基于烤烟品质确定烟田的养分管理分区

探明影响烤烟品质的关键土壤养分因子,为划分不同管理分区进行精准管理提供科学依据。在平顶山地区以20 m间隔的网格法取耕层（020 cm）土样111个,测定了8种土壤养分含量;进行逐步回归分析和模糊聚类分析。结果表明,研究区内有机质、总氮、碱解氮和速效磷含量偏低,速效钾含量偏高,且各种养分的差异性均较大;所有养分均可用球状模型进行较好拟合。逐步回归显示,土壤有机质、速效磷、速效钾和阳离子交换量对烟叶品质有较大的影响;应用模糊聚类分析将研究区域划分为4个管理区,验证表明分区结果是可行的。说明土壤有机质、速效钾、速效磷和阳离子交换量是制约烟叶品质的关键土壤养分因子;利用这4种因子可以科学合理地将研究区域划分为4个分区进行烟田养分的精准管理。     

小尺度下滴灌棉田养分管理分区研究

以小尺度下滴灌棉田为研究对象,采集研究区87个耕层土壤(0～30 cm)样品,土壤有机质、全氮、速效磷和总盐含量为变量进行土壤养分精确管理分区研究。结果表明,运用模糊c-均值聚类法进行分区,并采用c-φ多次组合法来确定适宜的模糊控制参数,得出研究区最佳分区数为4,模糊指数为1.7,平均混乱度指数为0.29,土壤属性数据的模糊分类输出结果不确定性较小,地理空间上土壤的隶属关系相对明确。在研究区内,模糊分类的输出结果符合管理分区的定义,各管理分区均可以作为变量施肥的单独作业单元进行耕作管理。     

云南玉溪植烟土壤速效养分空间变异特征及应用

为探讨烟田土壤养分空间变异特征及利用空间变异进行分区管理的技术路线,以全国烤烟种植典型产区云南省玉溪市烟田土壤为例,形成土壤养分空间变异分析—空间分布—肥料养分推荐—分区配方的技术思路。基于烟区土壤养分数据,应用地理信息系统(GIS),采用地统计学方法研究烟区耕作层(0~20 cm)土壤碱解氮、有效磷和速效钾的变异特征和空间分布。以乡镇作为管理单元,依据烟田土壤肥力评价及养分管理指标体系,计算出乡镇烤烟养分管理的氮、磷、钾肥料推荐量。采用聚类分析方法,结合烤烟养分管理"核心是氮、品质元素是钾"的特点,提出玉溪烤烟养分管理5个管理分区、5个基肥配方、2个追肥配方。研究表明:玉溪烟田土壤速效养分为中等强度空间变异,拟合模型为指数模型,变异来源于结构性因素和施肥等人为因素;土壤有效磷的变异最大,高于速效钾和碱解氮,与氮肥和钾肥用量相对稳定,而磷肥相对随机等农艺措施相关;超过67%的土壤碱解氮、有效磷和速效钾含量处于高和极高水平,肥料氮、磷、钾推荐量低于云南省烤烟养分管理平均水平11%左右;提出5个烤烟养分管理分区及相应的基肥和追肥配方,以满足"大配方、小调整"原则,实现分类指导和分区管理。     

滨海废弃盐田复垦区土壤空间变异及其分区管理研究

  目的  针对山东省莱州湾南岸废弃盐田复垦区盐分高、土壤养分空间差异性大、管理粗放和效益低等问题,研究田间管理分区的精准划分方法,便于农户差异化施肥管理,提高盐渍土改良水平。  方法  以废弃盐田复垦区典型地块为研究对象,运用传统统计学、主成分分析和模糊c-均值分类等方法对研究区进行管理分区的划分,并评价管理分区划分的适宜性和有效性。  结果  研究区土壤含盐量均值达到1.73 g kg?1,处于轻度盐渍化水平;土壤有机质、全氮、速效氮、速效钾和速效磷等含量均处于较低的水平;全磷和阳离子交换量处于中等水平;全钾和pH值达到了较高的水平。全钾和pH值的变异系数 < 0.1,属于弱变异,其他土壤属性属于中等变异强度。土壤各属性在空间分布上差异性大。主成分分析结果表明,将10个土壤属性分组为统计因子可划分成3个主成分。模糊c-均值分类结果表明,研究区可划分为2个管理分区,不同管理分区中土壤含盐量、有机质、土壤养分等属性存在显著差异。  结论  可以利用不同土壤属性借助模糊c-均值分类方法来确定废弃盐田复垦区农田的管理分区。     

云南省典型县域烟田土壤肥力演变及综合评价

对云南省典型县域宾川县烟田土壤pH和养分含量40年的变化进行定量分析，明确烟田土壤肥力演变特征，进一步为烟区土壤养分管理及平衡施肥提供科学依据。通过数据收集和野外采样，分析宾川县1982、2012、2018、2022年4个时期烟田耕层土壤养分变化，运用土壤综合评价法，克里格插值定量评价了土壤综合肥力指数（IFI）及其时空变异特征。近40年来（1982—2022），宾川县烟田土壤pH（7.13~6.23）和有机质含量（35.30~27.71 g/kg）呈下降趋势，有效磷（12.11~50.71 mg/kg）和速效钾含量（158.66~321.03 mg/kg）呈上升趋势，碱解氮含量（119.03~117.00 mg/kg）无显著变化。IFI（0.49~0.62）呈上升趋势，均值由1982年的0.49（Ⅲ）增加至2022年的0.62（Ⅱ），其中平川镇、拉乌彝族乡、州城镇及宾居镇IFI增加幅度最大，当前高肥力区域主要分布于县东北部和南部，低肥力区域分布于西北部。此外，主成分分析表明影响烟田土壤肥力的主要内在因素由有机质变为速效钾。经过40年耕种管理，宾川县烟田肥力自西向东、自北向南逐渐增加，但养分指标非均衡性和肥力空间不均匀性增加，应稳定氮肥钾肥，减少磷肥施用。     

重庆市植烟土壤质量评价指标体系的构建与应用

为准确评价重庆烟田土壤质量特征。以重庆市烟区2513个代表性植烟土壤的理化指标为基础数据,采用聚类分析和主成分分析法建立重庆烟田土壤质量最小数据集,构建重庆市植烟土壤质量评价指标体系。(1)基于主成分分析法建立的土壤质量评价体系更适合对重庆烟区土壤质量进行评价,评价指标从原来16个指标减少为7个指标,具体由土壤pH、有机质、有效磷、有效铁、有效锌、有效硫和水稳性大团聚体组成。(2)重庆烟区土壤酸化程度较为严重,有35.1%的植烟土壤偏酸;土壤氮素较为适宜,而速效磷和速效钾处于过量范围占比分别为62.9%和75.8%,其他元素缺乏和过量并存,水稳性大团聚体处于较低范围占47.2%。(3)重庆植烟土壤质量综合指数(SQI)的半方差函数最优拟合模型为指数模型,交叉验证结果表明模型和参数合理;基于最小数据集计算得到土壤质量指数SQI的平均值为0.61,表明重庆烟区土壤质量总体处于中等偏低水平,重庆烟区有45.04%的烟田急需要改良。(4)土壤质量评价指标隶属度值雷达图得出,土壤pH、速效磷、有效铁、有效硫和水稳性大团聚体隶属度比较小,为重庆烟区的土壤限制性因子。该研究建立了重庆市植烟土壤质量评价指标体系,研究结果可为重庆烟区土壤质量提升、土壤生态系统恢复和烟叶可持续生产提供支撑。     

喀斯特山地植烟土壤养分空间变异及分区研究

为揭示喀斯特山地植烟土壤养分空间变异特征并进行分区管理,利用地统计学和模糊C-均值聚类算法对贵州省黔南州喀斯特山地植烟土壤养分进行分析。结果表明,土壤总体呈弱酸性,极小部分土壤缺乏有机质、碱解氮、有效磷、有效铜和有效锌,小部分土壤缺乏速效钾、交换性钙和交换性镁,大部分土壤缺乏有效钼。p H、有机质、碱解氮、有效磷、速效钾、交换性镁、有效铜、有效锌和有效钼空间相关性中等,交换性钙空间相关性弱。p H、有机质、碱解氮、有效磷、速效钾、交换性钙、交换性镁和有效锌空间变异主要由随机因素引起,有效铜和有效钼的空间变异主要由结构性因素引起。土壤养分空间变异趋势效应明显,p H、有效磷、速效钾、交换性钙、交换性镁、有效铜、有效锌和有效钼均由几个高值中心向四周递减分布;有机质和碱解氮均由北部、西部和南部向中部和东部递增分布。研究区植烟土壤可分为4个管理分区,分区内土壤养分趋于同质化,分区间差异显著。本研究为喀斯特山地农田土壤养分管理、农作物平衡施肥和肥料高效利用提供了参考依据。     

河南南阳烟区土壤生态指标的主成分分析

采用主成分分析法对南阳烟区13个不同生态类型土壤的物理、化学及生物学性状指标进行分析,结果表明,南阳烟区土壤化学生态指标中第一主成分为有机质的综合指标;第二主成分为pH。南阳烟区土壤物理生态指标中第一主成分为容重、孔隙度;第二主成分为土粒密度。南阳烟区土壤生物学生态指标中第一主成分为脲酶活性、过氧化氢酶活性的综合指标;第二主成分为纤维菌数、放线菌数、氨化菌数的综合指标。南阳烟区土壤物理和化学生态指标中第一主成分为容重、孔隙度;第二主成分为土粒密度。南阳烟区土壤物理、化学和生物生态指标中第一主成分为有机质的综合指标;第二主成分为脲酶活性、过氧化氢酶活性、真菌数等生物学的综合指标;第三主成分为pH、土粒密度、容重等理化综合指标;第四主成分蛋白酶活性和放线菌数的生物学综合指标。为抓住主要矛盾从不同层次研究和改良南阳烟区土壤生态条件提供理论依据。     

喀斯特地区烟田土壤养分的空间变异特征

以我国典型的喀斯特地区—贵州省毕节地区为研究区域,利用地统计学和地理信息系统(GIS)相结合的方法对烟田土壤养分的空间变异特征进行研究,皆在为喀斯特地区烟草种植的平衡施肥及生态环境保护提供依据。描述性统计结果表明,研究区烟田土壤各养分指标均属中等程度变异。半方差函数分析表明,研究区烟田土壤全氮、全钾、速效磷变异函数的最适模型是球状模型,全磷和速效钾的最适模型是线性模型,碱解氮、pH和有机质的最适模型为指数模型;速效磷表现为强烈的空间自相关性,主要受结构性因素影响,而全氮、全磷、全钾、碱解氮、速效钾、pH和有机质表现为中等空间相关性,受结构性因素和随机性因素共同影响。普通克里格插值的土壤养分空间分布图表明,研究区域内烟田土壤全氮、全钾、速效磷和速效钾含量分布呈现空间连续分布的特点,而全磷、碱解氮和pH、有机质含量没有明显的分布规律,这主要与喀斯特地区复杂的立地因子和人为影响有关。     

基于水稻冠层光谱信息的稻田土壤速效N的Cokriging插值研究

该文以嘉善县陶庄农场内一块3.34 hm²农田为试验区，研究样点土壤养分(土壤全N、全P、有机质、速效N、速效K)与水稻各生长期水稻冠层光谱的关系，并将光谱指数作为协因子，进行土壤养分的Cokriging插值研究。结果表明，正常施肥区各生长期根据TM、SPOT波段组合计算的某些冠层光谱指数，特别是比值光谱指数RSI、归一化光谱指数NDSI，与土壤速效N、有机质等土壤养分具有显著的相关性，可以作为协因子参与这些土壤养分的估算；选择正常施肥区分蘖期TM、SPOT组合中与速效N相关性最高的比值光谱指数TM4/TM3、B3/B2作为协因子，参与土壤速效N的Cokriging插值，与普通Kriging相比，插值精度有一定程度的提高，并且，当采样点越少，或土壤养分与协因子的相关性越高时，插值精度提高更明显。     

Assessing soil spatial variability and delineating site-specific management zones for a coastal saline land in eastern India

ABSTRACT

The present study was to delineate management zones (MZs) in salt affected Mahakalpada block in eastern India by capturing both spatial variability of soil parameters along with satellite derived Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI). Grid wise 237 soil samples collected from the study area were analyzed and spatial maps were generated for physicochemical properties, DTPA extractable micronutrients, i.e. iron, zinc, copper, and manganese and major nutrients, i.e. available nitrogen (AN), phosphorous (AP), and potassium (AK). Soil electrical conductivity and AK showed a high CV of 100% and 56.7%, respectively. Principal component analysis was performed using the soil spatial maps, NDVI and EVI maps and only four principal components which produced eigenvalues > 1 and accounting for 75.4% of the total variability were retained for further analysis. Further, fuzzy c-mean clustering was used to delineate the MZs based on fuzzy performance index (FPI) and normalized classification entropy (NCE) was used for identifying the three MZs. There was a significant difference between MZ1 and MZ2 for all the variables except AN and EVI whereas all the variables were significantly different between MZ1 and MZ3 highlighting the usefulness of MZs delineation technique for site-specific nutrient management.     

Precision Manure Management on Site-Specific Management Zones: Topsoil Quality and Environmental Impact

Maintenance and improvement of soil quality across spatially variable soils in continuous cropping systems are critical to sustaining agricultural productivity and environmental quality. The objectives of this project were (i) to study the effects of variable-rate application of animal manure on selected topsoil quality parameters across site-specific management zones (MZs) and (ii) to evaluate the variable-rate applications of manure using risk-assessment tools of nitrogen (N) leaching and phosphorus (P) runoff indices to understand its impact on environmental quality. This study was conducted in northeastern Colorado on continuous and furrow-irrigated maize fields. Experimental strips, 4.5 m wide and 540 m long, spanned across all MZs with treatments nested within MZs in the field. Variable rates of dairy and beef feedlot manure applied on irrigated and dryland fields respectively ranged from 0 to 67 Mg ha^?1. Surface soil quality parameters evaluated before and after this study included bulk density, organic matter, water-holding capacity, electrical conductivity, and particle-size analysis. Results indicate that animal manure applications of 44 and 67 Mg ha^?1 significantly (P ≤ 0.05) increased soil organic matter and decreased bulk density of low- and medium-productivity-level MZs and had no significant impact on surface soil organic matter and bulk density of the high-productivity-level MZs. Animal manure significantly (P ≤ 0.05) increased surface soil water-holding capacity and soil electrical conductivity across zones; however, the maximum manure-induced soil EC was 1.0 dS m^?1, which was below levels regarded as potentially harmful for maize production. Soil texture was not affected by animal manure applications. Colorado N leaching and P index indicated no environmental hazard associated with variable rate application of animal manure across MZs. This study indicates that variable-rate application of animal manure across MZs has potential to improve or maintain soil quality parameters over time without impairing the environment.     

Spatial Distribution and Management Zones for Sulphur and Micronutrients in Shiwalik Himalayan Region of India

Agricultural land degradation due to nutrient deficiencies is a threat to agricultural sustainability. As nutrients availability is influenced by soil heterogeneity, climatic conditions and anthropogenic activities; hence, delineation of nutrient management zones (MZs) based on spatial variability could be an effective management option at regional scale. Thus, the present study was carried out to delineate MZs in the Shiwalik Himalayan region of India by capturing spatial variability of soil properties and secondary and micronutrients status because of the emerging nutrient deficiencies. For the study, a total of 2575 geo‐referenced representative surface (0–15 cm depth) soil samples were collected from the study region covering an area of 53,483 km². The soils were analysed for pH, electrical conductivity, soil organic carbon, available sulphur (S) and micronutrients (Zn, Fe, Cu, Mn, B and Mo) concentrations. There was a wide variation in soil properties with coefficient of variation values of 14 (for pH) to 86% for available Mo. Geostatistical analysis revealed spherical, Gaussian, exponential, stable, circular and K‐Bessel best‐fit models for soil properties. Most of the soil properties were having moderate spatial dependence except soil pH and S (strong spatial dependence) and Zn (weak spatial dependence). About 49%, 10%, 2%, 13%, 11%, 12% and 8% area of the study region were found to be deficient (including acute and marginal deficiency) in S, Zn, Fe, Cu, Mn, B and Mo, respectively. The principal component analysis and fuzzy c‐mean clustering were performed to develop the MZs. Four principal components with eigenvalues greater than 1 and accounting 65·4% of total variance were retained for further analysis. On the basis of fuzzy performance index and normalized classification entropy, four potential MZs were identified. Analysis of variance confirmed the heterogeneity in most of the studied soil properties among the MZs. The study indicated that the methodology of delineating MZs can be effectively used in site‐specific S and micronutrients management in the Shiwalik Himalayan region of India. Copyright © 2016 John Wiley & Sons, Ltd.     

基于多源环境变量的橡胶园土壤管理分区

为了提高大尺度范围内橡胶园土壤管理的针对性,以海南省国营八一农场橡胶园为研究对象,以地形因子(海拔、坡度和坡向)、成土母质、气候变量(平均降雨量和平均气温)和植被指数为数据源,对橡胶园进行土壤管理分区。利用模糊C均值聚类法进行分区,以模糊性能指数(fuzzy performance index,FPI)和归一化分类熵(normalized classification entropy,NCE)作为判断最佳分区数的标准,并通过单因素方差分析和分区前后土壤属性以及环境变量变异系数对比对分区结果进行评价和验证。研究结果表明,橡胶园管理分区的最佳数目为3个。不同管理分区之间土壤属性(pH值、有机质、全氮、有效磷、速效钾、有效硫、交换性钙、交换性镁、有效铜、有效铁和有效锰)和环境变量(高程、坡度、降雨量、平均温和归一化植被指数)的差异性都达到了极显著水平(P0.01),同时,3个分区中土壤属性和环境变量变异系数的均值比分区前明显下降。这就验证了在大尺度范围内,利用较易获取的多源环境变量进行橡胶园土壤管理分区是可行的,同时依据不同分区的特点制定了相应的土壤管理措施,提高了大范围区域内橡胶园土壤管理的针对性。     

An application of PCA and fuzzy C-means to delineate management zones and variability analysis of soil

Within-field variability is a well-known phenomenon and its study is at the centre of precision agriculture (PA). In this paper, site-specific spatial variability (SSSV) of apparent Electrical Conductivity (EC_a) and crop yield apart from pH, moisture, temperature and di-electric constant information was analyzed to construct spatial distribution maps. Principal component analysis (PCA) and fuzzy c-means (FCM) clustering algorithm were then performed to delineate management zones (MZs). Various performance indices such as Normalized Classification Entropy (NCE) and Fuzzy Performance Index (FPI) were calculated to determine the clustering performance. The geo-referenced sensor data was analyzed for within-field classification. Results revealed that the variables could be aggregated into MZs that characterize spatial variability in soil chemical properties and crop productivity. The resulting classified MZs showed favorable agreement between EC_a and crop yield variability pattern. This enables reduction in number of soil analysis needed to create application maps for certain cultivation operations.