基于GIS小尺度下豫中烟田管理分区与推荐施肥研究
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摘要
土壤是农业生产的载体、物质基础和主要环境因素。由于受到各种因素的影响,土壤养分和作物产质量不仅具有明显的空间变异,而且这种变异在时间上也表现出一定的变化。我国农业生产是以家庭为基本单位的小规模生产,这种生产往往忽视土壤养分的空间变异性,而把地块作为均质、统一的单元进行水肥管理,这就致使地块的某些区域施肥不足或过高,不但造成了肥料的浪费,还增加了生态环境的压力,导致生产效率和经济效益的降低。因此,准确的掌握田间土壤养分的空间分布状况,确定合理的土壤养分管理单元,并根据田间试验建立施肥模型,给不同管理单元以推荐施肥量,是实现烟田土壤养分精准管理的基础。
本试验选择平顶山郏县典型烟田为研究对象。利用GPS定位技术,于2009年在平顶山市郏县茨芭乡4 hm~2的烟田进行,以20 m×20 m间距的“网格取样法”取耕层土壤样品111个。综合运用逐步回归分析、地统计方法和GIS技术,分析了土壤养分的空间分布规律,提取了影响烟草品质的关键养分因子,划分了不同肥力水平的管理单元;利用大田试验数据建立推荐施肥模型,给每个分区以推荐施肥量,并通过烟叶品质分析来验证施肥模型,为实现烟田养分差异化管理提供理论基础。初步得到如下研究结果:
(1)研究区域土壤pH值变幅范围为7.39 ~ 8.44,为烤烟生长次适宜区。土壤有机质、总氮、碱解氮和速效磷含量偏低,其平均含量分别为17.19 g kg~(-1)、0.95 g kg~(-1)、74.97 mg kg~(-1)和7.39 mg kg~(-1);土壤速效钾和有效锌的平均含量为161.4 mg kg~(-1)和1.79 mg kg~(-1),基本上属于高含量水平;土壤有效铁、有效铜和有效锰含量为适应范围,其平均含量分别为8.56 mg kg~(-1)、0.93 mg kg~(-1)和7.37 mg kg~(-1);试验区为中等保肥供肥能力的土壤,其阳离子交换量为16.15 cmol kg~(-1);土壤pH、有机质、阳离子交换量、有效铜、砂粒和粉粒的变异系数较小,变幅为3.22% ~ 13.95%,表现出相对稳定性;其余土壤属性的变异系数在17.9% ~ 43.85%之间变化,表现出较大的空间异质性。因此,可以认为在研究区进行分区差异化管理是非常必要的。正态性检验表明,所有土壤数据均为正态分布或近似符合正态分布,均能满足地统计分析要求。
(2)地统计分析表明,土壤砂粒和粘粒的半方差理论模型为指数模型,其余土壤属性均为球状模型。除全氮、有机质和有效锌外,其它土壤属性理论模型的决定系数均大于0.91,且除速效钾外所有属性理论模型的残差均较小,说明所有土壤属性理论模型的拟合度较高,这些模型可用于后续空间插值。研究显示,研究区内土壤总氮、阳离子交换量、有效锌和粉粒的Co/(Co+C)比值的变幅为3.39% ~ 23.43%,均表现出强烈的空间相关性,说明其空间异质性主要是由结构性因素引起的;其余养分的Co/(Co+C)比值在30.87% ~ 50.00%之间变化,均为中等空间相关性,表明随机性因素和结构性因素均对其空间异质性起着作用。该区域土壤属性自相关范围在34.3 m ~ 376.3 m之间,所有土壤属性的空间相关距离均大于取样尺度,因此可以认为本研究的20 m土壤取样间距是合理的。空间插值结果显示,所有土壤属性均具有明显的空间分布格局。
(3)本研究通过删除样点的方法,人为地创造不同的土壤取样间距,然后对不同取样间距下土壤属性进行半方差函数模型拟合和Kriging插值,利用交叉检验方法评价不同取样间距下的空间插值精度,进而确定各土壤属性的最佳取样间距。结果表明,研究区域内的碱解氮、速效磷、速效钾、速效铁和速效锌的合理取样间距为20 m,有机质和速效铜的合理取样间距为60 m,速效锰则以40 m间距进行取样较为合理。
(4)逐步回归分析表明,研究区域土壤速效钾、有机质、速效磷和阳离子交换量对烤烟品质有着显著的影响,是限制该地区烤烟品质的关键养分因子。在农业生产上,要注意这4种养分的合理调控以保证高质量烤烟的生产。同时,这4种关键养分因子可作为分区数据源,利用模糊聚类分析进行管理单元划分。
(5)将这4种关键养分因子运用于MZA软件中进行模糊聚类分析。结果表明,研究区被划分为4个管理单元,各单元内土壤养分和烟叶品质趋于一致,而单元间则表现出较大的差异性,这说明运用此方法对烟田划分不同单元进行精准管理是可行的。
(6)利用曲劳-斯坦福方程进行合理的施肥推荐。通过2007年、2008年、2009年和2010年在平顶山市郏县选择有代表性烟田安排大田试验,以获取推荐施肥模型所需参数,并建立了土壤碱解氮、速效磷和速效钾含量和校正系数间的函数关系。结果表明,土壤养分与其校正系数之间以幂函数曲线相关最佳,各养分的校正系数均随其含量增加而下降。利用初步建立的推荐施肥模型,给出各分区推荐施肥量,为实现烟田养分的分区施肥奠定了基础。
(7)将推荐施肥模型与管理分区相结合,给定每管理分区以推荐施肥量,同时于相应分区内设置对照,每个处理分别取烤后样C3F进行室内分析。结果显示,运用推荐施肥模型来确定施肥量比常规施肥更有利于优质烟叶的形成,烟叶的各类致香物质物质和总致香物质含量均较高,并且推荐施肥量较常规施肥量少,降低了农业成本,为烟田土壤养分分区管理和推荐施肥提供了理论依据。
Soil is the important carrier, material basis and main environmental of agricultural production. Because of various factors, soil nutrients and crop yield have spatial within-field variability, changing with the time. Agricultural production is based on the family as the basic unit of small-scale production in China. It often regards soil as symmetrical, uniform integer to deal with and ignores the variation of soil nutrient inside soil, so caused fertilizer insufficiently in some areas or fertilizer amply in the others field. This is not only casued the waste of the fertilizer but also constituted a threat to ecological environment, therefore the production efficiency and economic benefits are low. Therefore, it is the basic for the accurate nutrient management of tobacco field which the management zones (MZs) were determined based on accurately understood the spatial distribution of soil nutrients; the fertilization models were established based on field experiment, and the amount of recommended fertilizer was given for each MZs.
In this study, the distinguishing tobacco plantation field of PingDingShan was selected for exploring the site-specific nutrient management. Soil samples were collected in March 2009. The samples were taken from the topsoil (0 ~ 20 cm) on an approximate 20 m grid sampling design (n = 111). A real-time kinematic global positioning system (GPS) survey was used to identify sampling locations. The spatial variability of soil nutrients in a tobacco-planted field was studied and spatial distribution maps of soil nutrients was generated by geostatistics and geographic information system (GIS), the key quality-limiting factors for tobacco in the study area was determine by stepwise multiple regression analysis, the MZs were delineated by fuzzy clustering algorithm. The fertilization models were established by the data from field experiment and the amount of recommended fertilizer was given for each MZs. Simultaneity, the fertilization models were evaluated by the quality of tobacco. This study provides a basis of information for site-spcific fertilizer management in tobacco-planted field. The primary conclusions were as follows:
(1) The soils are weakly alkaline with pH levels ranging from 7.39 to 8.44. These pH conditions are not conducive to the production of high-quality tobacco growth. The content of soil OM, TN, AN and AP have low levels, and their mean were 17.19 g kg~(-1), 0.95 g kg~(-1), 74.97 mg kg~(-1), and 7.39 mg kg~(-1), respectively. The high content of AK and Zn were 161.4 mg kg~(-1) and 1.79 mg kg~(-1), respectively. Soil Fe, Cu, and Mn have medium content with mean of 8.56 mg kg~(-1), 0.93 mg kg~(-1), and 7.37 mg kg~(-1). The soil nutrient holding and delivery capacity was medium according to the CEC content (cmol kg~(-1)). Coefficients of variation ranged from approximately 3.22% for pH to almost 43.85% for available AP. Soil pH, OM, CEC, Cu, Sand, and Silt had low CV (3.22% ~ 13.95%), suggesting the relative stability. All other soil properties exhibited a medium variation (CV, 17.9% ~ 43.85%), indicating the heterogeneity of soil properties. Thus, differentiated management may be necessary to achieve maximum economic and environmental benefits. The Kolmogorov-Smirnov test revealed that all variables were normally distributed (P > 0.05) and did not require transformation.
(2) The results of geostatisitical analyses are shown that the sand and clay ideally matched an exponential model, whereas the rest of the soil properties best fit the spherical model. The coefficients of determination (R2) of all the soil nutrients, expect for TN, OM, and Zn, were greater than 0.91, indicating a good fit. The value nugget-sill ratio is used to qualitatively define spatial dependence values. The nugget-sill ratios for TN, Zn, CEC, and silt were 3.39%, 13.61%, 17.01%, and 23.43%, respectively, suggesting strongly spatial dependence. Meanwhile, all other soil variables were moderately spatially dependent, with the nugget-sill ratios ranging from 30.48% to 49.99%. The range, expressed as distance, can be interpreted as the zone of in?uence diameter. This represents the average maximum distance over which the soil properties of the two samples are related. The range of Zn and silt were 34.3 m and 35.3 m, respectively, much smaller than the other nutrient. The smaller range suggests that smaller sampling intervals are needed for Zn and silt. The distributionmaps of all variables are shown that all soil properties have obvious spatial pattern.
(3) In this study, the different sampling intervals were obtained artificially by deleting soil-sampling points from the actual sample figure, and the best models were modeled in different sampling intervals. The best models were used to obtain the content contour maps of soil properties in different sampling intervals. To evaluate the accuracy of the estimates, the performance of each interpolation under different intervals was assessed by comparing the deviation of estimates from the measured data through cross-validation. In this region, the interpolation errors of soil organic matter and available copper were lowest in the 60-m sampling interval. In the 20-m sampling interval, alkaline hydrolyzable N, available phosphorus, available potassium, available iron, and available zinc had the least errors of interpolation. Available manganese had the least interpolation error at the 40-m sampling interval. Overall, the sampling efficiency could be further improved. The method can be applied in a practical and cost-effective manner to facilitate soil sampling.
(4) Through stepwise multiple regression analysis of the relationship between tobacco and soil nutrients showed that soil AK, OM, AP, and CEC were the key quality-limiting factors for tobacco in this area. To attain high-quality flue-cured tobacco, the four soil properties should be reasonably regulated. The four soil properties were aggregated into management zone (MZ) using a clustering algorithm.
(5) The classification of data on the four soil properties for the delineation of the MZ can be carried out to effectively characterize the spatial variation of the soil nutrients and manage fertilizer application in the tobacco fields. The data on the four soil variables were imported into the MZA software through which clustering analysis was performed. Results of clustering analysis clearly indicated that grouping the data into four classes allowed both FPI and NCE indexes to be minimized. Clustering the four soil properties resulted in an optimum number of four cluster classes. Analysis of variance and CV indicated the heterogeneity of the soil properties and flue-cured tobacco quality among the four MZs. This study may provide a method for variable-rate fertilization management in tobacco-planted fields, and the application of MZ should improve the quality of ?ue-cured tobacco.
(6) The rational fertilization models were building with Truog-Stanford equation. The models for nitrogen, phosphorus and potassium fertilizers recommendation were established based on four years field experiments. The result shown that the best relationship between soil nutrients and correction factors were power function. When the content of soil nutrients increased, their correction factor decreased. Using the three-fertilization model, the fertilizer application for four management zones were recommended, respectively. This study may provide a method for variable-rate fertilization management in tobacco-planted fields, and the application of MZ should improve the quality of ?ue-cured tobacco.
(7) The fertilization recommendation for each MZs were generated by fertilization models and management zones, and using the quality of tobacco evaluate the effect of fertilization recommendation. The results indicated that the quality of tobacco in fertilization recommendation zone was better than the conventional fertilization with the chemical components and content of aroma constituent in flue-cured tobacco leaves. Recommended fertilizer reduced the amount of fertilizer application and the cost of agriculture. Based on the study, we conclude that tobacco-planted fields can be managed in a site-specific manner by these methods.
本试验选择平顶山郏县典型烟田为研究对象。利用GPS定位技术,于2009年在平顶山市郏县茨芭乡4 hm~2的烟田进行,以20 m×20 m间距的“网格取样法”取耕层土壤样品111个。综合运用逐步回归分析、地统计方法和GIS技术,分析了土壤养分的空间分布规律,提取了影响烟草品质的关键养分因子,划分了不同肥力水平的管理单元;利用大田试验数据建立推荐施肥模型,给每个分区以推荐施肥量,并通过烟叶品质分析来验证施肥模型,为实现烟田养分差异化管理提供理论基础。初步得到如下研究结果:
(1)研究区域土壤pH值变幅范围为7.39 ~ 8.44,为烤烟生长次适宜区。土壤有机质、总氮、碱解氮和速效磷含量偏低,其平均含量分别为17.19 g kg~(-1)、0.95 g kg~(-1)、74.97 mg kg~(-1)和7.39 mg kg~(-1);土壤速效钾和有效锌的平均含量为161.4 mg kg~(-1)和1.79 mg kg~(-1),基本上属于高含量水平;土壤有效铁、有效铜和有效锰含量为适应范围,其平均含量分别为8.56 mg kg~(-1)、0.93 mg kg~(-1)和7.37 mg kg~(-1);试验区为中等保肥供肥能力的土壤,其阳离子交换量为16.15 cmol kg~(-1);土壤pH、有机质、阳离子交换量、有效铜、砂粒和粉粒的变异系数较小,变幅为3.22% ~ 13.95%,表现出相对稳定性;其余土壤属性的变异系数在17.9% ~ 43.85%之间变化,表现出较大的空间异质性。因此,可以认为在研究区进行分区差异化管理是非常必要的。正态性检验表明,所有土壤数据均为正态分布或近似符合正态分布,均能满足地统计分析要求。
(2)地统计分析表明,土壤砂粒和粘粒的半方差理论模型为指数模型,其余土壤属性均为球状模型。除全氮、有机质和有效锌外,其它土壤属性理论模型的决定系数均大于0.91,且除速效钾外所有属性理论模型的残差均较小,说明所有土壤属性理论模型的拟合度较高,这些模型可用于后续空间插值。研究显示,研究区内土壤总氮、阳离子交换量、有效锌和粉粒的Co/(Co+C)比值的变幅为3.39% ~ 23.43%,均表现出强烈的空间相关性,说明其空间异质性主要是由结构性因素引起的;其余养分的Co/(Co+C)比值在30.87% ~ 50.00%之间变化,均为中等空间相关性,表明随机性因素和结构性因素均对其空间异质性起着作用。该区域土壤属性自相关范围在34.3 m ~ 376.3 m之间,所有土壤属性的空间相关距离均大于取样尺度,因此可以认为本研究的20 m土壤取样间距是合理的。空间插值结果显示,所有土壤属性均具有明显的空间分布格局。
(3)本研究通过删除样点的方法,人为地创造不同的土壤取样间距,然后对不同取样间距下土壤属性进行半方差函数模型拟合和Kriging插值,利用交叉检验方法评价不同取样间距下的空间插值精度,进而确定各土壤属性的最佳取样间距。结果表明,研究区域内的碱解氮、速效磷、速效钾、速效铁和速效锌的合理取样间距为20 m,有机质和速效铜的合理取样间距为60 m,速效锰则以40 m间距进行取样较为合理。
(4)逐步回归分析表明,研究区域土壤速效钾、有机质、速效磷和阳离子交换量对烤烟品质有着显著的影响,是限制该地区烤烟品质的关键养分因子。在农业生产上,要注意这4种养分的合理调控以保证高质量烤烟的生产。同时,这4种关键养分因子可作为分区数据源,利用模糊聚类分析进行管理单元划分。
(5)将这4种关键养分因子运用于MZA软件中进行模糊聚类分析。结果表明,研究区被划分为4个管理单元,各单元内土壤养分和烟叶品质趋于一致,而单元间则表现出较大的差异性,这说明运用此方法对烟田划分不同单元进行精准管理是可行的。
(6)利用曲劳-斯坦福方程进行合理的施肥推荐。通过2007年、2008年、2009年和2010年在平顶山市郏县选择有代表性烟田安排大田试验,以获取推荐施肥模型所需参数,并建立了土壤碱解氮、速效磷和速效钾含量和校正系数间的函数关系。结果表明,土壤养分与其校正系数之间以幂函数曲线相关最佳,各养分的校正系数均随其含量增加而下降。利用初步建立的推荐施肥模型,给出各分区推荐施肥量,为实现烟田养分的分区施肥奠定了基础。
(7)将推荐施肥模型与管理分区相结合,给定每管理分区以推荐施肥量,同时于相应分区内设置对照,每个处理分别取烤后样C3F进行室内分析。结果显示,运用推荐施肥模型来确定施肥量比常规施肥更有利于优质烟叶的形成,烟叶的各类致香物质物质和总致香物质含量均较高,并且推荐施肥量较常规施肥量少,降低了农业成本,为烟田土壤养分分区管理和推荐施肥提供了理论依据。
Soil is the important carrier, material basis and main environmental of agricultural production. Because of various factors, soil nutrients and crop yield have spatial within-field variability, changing with the time. Agricultural production is based on the family as the basic unit of small-scale production in China. It often regards soil as symmetrical, uniform integer to deal with and ignores the variation of soil nutrient inside soil, so caused fertilizer insufficiently in some areas or fertilizer amply in the others field. This is not only casued the waste of the fertilizer but also constituted a threat to ecological environment, therefore the production efficiency and economic benefits are low. Therefore, it is the basic for the accurate nutrient management of tobacco field which the management zones (MZs) were determined based on accurately understood the spatial distribution of soil nutrients; the fertilization models were established based on field experiment, and the amount of recommended fertilizer was given for each MZs.
In this study, the distinguishing tobacco plantation field of PingDingShan was selected for exploring the site-specific nutrient management. Soil samples were collected in March 2009. The samples were taken from the topsoil (0 ~ 20 cm) on an approximate 20 m grid sampling design (n = 111). A real-time kinematic global positioning system (GPS) survey was used to identify sampling locations. The spatial variability of soil nutrients in a tobacco-planted field was studied and spatial distribution maps of soil nutrients was generated by geostatistics and geographic information system (GIS), the key quality-limiting factors for tobacco in the study area was determine by stepwise multiple regression analysis, the MZs were delineated by fuzzy clustering algorithm. The fertilization models were established by the data from field experiment and the amount of recommended fertilizer was given for each MZs. Simultaneity, the fertilization models were evaluated by the quality of tobacco. This study provides a basis of information for site-spcific fertilizer management in tobacco-planted field. The primary conclusions were as follows:
(1) The soils are weakly alkaline with pH levels ranging from 7.39 to 8.44. These pH conditions are not conducive to the production of high-quality tobacco growth. The content of soil OM, TN, AN and AP have low levels, and their mean were 17.19 g kg~(-1), 0.95 g kg~(-1), 74.97 mg kg~(-1), and 7.39 mg kg~(-1), respectively. The high content of AK and Zn were 161.4 mg kg~(-1) and 1.79 mg kg~(-1), respectively. Soil Fe, Cu, and Mn have medium content with mean of 8.56 mg kg~(-1), 0.93 mg kg~(-1), and 7.37 mg kg~(-1). The soil nutrient holding and delivery capacity was medium according to the CEC content (cmol kg~(-1)). Coefficients of variation ranged from approximately 3.22% for pH to almost 43.85% for available AP. Soil pH, OM, CEC, Cu, Sand, and Silt had low CV (3.22% ~ 13.95%), suggesting the relative stability. All other soil properties exhibited a medium variation (CV, 17.9% ~ 43.85%), indicating the heterogeneity of soil properties. Thus, differentiated management may be necessary to achieve maximum economic and environmental benefits. The Kolmogorov-Smirnov test revealed that all variables were normally distributed (P > 0.05) and did not require transformation.
(2) The results of geostatisitical analyses are shown that the sand and clay ideally matched an exponential model, whereas the rest of the soil properties best fit the spherical model. The coefficients of determination (R2) of all the soil nutrients, expect for TN, OM, and Zn, were greater than 0.91, indicating a good fit. The value nugget-sill ratio is used to qualitatively define spatial dependence values. The nugget-sill ratios for TN, Zn, CEC, and silt were 3.39%, 13.61%, 17.01%, and 23.43%, respectively, suggesting strongly spatial dependence. Meanwhile, all other soil variables were moderately spatially dependent, with the nugget-sill ratios ranging from 30.48% to 49.99%. The range, expressed as distance, can be interpreted as the zone of in?uence diameter. This represents the average maximum distance over which the soil properties of the two samples are related. The range of Zn and silt were 34.3 m and 35.3 m, respectively, much smaller than the other nutrient. The smaller range suggests that smaller sampling intervals are needed for Zn and silt. The distributionmaps of all variables are shown that all soil properties have obvious spatial pattern.
(3) In this study, the different sampling intervals were obtained artificially by deleting soil-sampling points from the actual sample figure, and the best models were modeled in different sampling intervals. The best models were used to obtain the content contour maps of soil properties in different sampling intervals. To evaluate the accuracy of the estimates, the performance of each interpolation under different intervals was assessed by comparing the deviation of estimates from the measured data through cross-validation. In this region, the interpolation errors of soil organic matter and available copper were lowest in the 60-m sampling interval. In the 20-m sampling interval, alkaline hydrolyzable N, available phosphorus, available potassium, available iron, and available zinc had the least errors of interpolation. Available manganese had the least interpolation error at the 40-m sampling interval. Overall, the sampling efficiency could be further improved. The method can be applied in a practical and cost-effective manner to facilitate soil sampling.
(4) Through stepwise multiple regression analysis of the relationship between tobacco and soil nutrients showed that soil AK, OM, AP, and CEC were the key quality-limiting factors for tobacco in this area. To attain high-quality flue-cured tobacco, the four soil properties should be reasonably regulated. The four soil properties were aggregated into management zone (MZ) using a clustering algorithm.
(5) The classification of data on the four soil properties for the delineation of the MZ can be carried out to effectively characterize the spatial variation of the soil nutrients and manage fertilizer application in the tobacco fields. The data on the four soil variables were imported into the MZA software through which clustering analysis was performed. Results of clustering analysis clearly indicated that grouping the data into four classes allowed both FPI and NCE indexes to be minimized. Clustering the four soil properties resulted in an optimum number of four cluster classes. Analysis of variance and CV indicated the heterogeneity of the soil properties and flue-cured tobacco quality among the four MZs. This study may provide a method for variable-rate fertilization management in tobacco-planted fields, and the application of MZ should improve the quality of ?ue-cured tobacco.
(6) The rational fertilization models were building with Truog-Stanford equation. The models for nitrogen, phosphorus and potassium fertilizers recommendation were established based on four years field experiments. The result shown that the best relationship between soil nutrients and correction factors were power function. When the content of soil nutrients increased, their correction factor decreased. Using the three-fertilization model, the fertilizer application for four management zones were recommended, respectively. This study may provide a method for variable-rate fertilization management in tobacco-planted fields, and the application of MZ should improve the quality of ?ue-cured tobacco.
(7) The fertilization recommendation for each MZs were generated by fertilization models and management zones, and using the quality of tobacco evaluate the effect of fertilization recommendation. The results indicated that the quality of tobacco in fertilization recommendation zone was better than the conventional fertilization with the chemical components and content of aroma constituent in flue-cured tobacco leaves. Recommended fertilizer reduced the amount of fertilizer application and the cost of agriculture. Based on the study, we conclude that tobacco-planted fields can be managed in a site-specific manner by these methods.
引文
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