豫西耕地土壤速效钾现况与冬小麦施钾效果

豫西土壤中速效钾的含量每年以2.2mg/kg下降。冬小麦试验表明,施钾增产效果明显,平均增产小麦28 4kg/667m2,增产率达11.5%,每kgK2O增产小麦3.55kg。干旱年份的增产效果明显高于正常年份,并且有随肥力水平的升高增产幅度更大的趋势,施钾使亩穗数增加最多。     

含盐量对土壤的水汽吸附及土壤水能量状态的影响

以甘肃景电灌区盐化土壤为对象用水汽平衡吸附法就盐分对土壤的水汽吸附和土壤水能量状态的影响进行了研究 .结果表明盐分显著增加了土壤水汽吸附量 ,水汽饱和度为 98%的情况下 ,含盐量为 1 0 .772 g/kg和 1 2 .887g/kg的两个土壤的水汽吸附量分别达到了 1 9.4 5 %和 2 5 .34 % .水汽饱和度大于65 %左右时水汽吸附有一个明显的转折点 ,.水汽饱和度大于 65 %时水汽吸附量主要受含盐量影响 ,而当饱和度小于 65 %时则主要受物理性粘粒含量的影响 .盐分非常显著地降低了土壤的水势 ,可以用盐化土样的水势与脱盐处理土样的水势估算盐化土样的渗透势 .估算结果表明在低水势段以及在相当大含水量范围内盐化土壤因盐分浓度所产生的渗透势的绝对值远大于基质势的绝对值     

土壤磷素对作物产量及供磷能力的影响

多年多点试验研究表明 ,河西走廊地区主要耕地 0～ 2 0cm耕层有效P平均含量 9 9mg/kg ,10mg/kg以下的农田占 5 6 4% ,大于 15mg/kg的占 19 5 % ,90 %的农田施P增产 15 0 %～ 2 6 0 %。作物对土壤磷依存率在氮肥激发条件下为 68 1%～ 85 9% ;无肥条件下 46 1～ 75 8% ,供磷力与土壤磷呈正相关。作物吸收的磷素 14 1%～ 3 1 9%由当季施肥供给 ,磷肥的当季利用率平均为 9 9%～ 17 6%。     

生草覆盖对果园土壤养分、果实产量及品质的影响

通过试验证明果园生草制是我国干旱、半干旱地区果园土壤管理的一个行之有效的模式。果园生草覆盖区与对照相比土壤养分明显提高,有机质增加4.1g/kg～4.7g/kg,提高47%～54%;全氮增加0.05g/kg～0.08g/kg,提高7.0%～12%;有效磷增加3.5mg/kg～6.2mg/kg,提高20%～35%;速效钾增加27mg/kg～75mg/kg,提高9.0%～25%;苹果可溶性固形物、硬度、果形指数、可溶性糖及糖酸比等指标明显提高,可滴定酸明显下降;苹果产量和经济效益显著提高,提高幅度分别为12.73%～31.57%和15.17%～36.22%。     

硫氮或硫硼配合对油菜籽产量及品质的影响

1995～ 1 996年进行的田间和盆栽试验表明 ,硫氮或硫硼配施可以显著增加菜籽产量 .硫氮配施比对照增产 1 0 8 2～ 3 1 4 0kg/hm2 和 5 5～ 1 9 6% ,硫硼配施比对照增产 83 4～ 2 4 8 2kg/hm2 和 6 9～2 3 1 % .施硫可以增加油菜植株体内的硫含量并改善其硫素营养 ;在缺硫土壤上施硫可以降低菜籽硫甙及芥酸含量 ,提高油酸含量 ,因此有改善菜籽品质的作用 .     

设施菜地土壤养分演变规律及对地下水威胁的研究

1994～1997年山东寿光设施蔬菜年平均施肥量达到N 1351.2kg hm-2、P2O51701.2kg hm-2和K2O 539.6kg hm-2;2004年与1997年相比,氮肥和磷肥的用量减少,钾肥的用量增加,有机养分的比例增加.日光温室蔬菜氮肥、磷肥、钾肥的表观利用率分别为21.33%、2.82%、61.34%.蔬菜土壤有机质含量高于露地土壤.寿光日光温室土壤中碱解氮含量平均205.4mg kg-1;速效磷的含量平均为225.2mg kg-1,具有明显的积累效应,与设施种植时间之间存在极显著的相关性(r=0.550**,n=35);土壤速效钾含量最高为369.7mg kg-1,也具有明显的积累效应,与设施使用时间具有极显著的相关性(r=0.502**,n=35).设施表层土壤中水溶性钙的含量平均为336.0mg kg-1,土壤水溶性镁的含量平均为70.6mg kg-1.日光温室土壤中微量元素除硼外,含量均高于露地土壤.地下水硝酸盐污染严重,而且上升迅速.     

江西省农田土壤有效硫现状研究

采集了江西 1 6个县市 9种主要母质的 6 0 9个农田耕层土样进行了土壤有效硫含量测定 .统计结果表明 :平均值为 2 6 7mg/kg ,缺硫和潜在缺硫样点占 39 1 % .按地区分 ,以赣南、赣东北山区缺硫最严重 ,有效硫小于 1 2mg/kg的样点占 2 6 6 %～ 4 4 7% ,其次是丘陵地区 ,有效硫小于 1 2mg/kg的样点占1 0 0 %～ 1 9 0 % .按母质分 ,以石英岩、花岗岩发育的土壤最缺 ,约占 50 %～ 6 0 % ,其次是红砂岩、泥质岩 ,缺硫为 30 %～ 4 0 % ,这些是江西省急需施用硫肥的土壤 .水稻土以黄砂泥田、麻砂泥田、红砂泥田、鳝泥田等土属有效硫缺乏面积最大 ,全省水稻土有效硫缺乏的面积约为 1 0 3 8万hm2 ,约占水稻土面积的 34 % .     

浙中红壤油菜田供钾特性和钾肥用量研究

通过多点田间试验研究红壤性水田油菜供肥特性和钾肥施用量.18个田间试验施钾油菜籽增产幅度为7.5～90.8kg/亩,无钾区相对产量变幅为48.2～93.1%.1mol/LNH4OAc提取的土壤速效钾含量与无钾区相对产量之间达极显著相关,相关系数为0.6449**(n＝18).土壤速效钾的"临界水平”为80mg/kgK,能满足95%相对产量的"足够水平值”为150mg/kgK,系统研究平衡施肥法中各参数的确定,并用平衡施肥法和施肥曲线确定油菜钾肥合理用量,两种方法具有可比性.     

洞庭湖区不同耕种方式下水稻土壤有机碳、全氮和全磷含量状况

在洞庭湖区的2km2典型样区内,按3个/hm2的密度采集土样,分析不同耕种方式下(水稻、水旱轮作油菜、水改旱种苎麻1~5年)水稻土壤的有机碳、全氮和全磷含量状况。结果表明,水稻田土壤有机碳、全氮和全磷含量水平均较高,水田改为旱地后土壤有机碳、全氮含量及C/N比值有较大幅度的下降,但全磷含量变化不大。土壤有机碳、全氮及C/N比值均以水稻田土壤>油菜地土壤>苎麻地土壤,与水稻田相比,油菜土壤有机碳平均下降了11.19%、全氮下降了10.33%,而苎麻土壤有机碳平均下降了35.57%、全氮下降了31.61%。土壤有机碳与全氮之间呈线性关系,相关性均达极显著水平(P<0.01)。     

辽宁省水稻土壤养分丰缺指标建立初探

根据"3414"试验结果,初步建立了辽宁省水稻土养分丰缺指标.水稻相对产量与土壤碱解氮、速效P、速效K含量进行方程拟合,以相对产量50%、50%～65%、65%～75%、75%～85%和大于85%为标准,得出土壤肥力等级为极低、低、中、高、较高对应的土壤碱解氮含量为小于58mg kg-1、58～120mg kg-1、120～196mg kg-1、196～318mg kg-1、大于318mgkg-1;以相对产量80%、80%～85%、85%～90%和大于95%为标准,得出土壤肥力等级为极低、低、中、高、较高对应的土壤速效P含量为小于7mg kg-1、7～9mg kg-1、9～12mg kg-1、12～15mg kg-1、大于15mg kg-1;对应的土壤速效K含量为小于6mg kg-1、6～20mg kg-1、20～63mg kg-1、63～205mg kg-1,大于205mg kg-1.     

Interference of salt and moisture on soil reflectance spectra

This article portrays the effects of salt and moisture on soil reflectance spectra and their consequent influences on the estimation of soil salinity and soil moisture contents (SMC). It is amid to demonstrate and discuss how the interference of salt and moisture, as soil constituents, on soil spectra can affect the estimation of either soil salinity or SMC when spectral variabilities are used as predictive variables. To achieve this objective, a data set was obtained from a test area where soil salinity and SMC were largely varied. Furthermore, the Inverted Gaussian (IG) modelling approach, which has been successfully used for the estimation of soil salinity under laboratory conditions and for the estimation of SMC for non-saline soil, is used in this study. Using the IG function, the near-infrared (NIR) and the shortwave infrared (SWIR) regions of the salt-affected soil spectra, with various amount of moisture, were fitted to an IG curve. Parameters of the fitted curve such as functional depth, distance to the inflection point and area under the curve were then used as predictors in a multi-regression analysis to quantify the effect of soil salinity and SMC on soil spectra. The results suggest that a combination of salt and moisture in soil causes anomalies and therefore variations in neither salt nor moisture contents can be modelled accurately on the basis of quantification of soil reflectance. These results suggest that further studies are required to determine a set of calibrating coefficients that can be used to eliminate the background spectral effects caused by either soil salinity or SMC.     

Salinity modelling by inverted Gaussian parameters of soil reflectance spectra

This paper presents an approach to estimate soil salinity through modelling of soil spectra using an inverted Gaussian (IG) function. The approach is tested on experimental datasets including measurements of soil physicochemical properties and their spectral reflectance which are obtained under controlled laboratory conditions. The near-infrared (NIR) and shortwave infrared (SWIR) region of the salt-affected soil spectra were fitted to an inverted Gaussian curve. Parameters of the fitted curve, such as functional depth, distance to the inflection point and area under curve, were then used as predictors in regression analysis to estimate soil salinity levels. The results suggest a successful estimation of salinity levels, especially, for soil samples treated with epsomite and bischofite solutions. Amongst the calculated IG parameters, the area under fitted curve resulted in the most accurate estimations. The results demonstrate the relative utility of high spectral resolution data for estimating soil salinity under laboratory controlled conditions.     

The relationships between electrical conductivity of soil and reflectance of canopy,grain, and leaf of rice in northeastern Thailand

Soil salinity is a global environmental problem and the most widespread land degradation problem that reduces crop yields and agricultural productivity. The characteristic of soil salinity is conventionally measured by the electric conductivity (EC) of soil while remote-sensing techniques have been extensively applied to detect the presence of salts indirectly through the vegetation using crop spectral reflectance. This study aims primarily to investigate whether salt stress the rice can be detected by field reflectance or not, and second, to search the significant bands of vegetation indices that can indicate the relationships between the EC of soil and field hyperspectral reflectance of canopy, grain, and leaf of rice, using the normalized difference spectral index (NDSI). Field investigations on various paddy fields in northeastern Thailand were carried out in late November 2010 during the ripening season just before harvest in an attempt to realize the applications of the field hyperspectral technique for monitoring the spread of saline soils and estimation of the effects of soil salinity on rice plants. Jasmine rice and glutinous rice were two different rice species selected for this study. Rice plant investigations were conducted by collecting data on crop length, panicle length, canopy openness, leaf area index, and digital photographs of plant conditions from each site. The statistical analysis revealed that the changes in soil EC were significantly sensitive to the ripening stages of both jasmine rice and glutinous rice planted on different levels of soil salinity. Among reflectance measurements, canopy reflectance was highly correlated with soil EC. However, the estimated accuracies of the relationship between soil EC and reflectance of glutinous rice were relatively lower than those of jasmine rice.     

Dielectric properties of salt-affected soils

A detailed laboratory experiment was conducted on three soils of different textures viz., sand, sandy clay loam and clay to study the influence of soil salinity and sodicity on the complex dielectric behaviour of soils as a function of volumetric soil moisture using an L-band (1 ·25 GHz) dielectric probe. The results revealed that soil salinity has no influence on the real part of the dielectric constant (?') whereas, the imaginary part (?'') is dependent and increases with increase in salinity for all the soils considered. It was found that the real part is more dependent on soil moisture and imaginary part on soil salinity. The sodicity of a soil has no influence either on real part or imaginary part. This study shows L-band (1·25 GHz) microwave response to soil salinity. It also demonstrates the possibility of separating saline soils from sodic soils at L-band frequencies under moist soil conditions.     

吉林西部盐碱地特性微波双频差分无损探测

针对吉林西部盐碱地特性(内地苏打盐类型),应用车载双频段被动微波遥感系统,对不同盐碱状态的4个裸盐碱区进行双极化多角度微波辐射无损探测。基于多角度双频率双极化的观测数据优势,选择逼近式迭代算法来反演其介电常数虚部,Dobson模型反演介电常数实部。在此基础上,应用双频差分法研究了该区域盐碱地介电特性与含水量、含盐量的关系。双频差分结果表明:实部双频差分与盐碱土含水量呈线性关系,相关系数为0.9996;虚部双频差分与含盐量呈线性关系,相关系数为0.9977。这为应用被动微波遥感定量反演盐碱地特性(含水量、含盐量)奠定了理论基础。     

Incorporating legacy soil data to minimize errors in salinity change detection: a case study of Darab Plain,Iran

The results of a 1990 soil survey of a salinized region in Darab Plain, southern Iran, were combined with soil sampling data taken in 2002 from the same locations and employed as a basis for salinity change detection in the region. New preprocessing of satellite imagery was used, along with statistical analysis of the digital number (DN)?salinity relationship, in order to determine salinization of the area. Removal of outliers on the basis of interfering land uses improved the correlations. Nonlinear regression (NLR) in the form y?=?a +?bx ^α provided a suitable predictor of salinity (y, dS m^?1) for both 1990 and 2002 based on DNs (x). Among the 12 tested methods of salinity classification in this study, the six salinity class method with intervals 0–4, 4–10, 10–32, 32–64, 64–80 and >80 dS m^–1 was selected. A series of accuracy assessments through a trial-and-error procedure was the basis of the selection of the best method and led to a final accuracy of 91%. About 42% of the lands located on ‘no saline’ and ‘low salinity’ classes in 1990 had changed to the ‘medium’, ‘very high’ and ‘new agricultural land’ classes in 2002.     

Detecting date palm trees health and vegetation greenness change on the eastern coast of the United Arab Emirates using SAVI

Due to shortage of fresh water resources, the vegetation of the eastern region of the United Arab Emirates (UAE) has experienced a series of declines resulting from salinization of groundwater, which is the major source of irrigation. To assess these changes, field measurements combined with Thematic Mapper (TM) and Enhanced Thematic Mapper Plus (ETM+) based Soil Adjusted Vegetation Index (SAVI) were analysed. TM and ETM+ images from two dates, 1987 and 2000 were acquired to enable the computation of the greenness anomalies for three sites in the eastern region, Fujairah, Kalba and Hatta. The results show an overall increase in agricultural area, associated with a severe decrease in vegetation greenness and health conditions, particularly in the Kalba study area. The SAVI values decreased with increased soil salinity, permitting the identification of salt‐affected areas. This remotely sensed data offered valuable information regarding vegetation health conditions, especially when using greenness indices. However, in open canopies, like date palm trees, soil line indices, such as, SAVI are more robust, since they account for the contribution of the soil background. This research suggests, that in order for the date palm trees of this region to stay productive, considerable attention needs to be placed in managing and monitoring soil salinity conditions and progress. Potential areas of further research range from studying the effects of tree spacing and understory crops as immediate and potential solutions to maintain productivity and mitigate the salinity problem.     

Dielectric Properties of Saline Soil and an Improved Dielectric Model

The measurement and analysis of the dielectric constant of soil samples with different moisture and salinity are achieved based control experiment. The saturation is introduced to the dielectric model of salinity soil to improve simulation accuracy by taking the Stogryn model and the influence of soil solution ion concentration, conductivity, moisture content, and salt content for dielectric constant imaginary part into consideration. The results indicate that the soil salt content has little influence on both real part and imaginary part of dielectric constant when soil volumetric moisture content is low, while soil volumetric moisture content is high, the real part of the dielectric constant decreases with the increase of soil salt content, and the imaginary part of the dielectric constant increases. The improved dielectric model of salinity soil can well reveal the changes of dielectric constant, and it is also having a great effect in Baiyin soil samples. That is to say, the improved dielectric model can apply to different soil types.     

盐渍土介电特性及模型改进研究

基于控制试验对配制的具有不同含水量和含盐量的土壤样本进行介电特征量测和分析,同时结合Stogryn盐水介电模型和土壤溶液离子浓度、电导率、含水量和含盐量等参数对介电常数虚部的影响,将饱和度这个关键参量引入盐渍土介电模型中,提高盐渍土介电模型模拟精度。结果表明：①当土壤体积含水量较低时,土壤含盐量对介电常数的实部和虚部均未产生明显的作用。当土壤体积含水量较高时,介电常数实部则随着土壤含盐量的增加呈逐渐下降趋势,介电常数虚部以增加态势为主;②修正后的盐渍土介电模型可以较好地刻画介电常数变化特征。此外,将修正后的模型在白银采样点进行验证,同样取得较好的模拟结果,表明修正后的盐渍土介电模型对不同土壤类型具有一定的适用性。     

Hyperspectral field estimation and remote-sensing inversion of salt content in coastal saline soils of the Yellow River Delta

This study explored hyperspectral field and satellite-based remote sensing of soil salt content. Using Kenli County in the Yellow River Delta as the study area, in situ soil field spectra and satellite-based remote-sensing images were integrated with laboratory measurements of soil sample salinity to improve remote sensing-based soil salt estimation and inversion procedures. First, the narrow-band hyperspectral reflectance field data were used to model the wide-band reflectance data from Landsat 7. Second, the bands and spectral features sensitive to soil salt content were identified through correlation analysis and band combination. Stepwise multiple linear regression was used to find a best model, which was then inverted to predict soil salt content using remote-sensing images from Landsat 7 and Landsat 8. The applicability of the model was verified by ground-checking the inversion results. The results show that the bands sensitive to soil salinity are mainly in the visible and near-infrared (NIR) regions. Combining information from these bands can eliminate some background effects and significantly improve the correlation with salinity. The best model of soil salinity is y = 1.345 ? 25.898 × g_SWIR1 ? 245.440 × g_Red × (g_Red ? g_NIR) ? 0.252 × (g_Red + g_NIR)/(g_Red ? g_NIR) ? 19.563 × (g_Red ? g_SWIR1). This model has a coefficient of determination (R²) of 0.896, a verification R² of 0.867, a relative prediction deviation (RPD) of 2.135, and a root mean square error (RMSE) of 0.264. The model fits well and is highly stable. The inversion results based on Landsat 7 and Landsat 8 images are consistent with the actual situation of soil salinity in the study area. This study provides an effective and feasible method for the estimation of soil salt content in coastal regions based on field spectral measurements and remote-sensing inversion.