using regionalised variables to assess field-scale spatiotemporal variability of soil impedance for different tillage management[J]. Biosystems Engineering, 85(3): 381-392.
99. Chien Y.J., DarY.L., Hong-Y.G., et al., 1997. Geostatistical analysis of mid-west TaiWan soil[J]. Soil Science, 162(4): 151-162.
100. Cohen M.J., Dunne E.J., Bruland G.L., 2008. Spatial variability of soil properties in cypress domes surrounded by different land uses[J]. Wetlands, 28(2): 411-422.
101. Da-Gang Yuan, Gan-Lin Zhang, Zi-Tong Gong, et al., 2007. Variations of soil phosphorus accumulation in Nanjing China as affected by urban development[J] Journal of Plant Nutrition and Soil Science[J]. 170(2): 244-249.
102. Dludlu D.L., 1990. Variable fertilizer rate trials based on spatial variability of soil characteristics and yield goal[J]. Dissertation Abstracts International. B, Sciences and Engineering, 51(4): 15-57B.
103. Earl R., Wheeler P.N., Blaekmore B., et al., 1996. Precision farming: the Management of variability[J]. Landwards, 51(4): 18-23.
104. Emmerling C., Udelhoven T., 2002. Discriminating factors of the spatial variability of soil qualityparameters at landscape-scale[J]. Journal of Plant Nutrition and Soil Science, 165(6): 706-712.
105. FAO, 2004. Statistical databases[S]. Food and Agriculture Organization (FAO) of the United Nations.
106. Farina A., 2006. Principles and methods in landscape ecology[M]. Chapman & Hall: London.
107. Fleming K.L., Westfall D.G.., Wiens D.W., et al., 2000. Evaluating farmer defined management zone maps for variable rate fertilizer application[J]. Precis. Agric.2: 201-215.
108. Franklin R.B., Mills A.L.M., 2003. Multi-scale variation in spatial heterogeneity for microbial community structure in an eastern Virginia agricultural field[J]. FEMS Microbiology Ecology, 44(3): 335-346.
109. Franzen, D.W., Peck T.R., 1995. Field soil sampling density for variable rate fertilization[J]. Prod. Agric, 8: 568-574.
110. Franzen D.W., Hofman V.L., Halvorson A.D., et al., 1996. Sampling for site specitic farming: Topograghy and nutrient considerations[J]. Better Crops, 80(3): 14-18.
111. Francisca L.G., Montserrat J.E., Silvia A., 2002. Spatial variability of agricultural oil parameters in southern Spain[J]. Plant and Soil, 246(1): 97-105.
112. Francisco, S.M., Birgitta B., Henrik E., et al., 2007. Aboveground nitrogen in relation to estimated total plant uptake in maize and bean[J]. Nutr.Cycl.Agro., 79:125-129.
113. Garten, C.T., Kang S., Brice D.J., 2007. Variability in soil properties at different spatial scales(1 m -1 km)in a deciduous forest ecosystem[J]. Soil biology & biochemistry, 39(10): 2621-2627.
114. Gilbert C., Sigua, Wayne, et al., 2008. Kriging analysis of soil properties[J]. Soils Sediments, 8: 193-202.
115. Goos R.J., Schimelfenig J.A., Bock B.R., et al., 1999. Response of spring wheat to nitrogen fertilizers of different nitrification rates[J]. Agron J, 91: 287-293.
116. Goovaerts P., 1999. Geostatisties insoil seience:state-of-the-art and perspectives[J]. Geoderm, 89: l-45.
117. Goovaerts P., 2001. Geostatistical modeling of uncertainty in soil science[J]. Geoderma, 103: 3-26.
118. Gupta R.K, Motaghimi S., Mcclellan P.W, et al., 1997. Spatial variability and sampling strategies for NO3--N, P, K determinations for site-specific farming[J]. Trans. ASAE, 40: 337-343.
119. Gupta R.K., Mostaghimi S., McClellan P.W., et al., 1999. Modeling Spatial Variability of Soil Chemical Parameters for Site-Specific Farming Using Stochastic Methods[J]. Water, Air & Soil Pollution, 10(1-2): 17-34.
120. Hallett P.D., Nunan N., Douglas J.T., 2004. Millimeter-Scale Spatial Variability in Soil Water Sorptivity: Scale, Surface Elevation and Subcritical Repellency Effects[J]. Soil Science Society of America, 68: 352-358.
121. Han S., Hummel J.W., Goering C.E., et al., 1994. Cell size selection for site-specific crop management[J]. Trans, ASAE, 37: 19-26.
122. Heuvelink G.B.M., Webster R., 2001. Modelling soil variation: Past, Present and future[J]. Geoderma, 100(3-4): 269-301.
123. Itaru Okuda, Masanori Okazaki, Takusei Hashitani, 1995. Spatial and temporal variations in the chemical weathering of Basaltic Pyroclastic materials[J]. Soil. Sci. Soc.Am. J. 59: 887-894.
124. Jiang P., Thelen K. D., 2004. Effect of Soil and Topographic Properties on Crop Yield in a North- Central Corn-Soybean Cropping System[J]. Agron. J. 96: 252-258.
125. Jose E., Francisco M., Sergio C., et al., 2006. GIS-based Site-Specific Management of Cocoa[J]. Better Crops, 90(1): 36-39.
126. Kamgar A., Hopmans J.W., Wallender W.W., et al., 1993. On plot size and sample number of neutron probe measurements in small field trials[J]. Soil Sci, 156: 213-224.
127. Junta Y., Keun L C., Mikio U., et al., 2002. Spatial variability of soil properties and rice yield in paddies: IS Precision agriculture worth practicing?[J]. World Congress of Soil Science(WCSS), 17: 14-21.
128. Khosla R., Fleming K., Delgado J.A., et al., 2002. Use of Site-specific management zones to improve nitrogen management for precision agriculture[J]. Journal of Soil and Water Conservation, 57: 5l3-5l8.
129. Kim D., Keun B., Park S., 2008. Identification and visualization of complex spatial pattern of coastal dune soil properties using gis-based terrain analysis and geostatistics[J]. Journal of Coastal Research, 24(4C): 50-60.
130. Koch B., Khosla R., Frasier W.M., et al., 2004. Economic Feasibility of Variable-Rate Nitrogen Application Utilizing Site-Specific Management Zones[J]. American Society of Agronomy, 98: 1572-1580.
131. Kravchenko A.N., Bullock D.G., 2000. Correlation of corn and soybean grain yield with topography and soil properties[J]. Agron.J, 92: 75-83.
132. Lin H.S, Wheeler D., Bell J., et al 2005. Assessment of soil spatial variability at multiple scales[J]. Ecological Modeling, 182: 271-290.
133. Liu X.M., Xu J.M., Zhang M.K., et al., 2004. Application of geostatistics and GIS technique to characterize spatial variabilities of available micronutrients in paddy soils[J]. Environmental Geology, 46: 189-194.
134. Liu X.M., Zhao K.L., Xu J.M., et al., 2008. Spatial variability of soil organic matter and nutrients in paddy fields at various scales in southeast China[J]. Environmental geology, 53(5): 1139-1147.
135. Lucy O.D., Deborah L., Gregory S.O., 2007. Changes in the spatial variation of soil properties following shifting cultivation in a Mexican tropical dry forest[J]. Biogeochemistry, 84(1): 99-113.
136. Malo D.D., Worcester B.K., 1975. Soil fertility and crop responses at selected landscape positions[J]. Agron.J., 67: 379-401.
137. Miao Y., Mulla D.J., Robert, P.C., 2006. Spatial Variability of Soil Properties, Corn Quality and Yield in Two Illinois, USA Fields: Implications for Precision Corn Management[J]. Precision Agriculture, 7(1): 5-20.
138. Mulla D.J., 1989. Soil spatial variability and methods of analysis. In Retard C.M. et al.(ed). Soil, crop and water management systems of rained agriculture in the Sudan-Sahelian zone[J]. Proc. Int.Workshop. Niamey, Niger. 7-11 Jan.1987. ICRSAT, Patancheru, Andhra Pradesh, India: 241-252.
139. Mulla D.J., 1993. Mapping and managing spatial patterns in soil fertility and crop yield[M]. In: Robert PC, Rust RH and L arson W E, eds. Soil specific crop management. ASA, CSSA, SSSA, Madison, W I: 15-26.
140. Neill R.V., Krummel J.R., Gardner R.H., 1988. Indices of landscape pattern[J]. Landscape Ecology, 1: 153-162.
141. Ovalles F.A., Collins M.E., 1986, Soil-landscape relationships and soil variability in north central Florida[J]. Soil Sci Soc, 50: 401-408.
142. Parkin T.B., 1993. Spatial variability of microbial process in soil-a review[J]. Emviron. Qual. 22: 409-417.
143. Pierce F.J., et al., 1995. Yield and nutrient variability in glacial soils of Michigan [J]. Site-Specific Management for Agricultural Systems[J]. ASA-CSSA-SSSA: 133-152.
144. Ping J.L., Green C.J., Zartman R.E., 2008. Spatial Variability of Soil Properties, Cotton Yield and Quality in a Production Field[J]. Communications in soil science and plant analysis, 39(1-2) : 1-16.
145. Robert P.C., 2002. Precision agriculture: a challenge for crop nutrition management[J]. Plant and Soil, 247: 143-149.
146. Rodrigo A.O., Oscar A.S., 2007. Determination of management zonesin corn (Zea mays L.) based on soil fertility[J]. Computers and Electronics in Agriculture, 58(1): 49-59.
147. Ritters K.H., Neill R.V., Hunsaker C.T., et al., 1995. A factor analysis of landscape and structure metrics[J]. Landscape Ecology, 10: 23-39.
148. Ryan J., Singh M., Yau S.K., 1998. Spatial variability of soluble boron in Syrian soils[J]. Soil & Tillage Research, 45: 407-417.
149. Samake O, Smaling E.M.A, Kropff M.J., et al., 2005. Effects of cultivation practies on spatial variabition of soil fertility and millet yields in the Sahel of Mail[J]. Agriculture,Ecosystems & Environment, 109(3-4): 335-345.
150. Santos D., Murphy S.L.S., Taubner H., 1997. Uniform separation of Concentric surface layers from soil aggregates[J]. Soil Sci.Soc.Am.J. 61: 720-724.
151. Huang S.W., Jin J.Y., Yang L.P., et al., 2006. Spatial variability of soil nutrients and influencing factors in a vegetable production area of Hebei Province in China[J]. Nutr Cycl Agroecosyst, 75: 201-212.
152. Sidorova V.A., Krasilnikov P.V., 2007. Soil-Geographic Interpretation of Spatial Variability in the Chemical and Physical Properties of Topsoil Horizons in the Steppe Zone[J]. Eurasian Soil Science, 40(10): 1042-1051.
153. Sigua G.C., Hudnall W.H., 2008. Kriging analysis of soil properties[J]. Journal of Soils and Sediments, 8(3): 193-202.
154. Solie J.B., Raun W.R., Stone M.L., 1999. Submeter spatial variability of selected soil and bermudagrass production variables[J]. Soil Sci Soc Am J, 63: 1724-1733.
155. Souza L.S., Cogo N.P., Vieira S.R., 1998. Soil spatial variability of phosphorus, potassium andorganic matter, in relation to management systems[J]. Revista Brasileira de Ciencia do Solo, 22(1): 77-86.
156. Stolt M.H., Baker J.C., Simpson T.W, 1993. Soil-landscape relationships in Virginia Soil variability and parent material uniformity[J]. Soil Sci, 57: 414-421.
157. Stafford J.V., 2000. Implementing Precision Agriculture in the 21st Century[J]. Journal of Agricultural Engineering Research, 76(3): 267-275.
158. Stenger R., Priesack E., Beese F., 2002. Spatial variation of nitrate-N and related soil properties at the plot-scale[J]. Geoderma, 105(3-4): 259-275.
159. Sylla M., Steln A., Breemen N., et al., 1995. Spatial variability of soil salinity at different scales in the mangrove rice agro-ecosystem in West Africa[J]. Agriculture Ecosystem & Environment, 54: 1-15.
160. Tatsuya I., Kei G., Michihisa I., et al., 2004. Geostatistical analysis of yield, soil properties and crop management practices in paddy rice fields[J]. Plant Prod. Sci., 7(2): 230-239.
161. Taylor J.C., Wood G.A., Earl R., 2003. Soil factors and their influence on within-field crop variability,Part II: Spatial analysis and determination of management zones. (Special issue: Precision agriculture - managing soil and crop variability for cereals)[J]. Biosystems Engineering, 84(4): 441-453.
162. Tsegaye T., Hill R.L., 1998. Intensive tillage effects on spatial variability of soil test, plant growth, and nutrient uptake measurements[J], Soil Science, 163(2): 155-165.
163. Tening A.S., Omueti J.I., 1995. Potassium status of some selected soils under different land-use systems in the subhumid zone of Nigerial[J]. Commun.Sol.Sci.Plant Anal, 26(5&6): 657-672.
164. Timsina J., Connor D.J., 2001. Productivity and management of rice-wheat cropping systems: issues and challenges[J]. Field Crops Res, 69: 93-132.
165. Trangmar B.B., Yost R.S., Uehara G., 1985. Application of geostatistics to spatial studies of soil properties[J]. Advance in Agronomy, Academic Press, 38: 45-94.
166. Tsegaye T., Hill R.L., 1998. Intensive tillage effects on spatial variability of soil test,plant growth, and nutrient uptake measurements[J]. Soil Science, 163(2): 155-165.
167. Udoyara S.T., Robert J., 1994. Evaluating Agricultural Nonpoint-Source Pollution Using Integrated Geographic Information Systems and Hydrologic/Water Quality Model[J]. J. Environ Qual, 23: 25-35.
168. Wang X.Z., Liu G.S., Hu H.C., 2009. Determination of management zones for a tobacco field based on soil fertility[J]. Computers and Electronics in Agriculture, 65(2): 168-175.
169. Wagenet R.J., 1998. Scale issues in agroecological research chains[J]. Nutrient Cycling in Agroecosystems, 50: 23-34.
170. Webster R., 1985. Quantitative spatial analysis of soil in the field[J]. Advances in Soi1 Seience, 3: 1-70.
171. Webster R., 2000. Is soil variation random?[J]. Geoderma, 97: 149-163.
172. Wei J., Wu G., Deng H.B., et al., 2004. Spatial pattern of soil carbon and nutrient storage at theAlpine tundra ecosystem of Changbai Mountain, China[J]. Journal of Forestry Research, 15(4): 249-254.
173. White J.G., Welch R.M., Novell W.A., 1997. Soil Zn map of the USA using Geostatistics and Geographic information systems[J]. Soil Sci.Soc.Am.J, 61: 185-194.
174. Wild A., 1971. The potassium status of soils in the savanna zone of Nigeria[J]. Expl. Agric., 7: 257-270.
175. Wilcke W., 2000. Small-scale variability of metal concentrations in soil leachates[J]. Soil Sci. Soc. Am. J., 64: 138-143.
176. Wollenhaupt N.C., Wolkowski R.P., Clayton M.K., 1994. Mapping soil test phosphorus and potassium for variable-rate fertilizer application[J]. Prod. Agric, 7: 441-448.
177. Yang C., Anderson G.L., King J.H., et al., 1999. Comparison of uniform and variable rate fertilization strategies using grid soil sampling, variable rate technology, and yield moni-toring: 675-686. In P.C. Robert, R.H. Rust, and W.E. Larson (ed.) Precision agriculture. Proc. Int. Conf., 4th, St. Paul, MN. 19-22 July 1998. ASA, CSSA, and SSSA, Madison, WI.
178. Yanai J., Lee C.K., Umeda M., et al., 2000. Spatial variability of soil chemical properties in a paddy field[J]. Japanese Journal of Soil Science and Plant Nutrition, 71(4): 520-529.
179. Yuan X.Y., Chai X.R., Gao R., et al., 2007. Temporal and spatial variability of soil organic matter in a county scale agricultural ecosystem[J]. New Zealand Journal of Agricultural Research, 50(5): 1157-1168.