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1.
Rapid soil testing and soil quality assessment are essential to address soil degradation and low farm incomes in smallholder farms. With the objective of testing diffuse reflectance spectroscopy (DRS) to rapidly assess soil chemical properties, nutrient content and a soil quality index (SQI), samples of surface soil were collected from 1113 smallholder farms in seven districts in Bundelkhand region of Uttar Pradesh, India. A minimum dataset (MDS) approach was followed to estimate SQI using the three chemical parameters of soil pH, electrical conductivity (EC) and soil organic carbon (SOC), and 11 different soil nutrients. Principal component and correlation analyses showed that soil pH, SOC content and three available nutrients − copper (Cu), iron (Fe) and sulphur (S) − may constitute the MDS. Estimated SQI values showed strong positive correlation with crop yields. Results of chemometric modelling showed that the DRS approach could yield the coefficient of determination (R2) values in the validation datasets ranging from 0.79 to 0.94 for exchangeable calcium (Ca) followed by 0.67–0.88 for exchangeable potassium (K), 0.52–0.86 for SOC and 0.53–0.81 for available boron (B) content. Except in one district, the DRS approach could be used to estimate SQI values with R2 values in the range of 0.63–0.81; an R2 value of 0.71 was obtained in the pooled dataset. We also estimated the three-tier soil test crop response (STCR) ratings to compare DRS and wet chemistry soil testing approaches. Similar STCR ratings were obtained for both these approaches in more than 86% of the samples. Parameters for which both the methods yielded similar ratings in more than 80% of the samples were EC (>98%), pH and exchangeable Ca (>81%) and available B (>89%). With similar ratings, these results suggest that the DRS approach may safely be used for farmers' fields, replacing the traditional wet analysis approach of soil testing.  相似文献   

2.
Soil organic matter (SOM) is a fundamental soil constituent. The estimation of this parameter in the laboratory using the classical method is complex time-consuming and requires the use of chemical reagents. The objectives of this study were to assess the accuracy of two laboratory measurement setups of the VIS-NIR spectroscopy in estimating SOM content and determine the important spectral bands in the SOM estimation model. A total of 115 soil samples were collected from the non-root zone (0–20 cm) of soil in the study area of the Triffa Plain and then analysed for SOM in the laboratory by the Walkley–Black method. The reflectance spectra of soil samples were measured by two protocols, Contact Probe (CP) and Pistol Grip (PG)) of the ASD spectroradiometer (350–2500 nm) in the laboratory. Partial least squares regression (PLSR) was used to develop the prediction models. The results of coefficient of determination (R2) and the root mean square error (RMSE) showed that the pistol grip offers reasonable accuracy with an R2 = 0.93 and RMSE = 0.13 compared to the contact probe protocol with an R2 = 0.85 and RMSE = 0.19. The near-Infrared range were more accurate than those in the visible range for predicting SOM using the both setups (CP and PG). The significant wavelengths contributing to the prediction of SOM for (PG) setup were at: 424, 597, 1432, 1484, 1830,1920, 2200, 2357 and 2430 nm, while were at 433, 587, 1380, 1431, 1929, 2200 and 2345 nm for (CP) setup.  相似文献   

3.
Soil salinization is an important desertification process that threatens the stability of ecosystems, especially in arid lands. Quantifying and mapping soil salinity to monitor soil salinization is difficult because of its large spatial and temporal variability. There has been a growing interest in the use of hyperspectral reflectance as a rapid and inexpensive tool for soil salinity characterization in the recent past. However, as soil moisture often jointly affects soil reflectance, a moisture-insensitive reflectance model is needed to provide the base for soil salinity monitoring from soil reflectance. In this paper, we developed an exponent reflectance model to estimate soil salt contents inversely under various soil moisture conditions, based on a control laboratory experiment on the two factors (soil salinity and soil moisture) to soil reflectance. Main soil salt types (Na2SO4, NaCl, Na2CO3) with wide soil salinity (0% to 20%) and soil moisture (1.75% to 20%) levels (in weight base) from Western China were examined for their effects on soil reflectance through a model based approach. Moisture resistant but salt sensitive bands of reflected spectra have been identified for the model before being applied to inversely estimate soil salt content. Sensitive bands for Na2SO4 type of salt affected soils were identified as from 1920 to 2230 nm, and 1970 to 2450 nm for NaCl, 350 to 400 nm for Na2CO3 type of salt affected soils, respectively. The sensitive bands focused on ranged from 1950 to 2450 nm when all data were considered when ignoring salt types. The model was then applied to inversely estimate soil salt contents. High R2 of 0.87, 0.79, and 0.66, and low mean relative error (MRE) of 16.42%, 21.17%, and 27.16%; have been obtained for NaCl, Na2SO4 and Na2CO3, respectively. Performance of the inverse model dropped but remained significant when ignoring salt types with an R2 of 0.56 and a MRE of 33.25%. The approach proposed in this study should thus provide a new direction for estimating salinity from reflectance under various soil moisture conditions and should have wide applications in future monitoring of soil salinization.  相似文献   

4.
《Soil & Tillage Research》2007,94(1):239-250
Uniform phosphorous fertilisation has economical, ecological and agronomical shortcomings. This study was undertaken to optimise the variable rate (VR) elemental P application using a previously developed on-the-go visible (VIS) and near infrared (NIR) soil sensor. This VIS–NIR sensor consists of a chisel unit, to which the optical unit to detect soil extractable phosphorous (P-ext) was attached. A mobile, fibre-type VIS–NIR spectrophotometer (Zeiss Corona 45 visnir, Germany) with a measurement range between 305 and 1711 nm was used to measure soil spectra in reflectance mode. On-the-go measurement of soil spectra was carried out in two fields (A and B) situated near Leuven in Belgium. From the spectra, P-ext was calculated in soil and subsequently the required elemental P was determined. Different averaging windows (AW) of the predicted P-ext from successive spectra (2–22) and five recommendation classification intervals (RCI) of elemental P of 20, 10, 5, 2 and 1 kg ha−1 were assigned and tested. The VR of elemental P was compared with uniform rate (UR) application. Results showed that among the five RCIs, the minimum elemental P application rate was for interval of 5 kg ha−1, with small differences of among the different RCIs. In the fields under study, the amount of elemental P fertiliser according to the VR approach was higher than the UR application with an extra elemental P of 4 and 2.38 kg ha−1 for fields A and B, respectively. However, this higher elemental P fertiliser recommendation of VR is only valid when an equal number of samples (1200 in field A and 660 in field B) is considered for both VR and UR methods. Larger amounts of elemental P fertiliser were needed for plots and/or fields having higher variation in measured P-ext. The results also showed that in both fields the application rate decreased with larger AWs. Averaging of less than five P-ext successive values was not a proper choice with any RCIs due to the large deviation between the target and classified elemental P into the different RCIs. The combination of RCI 5 and AW between 10 and 15 is recommended to provide a good matching between uniform and applied elemental P at low cost.  相似文献   

5.
Soil structure and structural stability are key parameters in sustainable soil management and optimum cropping practices. This study aimed to improve the knowledge of potential precision tillage practices by characterizing the effect of varied tillage intensities on structural properties of a clay loam soil. An experiment with seedbed preparation was conducted using a power take‐off‐driven rotovator equipped to measure torque and angular velocity and with operational speed (OS) and rotational speed (RS) as main factors. Effects of soil coverage prior to tillage and wheeling directly after tillage were measured at one combination of OS and RS. The soil was sampled at 0–80 mm depth. Under slow OS (2.9 km hr?1) compared with fast OS (6.3 km hr?1), specific energy input was greater (116 and 52 J kg?1 on average, respectively), and it increased with RS. Wheeling resulted in larger aggregate diameter right after tillage (at T1; 56 mm as geometric mean compared with 9 mm), with 42 times smaller geometric mean of air permeability 45 days after tillage (at T2) and with greater soil dispersibility at T2. Highly significant correlations were observed between soil dispersibility and energy input, specific surface area of aggregates, fractions of small (<4 mm) and medium (8–16 mm) aggregates, and geometric mean diameter. Slow OS combined with fast RS showed significantly greater air permeability than all other treatments. The results suggest that there is a potential for controlling soil structure in seedbed preparation by minimizing compaction from traffic and adapting site‐specific control of rotovation intensity.  相似文献   

6.
The emergence of a new sensor technology based on the use of ion‐selective membranes provides an increasing number of opportunities for on‐the‐go field measurements of soil nutrients and soil pH. In the future, on‐the‐go sensing should provide a cost‐effective monitoring of heterogeneous soils with high sampling resolution. It is suitable for site‐specific management because it can be focused on the spatial representativity of observation. This study evaluates the on‐the‐go‐sensing sampling design by comparing it with a standard approach to soil sampling for soil pH and the base nutrients P, K, and Mg under local field conditions in Germany. Soil samples were taken in two test sites at a resolution and in a manner as if they were sampled with an on‐the‐go sensing system and were compared with soil samples taken at a coarser resolution and with standard methods. In general, a higher variability was observed among the on‐the‐go samples due to their smaller sample support. The finer sampling resolution of the on‐the‐go design improved field‐scale semivariogram‐analysis results, identifying the spatial structures for soil pH, P, and Mg clearly. In addition, kriged maps of these soil parameters had predominantly higher estimation accuracies. However, the on‐the‐go samples were strongly influenced by the small‐scale variability of K in one of the test sites. This variability increased the kriging standard deviation for K by 50% compared with standard sampling design. Despite of this problem, the on‐the‐go‐sensing sampling design revealed field‐scale spatial variability for base nutrient status more accurately. Except for K, the mean absolute error of fertilizer‐application maps was reduced when using the on‐the‐go sample design in comparison with the standard sample design (Ca: 210/268 kg ha–1, P: 2.85/6.75 kg ha–1, K: 13.7/6.0 kg ha–1, Mg 5.7/6.8 kg ha–1). This will reduce over‐ and underfertilization using variable‐rate fertilizer‐application systems. In the future, it will be of interest if real on‐the‐go soil‐sensor measurements exhibit the same variability behavior addressed here or if results will differ substantially.  相似文献   

7.
The value of hyperspectral imagery in agricultural management has been amply demonstrated. Despite this, image interpretation is often drastically impeded by changes in soil moisture content (SMC). Soil moisture variations dominate the spectral reflectance in the 350–2500‐nm wavelength domain and affect the effectiveness of spectral indices used to monitor variations in soil and vegetation properties. Consequently, removing soil moisture effects in spectral images is critical and would provide a significant breakthrough for agricultural remote sensing. Yet, current available soil moisture reflectance models fail to properly address the moisture‐induced reflectance changes occurring within soils of the same texture class. This very much limits the operational implementation of these models, particularly in agricultural fields where within‐field variations in soil characteristics such as organic matter and clay content prevail. In this study, the effect of SMC on the reflectance in the 400–2500‐nm spectral domain was studied for six sandy soils located in citrus orchards in the Western Cape Province, South Africa. In a series of experiments, novel insights into soil moisture reflectance modelling of sandy cultivated soils are provided. The wavelength and soil‐specific variations in model parameters are mechanistically modelled and a general model for moist reflectance of cultivated sand soils is presented and successfully tested. Model comparison and validation demonstrate that the model fit of soil‐type‐specific models can be approximated (R2 = 0.82; RRMSE = 0.14) while a significant increase in model fit compared with the traditional general models (R2 = 0.59; RRMSE = 0.28) was achieved.  相似文献   

8.
Arid soil is common worldwide and has unique properties that often limit agronomic productivity, specifically, salinity expressed as soluble salts and large amounts of calcium carbonate and gypsum. Currently, the most common methods for evaluating these properties in soil are laboratory‐based techniques such as titration, gasometry and electrical conductivity. In this research, we used two proximal sensors (portable X‐ray fluorescence (PXRF) and visible near‐infrared diffuse reflectance spectroscopy (Vis–NIR DRS)) to scan a diverse set (n = 116) of samples from arid soil in Spain. Then, samples were processed by standard laboratory procedures and the two datasets were compared with advanced statistical techniques. The latter included penalized spline regression (PSR), support vector regression (SVR) and random forest (RF) analysis, which were applied to Vis–NIR DRS data, PXRF data and PXRF and Vis–NIR DRS data, respectively. Independent validation (30% of the data) of the calibration equations showed that PSR + RF predicted gypsum with a ratio of performance to interquartile distance (RPIQ) of 5.90 and residual prediction deviation (RPD) of 4.60, electrical conductivity (1:5 soil : water) with RPIQ of 3.14 and RPD of 2.10, Ca content with RPIQ of 2.92 and RPD of 2.07 and calcium carbonate equivalent with RPIQ of 2.13 and RPD of 1.74. The combined PXRF and Vis–NIR DRS approach was superior to those that use data from a single proximal sensor, enabling the prediction of several properties from two simple, rapid, non‐destructive scans.  相似文献   

9.
Residue retention and reduced tillage are both conservation agricultural practices that may enhance soil organic carbon (SOC) stabilization in soil. We evaluated the long‐term effects of no‐till (NT) and stover retention from maize on SOC dynamics in a Rayne silt loam Typic Hapludults in Ohio. The six treatments consisted of retaining 0, 25, 50, 75, 100 and 200% of maize residues on each 3 × 3 m plot from the crop of previous year. Soil samples were obtained after 9 yrs of establishing the experiment. The whole soil (0–10 and 10–20 cm of soil depths) samples under different treatments were analysed for total C, total N, recalcitrant C (NaOCl treated sample) and 13C isotopic abundance (0–10 cm soil depth). Complete removal of stover for a period of 9 yrs significantly (P < 0.01) decreased soil C content (15.5 g/kg), whereas 200% of stover retention had the maximum soil C concentration (23.1 g/kg). Relative distribution of C for all the treatments in different fractions comprised of 55–58% as labile and 42–45% as recalcitrant. Retention of residue did not significantly affect total C and N concentration in 10–20 cm depth. 13C isotopic signature data indicated that C4‐C (maize‐derived C) was the dominant fraction of C in the top 0–10 cm of soil layer under NT with maize‐derived C accounting for as high as 80% of the total SOC concentration. Contribution of C4‐C or maize‐derived C was 71–84% in recalcitrant fraction in different residue retained plots. Residue management is imperative to increase SOC concentrations and long‐term agro‐ecosystem necessitates residue retention for stabilizing C in light‐textured soils.  相似文献   

10.
Recent advances in semiconductor technologies have given rise to the development of mid‐infrared (mid‐IR) spectrometers that are compact, relatively inexpensive, robust and suitable for in situ proximal soil sensing. The objectives of this research were to evaluate a prototype portable mid‐IR spectrometer for direct measurements of soil reflectance and to model the spectra to predict sand, clay and soil organic matter (SOM) contents under a range of field soil water conditions. Soil samples were collected from 23 locations at different depths in four agricultural fields to represent a range of soil textures, from sands to clay loams. The particle size distribution and SOM content of 48 soil samples were measured in the laboratory by conventional analytical methods. In addition to air‐dry soil, each sample was wetted with two different amounts of water before the spectroscopic measurements were made. The prototype spectrometer was used to measure reflectance (R) in the range between 1811 and 898 cm?1 (approximately 5522 to 11 136 nm). The spectroscopic measurements were recorded randomly and in triplicate, resulting in a total of 432 reflectance spectra (48 samples × three soil water contents × three replicates). The spectra were transformed to log10 (1/R) and mean centred for the multivariate statistical analyses. The 48 samples were split randomly into a calibration set (70%) and a validation set (30%). A partial least squares regression (PLSR) was used to develop spectroscopic calibrations to predict sand, clay and SOM contents. Results show that the portable spectrometer can be used with PLSR to predict clay and sand contents of either wet or dry soil samples with a root mean square error (RMSE) of around 10%. Predictions of SOM content resulted in RMSE values that ranged between 0.76 and 2.24%.  相似文献   

11.
Soil fertility depletion in smallholder agricultural systems in sub-Saharan Africa presents a formidable challenge both for food production and environmental sustainability. A critical constraint to managing soils in sub-Saharan Africa is poor targeting of soil management interventions. This is partly due to lack of diagnostic tools for screening soil condition that would lead to a robust and repeatable spatially explicit case definition of poor soil condition. The objectives of this study were to: (i) evaluate the ability of near infrared spectroscopy to detect changes in soil properties across a forest-cropland chronosequence; and (ii) develop a heuristic scheme for the application of infrared spectroscopy as a tool for case definition and diagnostic screening of soil condition for agricultural and environmental management. Soil reflectance was measured for 582 topsoil samples collected from forest-cropland chronosequence age classes namely; forest, recently converted, RC (17 years) and historically converted, HC (ca.70 years). 130 randomly selected samples were used to calibrate soil properties to soil reflectance using partial least-squares regression (PLSR). 64 randomly selected samples were withheld for validation. A proportional odds logistic model was applied to chronosequence age classes and 10 principal components of spectral reflectance to determine three soil condition classes namely; “good”, “average” and “poor” for 194 samples. Discriminant analysis was applied to classify the remaining 388 “unknown” samples into soil condition classes using the 194 samples as a training set. Validation r2 values were: total C, 0.91; total N, 0.90; effective cation exchange capacity (ECEC), 0.90; exchangeable Ca, 0.85; clay content, 0.77; silt content, 0.77 exchangeable Mg, 0.76; soil pH, 0.72; and K, 0.64. A spectral based definition of “good”, “average” and “poor” soil condition classes provided a basis for an explicitly quantitative case definition of poor or degraded soils. Estimates of probabilities of membership of a sample in a spectral soil condition class presents an approach for probabilistic risk-based assessments of soil condition over large spatial scales. The study concludes that reflectance spectroscopy is rapid and offers the possibility for major efficiency and cost saving, permitting spectral case definition to define poor or degraded soils, leading to better targeting of management interventions.  相似文献   

12.
A soil quality database (SQDB) is a collection of soil samples described by a given set of parameters, allowing farmers, scientists and other stakeholders to make informed decisions about practices, processes and policies for soil use and management. If each parameter is considered as a dimension of the space spanned by the SQDB, extracting information becomes a difficult task when the number of parameters is >3. A widely used approach to explore multidimensional data sets is the self‐organizing map (SOM) method, which is suitable for clustering, visualization and extraction of information from multidimensional data. We applied the SOM method as an exploratory technique to an unlabelled SQDB to extract knowledge – data patterns and data associations – from the data set (the time and location of each sample were unknown). The SQDB used in this study is a set of 1240 unlabelled samples within the Central Valley of Chile, covering ca 7500 km2. The predominant soils are Andisols with a large organic matter content (7–12%), small bulk densities (0.6–1.0 g/cm3) and large water‐holding capacity. We identified three patterns: (i) isolated region within the map with close neurons (smooth transitions), (ii) two or more regions with predominantly large or small values and (iii) homogeneous map with small values with an isolated region of large values. These patterns show that the data set represented more than two groups that were not necessarily related. For pH, no important associations with other investigated parameters were observed. Previous studies carried out by the local agricultural research station showed that pH values below 5.5 constrain nutrient uptake. Thus, locations presenting pH<5,5 should be subject to seasonal monitoring to assess management practices that mitigate soil acidity. The component plane for organic matter indicates that ca. 50% of the soil samples had contents <8% related to soil series characteristics and management practices. As the k‐means is initialized by random partitions, the two‐step approach (clustering the map representing the input data) is less sensitive to variations in the input data (subsamples) than is the direct application of k‐means to the input data, but it also reduces the computational cost. The ability of SOMs to visualize multidimensional data sets helps gain an understanding of the data in the exploratory phase, such as the association and integration of physical, chemical and biological parameters.  相似文献   

13.
《Soil Use and Management》2018,34(3):306-315
Quantifying temporal and spatial variation of soil phosphorus (P) input, output and balance across Chinese arable land is necessary for better P management strategies. Here, we address this challenge using a soil P budget to analyse the soil P balance in arable land across the whole of China, for the period 1980–2012. Results indicated that the total P input to soil increased from 22.5 kg P/ha in 1980 to 79.1 kg P/ha in 2012. However, the total P output from soil only increased from 17.9 kg P/ha in 1980 to 36.9 kg P/ha in 2012. Therefore, the average net soil P surplus in China increased from 4.6 kg P/ha in 1980 to 42.1 kg P/ha in 2012. Our research found great variation in soil P balances across different regions. Soil P balance varied between regions with the order of southeast (SE) > north central (NC) and the middle and lower reaches of Yangtze River (MLYR) > southwest (SW) > northwest (NW) > northeast (NE). Phosphorus that has accumulated in agricultural soil across China could theoretically meet crop P demands for approximately 4.8–12.0 yrs, depending on the bioavailability of P stored in soils. Increasing the return rates of manure and straw could substantially reduce the demand for fertilizer‐P. This paper represents a basis for more targeted, regionally informed P fertilizer recommendations in Chinese soils.  相似文献   

14.
The Australian grains industry relies on mineralized nitrogen (N) from soil organic matter and plant residues, but fertilizer N is increasingly needed to optimize yields. Most farmers are guided on N fertilizer requirements by commercial crop advisors. We surveyed (n = 132) and interviewed (n = 11) New South Wales grains advisors to gauge the usage of soil process understanding, soil data and decision support systems (DSSs) when developing N recommendations. Soil moisture at sowing, seasonal forecasts, crop rotation, soil mineral N, financial risk profiles and paddock history were all used to prepare N fertilizer advice, but stored soil moisture was most important. Farmer confidence in soil N testing was low due to high spatial variability. Most advisors calculated N fertilizer required for yields within 10%–15% of crop potential, but clients’ attitude to financial risk guided final N recommendations. Conservative growers preferred a low input system, while more reliable rainfall or greater reliance on stored soil water led growers to apply higher N rates to maximize long‐term profits. Advisors preferred “rules‐of‐thumb,” simple DSSs and knowledge of crop growth, to elaborate DSSs requiring detailed inputs and soil characterization. Few used in‐crop N sensing. N decision methodologies need to be updated to account for changes in soil fertility, cropping systems and farming practices. New research is needed to answer practical questions regarding soil N mineralization and N losses associated with alternative N application practices and extreme weather events. Training of new advisors in N processes and DSS use needs to be ongoing.  相似文献   

15.
This study aims to assess the performance of a low‐cost, micro‐electromechanical system‐based, near infrared spectrometer for soil organic carbon (OC) and total carbon (TC) estimation. TC was measured on 151 soil profiles up to the depth of 1 m in NSW, Australia, and from which a subset of 24 soil profiles were measured for OC. Two commercial spectrometers including the AgriSpecTM (ASD) and NeoSpectraTM (Neospectra) with spectral wavelength ranges of 350–2,500 and 1,300–2,500 nm, respectively, were used to scan the soil samples, according to the standard contact probe protocol. Savitzky–Golay smoothing filter and standard normal variate (SNV) transformation were performed on the spectral data for noise reduction and baseline correction. Three calibration models, including Cubist tree model, partial least squares regression (PLSR) and support vector machine (SVM), were assessed for the prediction of soil OC and TC using spectral data. A 10‐fold cross‐validation analysis was performed for evaluation of the models and devices accuracies. Results showed that Cubist model predicts OC and TC more accurately than PLSR and SVM. For OC prediction, Cubist showed R2 = 0.89 (RMSE = 0.12%) and R2 = 0.78 (RMSE = 0.16%) using ASD and NeoSpectra, respectively. For TC prediction, Cubist produced R2 = 0.75 (RMSE = 0.45%) and R2 = 0.70 (RMSE = 0.50%) using ASD and NeoSpectra, respectively. ASD performed better than NeoSpectra. However, the low‐cost NeoSpectra predictions were comparable to the ASD. These finding can be helpful for more efficient future spectroscopic prediction of soil OC and TC with less costly devices.  相似文献   

16.
Under the conditions of a long‐term fertilizer experiment, this study aimed to determine the contents of total and exchangeable aluminium in soil as well as the Al concentration in the soil solution. Additionally, Al speciation was evaluated with the use of the MINTEQA2 software. The results obtained indicated that under the conditions of long‐term application of different mineral fertilizers or farmyard manure, the soil reaction changed to a great extent (pH 3.58–6.78). At the same time, the content of total Al in soil fluctuated from 18.85 to 22.13 g/kg and that of exchangeable Al ranged from 1.42 to 102.66 mg/kg. The concentration of Al in the soil solution was highly differentiated (5.19–124.07 μmol/L) as well as that of free aluminium ions (Al3+) (0–16.9 μmol/L). In acidic soils, aluminium complexes with organic matter are the predominant forms of Al in the soil solution. In soils with neutral soil reaction, there were no free aluminium ions. Soil liming and addition of organic amendment were the treatments that restricted the presence of toxic aluminium forms in soil.  相似文献   

17.
Soil mapping across large areas can be enhanced by integrating different methods and data sources. This study merges laboratory, field and remote sensing data to create digital maps of soil suborders based on the Brazilian Soil Classification System, with and without additional textural classification, in an area of 13 000 ha in the state of São Paulo, southeastern Brazil. Data from 289 visited soil profiles were used in multinomial logistic regression to predict soil suborders from geospatial data (geology, topography, emissivity and vegetation index) and visible–near infrared (400–2500 nm) reflectance of soil samples collected at three depths (0–20, 40–60 and 80–100 cm). The derived maps were validated with 47 external observations, and compared with two conventional soil maps at scales of 1:100 000 and 1:20 000. Soil suborders with and without textural classification were predicted correctly for 44 and 52% of the soil profiles, respectively. The derived suborder maps agreed with the 1:100 000 and 1:20 000 conventional maps in 20 and 23% (with textural classification) and 41 and 46% (without textural classification) of the area, respectively. Soils that were well defined along relief gradients (Latosols and Argisols) were predicted with up to 91% agreement, whereas soils in complex areas (Cambisols and Neosols) were poorly predicted. Adding textural classification to suborders considerably degraded classification accuracy; thus modelling at the suborder level alone is recommended. Stream density and laboratory soil reflectance improved all classification models, showing their potential to aid digital soil mapping in complex tropical environments.  相似文献   

18.
Field experiments were conducted to study soil properties, soil enzymes activities, water use efficiency (WUE) and crop productivity after six years of soya bean straw mulching in the semi‐arid conditions of China. The experiment included four treatments: CK (Control), N (240 kg N ha‐1), H (soya bean straw mulching at half rate 700 kg ha‐1 with 240 kg N ha‐1) and F (soya bean straw mulching at full rate 1,400 kg ha‐1 with 240 kg N ha‐1). Soil organic carbon (SOC), soil labile organic carbon (LOC), soil available N (AN), available P (AP) and enzyme activities were analysed after wheat harvesting in 2016 and 2017. Results show that straw amounts had positive effects on the soil fertility indices being higher for treatment F. The SOC, LOC, AN, AP and enzyme activities (i.e. saccharase, urease and alkaline phosphatase) were in the order of F > H > N > CK. High wheat grain yield and WUE were observed for F treatment. A total of six years mulching along with 240 kg ha‐1 nitrogen fertilizer application is sufficient for wheat yield stability and improving soil properties except urease activities in the semi‐arid condition of China. However, the straw mulching amount should be further studied with minimum nitrogen fertilizer for an environment‐friendly and effective approach for improving the soil biological properties with adequate crop production on a sustainable basis in the semi‐arid region of China.  相似文献   

19.
Recent development in canopy optical‐sensing technology provides the opportunity to apply fertilizer variably at the field scale according to spatial variation in plant growth. A field experiment was conducted in Ottawa, Canada, for two consecutive years to determine the effect of fertilizer nitrogen (N) input at variable‐ vs. uniform‐application strategies at the V6–V8 growth stage, on soil mineral N, canopy reflectance, and grain yield of maize (Zea mays L.). The variable N rates were calculated using an algorithm derived from readings of average normalized difference vegetation index (NDVI) of about 0.8 m × 4.6 m, and N fertilizer was then applied to individual patches of the same size of NDVI readings (0.8 m × 4.6 m) within a plot (2184 m2). Canopy reflectance, expressed as NDVI, was monitored with a hand‐held spectrometer, twice weekly before tasseling and once a week thereafter until physiological maturity. Soil mineral N (0–30 cm depth) was analyzed at the V6 and VT growth stages. Our data show that both variable and uniform‐application strategies for N side‐dressings based on canopy‐reflectance mapping data required less amount of N fertilizer (with an average rate of 80 kg N ha–1 as side‐dressing in addition to 30 kg N ha–1 applied at planting), and produced grain yields similar to and higher nitrogen‐use efficiency (NUE) than the preplant fully fertilized (180 kg N ha–1) treatment. No difference was observed in either grain yield or NUE between the variable‐ and uniform‐application strategies. Compared to unfertilized or fully fertilized treatments, the enhancements in grain yield and NUE of the variable‐rate strategy originated from the later N input as side‐dressing rather than the variation in N rates. The variable‐rate strategy resulted in less spatial variations in soil mineral N at the VT growth stage and greater spatial variations in grain yield at harvest than the uniform‐rate strategy. Both variable‐ and uniform‐application strategies reduced spatial variations in soil mineral N at the VT stage and grain yield compared to the unfertilized treatment. The variable‐rate strategy resulted in more sampling points with high soil mineral N than the uniform‐rate strategy at the VT stage.  相似文献   

20.
Soil- and plant-based fertilizer recommendations hold promise for increasing farmers’ incomes with high-input crops such as cassava. Considering the significance of cassava for the food, nutritional, and economic security of a half billion people globally and the positive response of the crop to fertilizer and manure applications in terms of tuber yield and quality through starch improvement and cyanogenic glucoside reduction, these recommendations were validated and popularized in two districts of Kerala State. Soil and plant samples from nine major cassava-growing districts of Kerala were analyzed for soil reaction, organic carbon, and essential nutrients, which formed the basis for the recommendation. The soil-test-based recommendation [nitrogen (N)–phosphorus (P)–potassium (K)–zinc (Zn) at 82:6.3:68:2 kg ha?1 along with farmyard manure (FYM) at 6.25 t ha?1] resulted in the greatest benefit–cost ratio of 1.75 with improvements in tuber and soil quality.  相似文献   

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