Impact of Residual Soil Nitrate on In-Season Nitrogen Applications to Irrigated Corn Based on Remotely Sensed Assessments of Crop Nitrogen Status

Spatial and temporal variability of soil nitrogen (N) supply together with temporal variability of plant N demand make conventional N management difficult. This study was conducted to determine the impact of residual soil nitrate-N (NO₃-N) on ground-based remote sensing management of in-season N fertilizer applications for commercial center-pivot irrigated corn (Zea mays L.) in northeast Colorado. Wedge-shaped areas were established to facilitate fertigation with the center pivot in two areas of the field that had significantly different amounts of residual soil NO₃-N in the soil profile. One in-season fertigation (48 kg N ha⁻¹) was required in the Bijou loamy sand soil with high residual NO₃-N versus three in-season fertigations totaling 102 kg N ha⁻¹ in the Valentine fine sand soil with low residual NO₃-N. The farmer applied five fertigations to the field between the wedges for a total in-season N application of 214 kg N ha⁻¹. Nitrogen input was reduced by 78% and 52%, respectively, in these two areas compared to the farmer’s traditional practice without any reductions in corn yield. The ground-based remote sensing management of in-season applied N increased N use efficiency and significantly reduced residual soil NO₃-N (0–1.5 m depth) in the loamy sand soil area. Applying fertilizer N as needed by the crop and where needed in a field may reduce N inputs compared to traditional farmer accepted practices and improve in-season N management.     

Quantifying spatial variability of indigenous nitrogen supply for precision nitrogen management in small scale farming

Understanding spatial variability of indigenous nitrogen (N) supply (INS) is important to the implementation of precision N management (PNM) strategies in small scale agricultural fields of the North China Plain (NCP). This study was conducted to determine: (1) field-to-field and within-field variability in INS; (2) the potential savings in N fertilizers using PNM technologies; and (3) winter wheat (Triticum aestivum L.) N status variability at the Feekes 6 stage and the potential of using a chlorophyll meter (CM) and a GreenSeeker active crop canopy sensor for estimating in-season N requirements. Seven farmer’s fields in Quzhou County of Hebei Province were selected for this study, but no fertilizers were applied to these fields. The results indicated that INS varied significantly both within individual fields and across different fields, ranging from 33.4 to 268.4 kg ha⁻¹, with an average of 142.6 kg ha⁻¹ and a CV of 34%. The spatial dependence of INS, however, was not strong. Site-specific optimum N rates varied from 0 to 355 kg ha⁻¹ across the seven fields, with an average of 173 kg ha⁻¹ and a CV of 46%. Field-specific N management could save an average of 128 kg N ha⁻¹ compared to typical farmer practices. Both CM and GreenSeeker sensor readings were significantly related to crop N status and demand across different farmer’s fields, showing a good potential for in-season site-specific N management in small scale farming systems. More studies are needed to further evaluate these sensing technology-based PNM strategies in additional farmer fields in the NCP.     

Application of the CSM-CERES-Rice model for evaluation of plant density and nitrogen management of fine transplanted rice for an irrigated semiarid environment

The objectives of this study were to evaluate the performance of the cropping system model (CSM)-CERES-Rice to simulate growth and development of an aromatic rice variety under irrigated conditions in a semiarid environment of Pakistan and to determine the impact of various plant densities and nitrogen (N) application rates on grain yield and economic return. The crop simulation model was evaluated with experimental data collected in experiments that were conducted in 2000 and 2001 in Faisalabad, Punjab, Pakistan. The experimental design was a randomized complete block design with three replications and included three plant densities (one seedling hill⁻¹, PD₁; two seedlings hill⁻¹, PD₂; and three seedlings hill⁻¹, PD₃) and five N fertilizer regimes (control, N₀; 50 kg ha⁻¹, N₅₀; 100 kg ha⁻¹, N₁₀₀; 150 kg ha⁻¹, N₁₅₀; and 200 kg ha⁻¹, N₂₀₀). To determine the most appropriate combination of plant density and N levels, four plant densities from one seedling hill⁻¹ to four seedlings hill⁻¹ and 13 N levels ranging from 0 to 300 kg N ha⁻¹ (52 scenarios) were simulated for 35 years of historical daily weather data under irrigated conditions. The evaluation of CSM-CERES-Rice showed that the model was able to simulate growth and yield of irrigated rice in the semiarid conditions, with an average error of 11% between simulated and observed grain yield. The results of the stimulation analysis result showed that two seedlings hill⁻¹ along with 200 kg N ha⁻¹ (PD₂N₂₀₀) produced the highest yield as compared to all other scenarios. Furthermore, the economic analysis through the mean gini dominance also showed the dominance of this treatment (PD₂N₂₀₀) compared to the other treatment combinations. Thus, the management scenario that consisted of two seedlings hill⁻¹ and 200 kg N ha⁻¹ was the best for high yield and monitory return of irrigated rice in the semiarid environment. The mean monetary returns ranged from 291 US $ ha⁻¹ to 1 460 US $ ha⁻¹ to 1 460 US  ha⁻¹ among the 52 production options that were simulated. This approaching was demonstrated as effective way to optimize the density and N management for high yield and monetary return. It will help the rice production.     

Within-field nitrogen response in corn related to aerial photograph color

Precise management of nitrogen (N) using canopy color in aerial imagery of corn (Zea mays L.) has been proposed as a strategy on which to base the rate of N fertilizer. The objective of this study was to evaluate the relationship between canopy color and yield response to N at the field scale. Six N response trials were conducted in 2000 and 2001 in fields with alluvial, claypan and deep loess soil types. Aerial images were taken with a 35-mm slide film from ≥1100 m at the mid- and late-vegetative corn growth stages and processed to extract green and red digital values. Color values of the control N (0 kg N ha⁻¹) and sufficient N (280 kg N ha⁻¹ applied at planting) treatments were used to calculate the relative ratio of unfertilized to fertilized and relative difference color values. Other N fertilizer treatments included side-dressed applications in increments of 56 kg N ha⁻¹. The economic optimal N rate was weakly related (R ² ≤ 0.34) or not related to the color indices at both growth stages. For many sites, delta yield (the increase in yield between control N and sufficient N treatments) was related to the color indices (R ² ≤ 0.67) at the late vegetative growth stage; the best relationship was with green relative difference. The results indicate the potential for color indices from aerial photographs to be used for predicting delta yield from which a site-specific N rate could be determined.     

Use of soil nitrogen parameters and texture for spatially-variable nitrogen fertilization

Recent studies have demonstrated the potential importance of using soil texture to modify fertilizer N recommendations. The objective of this study was to determine (i) if surface clay content can be used as an auxiliary variable for estimating spatial variability of soil NO₃–N, and (ii) if this information is useful for variable rate N fertilization of non-irrigated corn [Zea mays (L.)] in south central Texas, USA across years. A 64 ha corn field with variable soil type and N fertility level was used for this study during 2004–2007. Plant and surface and sub-surface soil samples were collected at different grid points and analyzed for yield, soil N parameters and texture. A uniform rate (UR) of 120 kg N ha⁻¹ in 2004 and variable rates (VAR) of 0, 60, 120, and 180 kg N ha⁻¹ in 2005 through 2007 were applied to different sites in the field. Distinct yield variation was observed over this time period. Yield and soil surface clay content and soil N parameters were strongly spatially structured. Corn grain yield was positively related to residual NO₃–N with depth and either negatively or positively related to clay content depending on precipitation. Residual NO₃–N to 0.60 and 0.90 m depths was more related to corn yield than from shallower depths. The relationship of clay content with soil NO₃–N was weak and not temporally stable. Yield response to N rate also varied temporally. Supply of available N with depth, soil texture and growing season precipitation determined proper N management for this field.     

Estimation of economic and environmental potentials of variable rate versus uniform N fertilizer application to spring barley on morainic soils in SE Norway

Spring barley was grown for 4 years (2001–2004) in field trials at two sites on morainic soil in central SE Norway, with five N level treatments: 0, 60, 90, 120 and 150 kg N ha^-1. Regression analyses showed that a selection of soil properties could explain 95–98% of the spatial yield variation and 47–90% of the yield responses (averaged over years). A strategy with uniform fertilizer application of 120 kg N ha⁻¹ (U _N120) was compared with two variable-rate (VR) strategies, with a maximum N rate of either 150 kg N ha⁻¹ (VR_N150) or 180 kg N ha⁻¹ (VR_N180). These strategies were tested using either Norwegian prices (low price ratio of N fertilizer to yield value; P_N/P_Y), or Swedish prices (high P_N/P_Y). The VR_N180 strategy had the highest potential yield and net revenue (yield value minus N cost) at both sites and under both price regimes. Using this strategy with Norwegian prices would increase the profit of barley cropping as long as at least 40 and 31% of the estimated potential increase in net revenue was realized, respectively. Using Swedish prices, uniform application appeared to be as good as or even better economically than the VR methods, when correcting for extra costs of VR application. The environmental effect of VR compared with uniform application, expressed as N not accounted for, showed contrasting effects when using Norwegian prices, but was clearly favourable using Swedish prices, with up to 20% reduction in the amount of N not accounted for.     

Canopy reflectance response to plant nitrogen accumulation in rice

Tools to quantify the nitrogen (N) status of a rice canopy during inter-nodal elongation (IE) would be valuable for mid-season N management because N accounts for the largest input cost. The objective of this paper was to study canopy reflectance as a potential tool for assessing the mid-season status of N in a rice crop. Three field plot experiments were conducted in 2002 and 2003 on cultivars Wells and Cocodrie to study the canopy reflectance response of rice to plant N accumulation (PNA) during IE and to identify the wavelengths and vegetation indices that are good indicators of PNA. Each experiment included six pre-flood N treatments of 0, 33.6, 67.2, 100.8, 133.4 and 168 kg N ha⁻¹. Rice canopy reflectance, biomass, tissue N concentration and PNA were measured weekly during IE. The wavelengths most strongly correlated to PNA at the beginning of IE were 937 and 718 nm. Several vegetation indices were examined to determine which were strongly correlated (>0.7) with PNA at the beginning of IE. Multiple linear regression models of PNA on selected vegetation indices explained 53–85% of the variation in PNA during the first week of IE. This study identifies the best combinations of vegetation indices for estimating PNA in rice.     

Profitability of variable rate nitrogen application in wheat production

Using plant sensing to determine the amount of nitrogen (N) to apply has the potential to increase profits in wheat (Triticum aestivum) production by reducing N cost or by increasing grain yield. The objective of this paper was to determine if yields and profits from experimental trials that used a precision N applicator to apply N were significantly different from trials that applied pre-determined amounts of N. Across Oklahoma, USA, experiments were designed to test 10 N treatments that included two variable rate treatments (VRT), two uniform rate treatments (URT) where the level of N applied was based on optical reflectance measurements (ORM), and six conventional treatments (i.e., pre-determined uniform rates of N). Data included treatments during 2005–2009 from eight different locations. Results indicated no statistical difference in yields between the conventional treatments that apply 90 kg ha⁻¹ of N and the VRT and URT treatments. On average, the conventional treatment that applied 90 kg ha⁻¹ of top-dress N produced the largest yield, with a VRT treatment producing the third largest yield. Profits were calculated for each treatment using a partial budget. On average, the treatment that received 90 kg ha⁻¹ of top-dress N was the most profitable even though the pre-plant N (anhydrous ammonia) had a cost advantage relative to top-dress N (urea and ammonium nitrate).     

Spectral and thermal sensing for nitrogen and water status in rainfed and irrigated wheat environments

Variable-rate technologies and site-specific crop nutrient management require real-time spatial information about the potential for response to in-season crop management interventions. Thermal and spectral properties of canopies can provide relevant information for non-destructive measurement of crop water and nitrogen stresses. In previous studies, foliage temperature was successfully estimated from canopy-scale (mixed foliage and soil) temperatures and the multispectral Canopy Chlorophyll Content Index (CCCI) was effective in measuring canopy-scale N status in rainfed wheat (Triticum aestivum L.) systems in Horsham, Victoria, Australia. In the present study, results showed that under irrigated wheat systems in Maricopa, Arizona, USA, the theoretical derivation of foliage temperature unmixing produced relationships similar to those in Horsham. Derivation of the CCCI led to an r ² relationship with chlorophyll a of 0.53 after Zadoks stage 43. This was later than the relationship (r ² = 0.68) developed for Horsham after Zadoks stage 33 but early enough to be used for potential mid-season N fertilizer recommendations. Additionally, ground-based hyperspectral data estimated plant N (g kg⁻¹) in Horsham with an r ² = 0.86 but was confounded by water supply and N interactions. By combining canopy thermal and spectral properties, varying water and N status can potentially be identified eventually permitting targeted N applications to those parts of a field where N can be used most efficiently by the crop.     

Regional model for nitrogen fertilization of site-specific rainfed corn in haplustolls of the central Pampas,Argentina

In semi-arid regions, soil water and nitrogen (N) are generally limiting factors for corn (Zea mays L.) production; hence, implementation of appropriate N fertilization strategies is needed. The use of precision agriculture practices based on specific site and crop properties may contribute to a better allocation of fertilizer among management zones (MZ). The aim of this study was to develop a model for diagnosis of N availability and recommendation of N fertilizer rates adjusted to MZ for dryland corn crops growing in Haplustolls. The model considered variability between MZ by including site-specific variables [soil available water content at sowing (SAW) and Available Nitrogen (soil available N-NO₃ at planting + applied N, Nd)] using spatial statistical analysis. The study was conducted in Córdoba, Argentina in Haplustolls and consisted in four field trials of N fertilizer (range 0–161 kg N ha⁻¹) in each MZ. The MZ were selected based on elevation maps analysis. Grain yields varied between MZ and increased with larger SAW and Nd at sowing. Grain responses to Nd and SAW in any MZ were not different between sites, allowing to fit a regional model whose parameters (Nd, Nd², SAW, SAW²) contributed significantly (p < 0.001) to yield prediction. Agronomical and economically optimum N rates varied among MZs. However, the spatial variability of optimum N rates among MZs within sites was not enough to recommend variable N fertilizer rates instead of a uniform rate. Variable N fertilizer rates should be recommended only if variability in SAW and soil N among MZ is greater than that found in this work.     

Algorithms for sensor-based redistribution of nitrogen fertilizer in winter wheat

Several methods were developed for the redistribution of nitrogen (N) fertilizer within fields with winter wheat (Triticum aestivum L.) based on plant and soil sensors, and topographical information. The methods were based on data from nine field experiments in nine different fields for a 3-year period. Each field was divided into 80 or more subplots fertilized with 60, 120, 180 or 240 kg N ha⁻¹. The relationships between plot yield, N application rate, sensor measurements and the interaction between N application and sensor measurements were investigated. Based on the established relations, several sensor-based methods for within-field redistribution of N were developed. It was shown that plant sensors predicted yield at harvest better than soil sensors and topographical indices. The methods based on plant sensors showed that N fertilizer should be moved from areas with low and high sensor measurements to areas with medium values. The theoretical increase in yield and N uptake, and the reduced variation in grain protein content resulting from the application of the above methods were estimated. However, the estimated increases in crop yield, N-uptake and reduced variation in grain protein content were small.     

Using apparent soil electrical conductivity (EC<Subscript>a</Subscript>) to characterize vineyard soils of high clay content

The adoption of precision viticulture requires a detailed knowledge of variation in soil chemical, physical and profile properties. This study evaluates the usefulness of apparent electrical conductivity (EC_a) data within a GIS framework to identify variations in soil chemical and physical properties and moisture content. The work was conducted in a vineyard located in the Carneros Region (Napa Valley, California). The soil was sampled using 44 boreholes to quantify chemical and physical characteristics and 9 open pits to verify the borehole observations. Moisture content was determined using time domain reflectometry (TDR). To characterize soil EC_a, three campaigns were undertaken using a soil electrical conductivity meter (EM38). Linear regressions between soil EC_a and soil properties were determined. Boreholes and TDR data were interpolated by kriging to characterize the spatial distribution of soil variables. The resulting maps were compared to the results obtained using the best EC_a linear regressions. Using EC_a measurements, soil properties like extractable Na⁺ and Mg²⁺, clay and sand content were well estimated, while best estimates were obtained for extractable Na⁺ (r ²  = 0.770) and clay content (r ²  = 0.621). The best estimates for soil moisture content corresponded to moisture in the deeper soil horizons (r ²  = 0.449). The methods described above provided maps of soil properties estimated by EC_a in a GIS framework, and could save time and resources during vineyard establishment and management.     

Soil electrical conductivity as a function of soil water content and implications for soil mapping

Apparent soil electrical conductivity (EC_a) has shown promise as a soil survey tool in the Midwestern United States, with a share of this interest coming from the precision agriculture community. To fully utilize the potential of EC_a to map soils, a better understanding of temporal changes in EC_a is needed. Therefore, this study was undertaken to compare temporal changes in soil EC_a between different soils, to investigate the influence of changes in soil water content on soil EC_a, and to explore the impacts these EC_a changes might have on soil mapping applications. To this end, a 90 m long transect was established. Soil EC_a readings were taken in the vertical and horizontal dipoles at five points once every one to two weeks from June until October in 1999 and 2000. At the same time, soil samples were collected to a depth of 0.9 m for volumetric soil water content analysis. Soil EC_a readings were compared to soil water content. At four of the five sites linear regression analysis yielded r ² values of 0.70 or higher. Regression line slopes tended to be greater in lower landscape positions indicating greater EC_a changes with a given change in soil water content. Two of the soils had an EC_a relationship that changed as the soils became dry. This is an item of concern if EC_a is to be used in soil mapping. Results indicated that soil water content has a strong influence on the EC_a of these soils, and that EC_a has its greatest potential to differentiate between soils when the soils are moist. Soil water content is an important variable to know when conducting EC_a surveys and should be recorded as a part of any report on EC_a studies.     

Strategies to evaluate goodness of reference strips for in-season, field scale, irrigated corn nitrogen sufficiency

The nitrogen (N) sufficiency approach to assess plant N status for in-season N management requires a non-N-limiting reference to make N recommendations. Use of reference strips in fields with spatially variable soils and the impact this variability has within N enriched reference strips are not well understood. Consequently three strategies were investigated to evaluate the impact of spatially variable sandy soils within reference strips in two commercial center pivot-irrigated corn fields. Evaluation strategies were: (i) ignore soil spatial variability throughout the reference strips, (ii) account for soil variability in the reference strips based on second-order NRCS soil map units, and (iii) account for soil variability based on apparent electrical conductivity (EC_a) data as a surrogate for soil texture differences in the reference strips. A sufficiency index (SI) calculated from radiometer measured canopy reflectance data (SI_sensor) and from SPAD chlorophyll meter data (SI_meter) at two growth stages during corn vegetative growth were used to assess N sufficiency within the N enriched reference strips. By ignoring soil spatial variability in the reference strips, corn in the sandier soils was designated N deficient. Accounting for soil spatial variability using NRCS soil mapping units improved N sufficiency designations of corn in the reference strip for the different soil types contained within the reference strip but tended to designate corn in lighter texture areas within a mapping unit as N deficient. Use of EC_a as a surrogate for soil texture typically performed best for classifying corn N sufficiency throughout the reference strip and is recommended as a method to obtain reference strip normalizing values in fields with spatially variable sandy soils.     

A floating sensing system to evaluate soil and crop variability within flooded paddy rice fields

Continuous paddy rice cultivation requires fields to be flooded most of the time limiting seriously the collection of detailed soil information. So far, no appropriate soil sensor technology for identifying soil variability of flooded fields has been reported. Therefore, the primary objective was the development of a sensing system that can float, acquire and process detailed geo-referenced soil information within flooded fields. An additional objective was to determine whether the collected apparent electrical conductivity (EC_a) information could be used to support soil management at a within-field level. A floating sensing system (FloSSy) was built to record EC_a using the electromagnetic induction sensor EM38, which does not require physical contact with the soil. Its feasibility was tested in an alluvial paddy field of 2.7 ha located in the Brahmaputra floodplain of Bangladesh. The high-resolution (1 × 1 m) EC_a data were classified into three classes using the fuzzy k-means classification method. The variation among the classes could be attributed to differences in subsoil (0.15–0.30 m below soil surface) bulk density, with the smallest EC_a values representing the lowest bulk density. This effect was attributed to differences in compaction of the plough pan due to differential puddling. There was also a significant difference in rice yield among the EC_a classes, with the smallest EC_a values representing the lowest yield. It was concluded that the floating sensing system allowed the collection of relevant soil information, opening potential for precision agriculture practices in flooded crop fields.     

Evaluation of a Geonics EM31-3RT probe to delineate hydrologic regimes in a tile-drained field

A world-wide need to use water resources efficiently necessitates more effective approaches to study water and contaminant transport in soil. This study examined the effectiveness of a multi-receiver electromagnetic induction probe (Geonics EM31-3RT) and modeling software (EMIGMA) to delineate hydrological regimes at field scale. The site consisted of 20 (15 m × 15 m) tile-drained plots in Southern Ontario, Canada. Measurements of apparent soil electrical conductivity (EC_a) and magnetic susceptibility were obtained using the EM31-3RT in each plot at four distances (0, 2.25, 4.5 and 7.5 m) from the tile drain, and on three occasions (August 22, 26 and 29) in 2003. The EMIGMA was used to simulate a depth profile of electrical conductivity (EC_s) from EM31-3RT readings. The near-surface soil showed significantly (p < 0.01) smaller EC_a values than at greater depth. The EC_a measurements made directly over the tile drains were smaller than those observed further away due to the presence of the drains. Cluster analysis indicated that the largest EC_a values were at the lower elevations of the site related to the redistribution of moisture from higher elevations. The effect of tile drains and rainfall events on EC_a was simulated well by EMIGMA, with smaller EC_s values above the drains compared to further away, and showing an increase in EC_s in the near-surface soil after rain. This study suggests that EM31-3RT measurements combined with EMIGMA simulation of electrical conductivity can provide valuable information on depth profiles of EC_a and water dynamics in soil.     

Apparent Electrical Conductivity,Soil Properties and Spatial Covariance in the U.S. Southern High Plains

Site-specific soil and crop management will require rapid low-cost sensors that can generate position-referenced data that measure important soil properties that impact crop yields. Apparent electrical conductivity (EC_a) is one such measure. Our main objective was to determine which commonly measured surface soil properties were related to EC_a at six sites in the Texas Southern High Plains, USA. We used the Veris 3100 and Geonics EM-38 EC mapping systems on 12 to 47 ha areas in six center-pivot irrigation sites. Soil samples were taken from 0–150 mm on a 0.1 to 0.8 ha grid and analyzed for routine nutrients and particle size distribution. At four of the six sites, shallow EC_a measured with the Veris 3100 (EC_a-sh) positively correlated to clay content. Clay content was negatively related with EC_a-sh at one site, possibly due to low bulk density of the shallow calcic horizon at that site. Other soil properties that were often correlated with EC_a included soil extractable Ca²⁺, Mg²⁺, Na⁺, CEC, silt and soluble salts. Extractable K⁺, NO₃^–, SO₄^–, Mehlich-3-P, and pH were not related to EC_a. Partial least squares regression (PLS) of seven soil properties explained an average of 61%, 51% and 37% of the variation in observed shallow EC_a-sh, deep EC_a with the Veris 3100 (EC_a-dp) and EC_a with the Geonics EM-38 (EC_a-em), respectively. Including nugget, range and sill parameters from a spherical semivariance model of the residuals from PLS regression improved the fit of mixed models in 15 of 18 cases. Apparent EC, therefore can provide useful information to land-users about key soil properties such as clay content and extractable Ca²⁺, but that spatial covariance in these relationships should not be ignored.     

干湿交替和模拟氮沉降对巴音布鲁克高寒湿地土壤CO2排放的影响

为探讨干湿交替和模拟氮沉降对高寒湿地土壤CO_2排放的规律,以新疆巴音布鲁克高寒湿地土壤为研究对象,通过室内模拟控制试验,研究水分变化下[100%、70%、50%、40%和25%WFPS(土壤充水孔隙度Water filling soil porosity)]氮添加N0(0 kg·hm~(-2)·a~(-1))、N10(10 kg·hm~(-2)·a~(-1))和N100(100 kg·hm~(-2)·a~(-1))处理对巴音布鲁克高寒湿地土壤CO_2排放的影响。研究结果表明:土壤CO_2排放速率及累积排放量随WFPS值及氮添加量的增大而增加。一个循环,土壤由干到湿的过程中,初期土壤CO_2排放速率最高,随后随着水分减少,土壤CO_2排放速率呈降低趋势;首次干湿循环土壤CO_2累积排放量最大。土壤TN、NO_3~--N、NH_4~+-N、SOC含量均随土壤水分和氮添加量的增加而增加,而土壤SON随土壤水分和氮添加量的增加而减少。水分与土壤CO_2排放速率呈极显著正相关,氮添加与CO_2排放亦呈正相关。除了土壤SON、SOC含量与土壤CO_2排放速率呈负相关关系外,土壤TN、NO_3~--N、NH_4~+-N与CO_2排放都呈现出正相关关系。     

测墒补灌和施氮对冬小麦产量及水分、氮素利用效率的影响

【目的】测墒补灌是近年来研究的一种小麦节水灌溉新技术。论文旨在探索测墒补灌与施氮对冬小麦生长的影响,为该区节水、节氮提供依据。【方法】采用漫灌的方式设置测墒补灌和施氮两因素田间试验,补灌设置4个处理,于冬小麦拔节期、开花期依据0-40 cm土层土壤质量含水量进行测墒补灌,补灌至土壤田间持水量的50%（W₁）、60%（W₂）、70%（W₃）、80%（W₄）。施氮设置4个处理,不施氮（N₀）、施纯氮180 kg·hm^-2（N₁₈₀）、240 kg·hm^-2（N₂₄₀）和300 kg·hm^-2（N₃₀₀）。在此处理下研究了测墒补灌和施氮对冬小麦产量及水分、氮素利用效率的影响。【结果】(1)各施氮处理下,补灌量的增加可增加冬小麦籽粒产量,当补灌量至土壤田间持水量的60%-80%范围内时,冬小麦籽粒的增产效应差异不显著。各补灌处理下,当施氮量超过240 kg·hm^-2时籽粒产量无显著性变化。本试验条件下当补灌至土壤田间持水量的60%,施氮量为240 kg·hm^-2时冬小麦籽粒产量达到最高,为8 104.6 kg·hm^-2。(2)增加施氮量和补灌量均可显著增加麦田总耗水量,但当施氮量超过240 kg·hm^-2时,施氮的提高效果不显著。补灌量的增加会显著增加麦田总耗水量,但当补灌至土壤田间持水量60%（W₂）、70%（W₃）时较补灌至80%（W₄）处理显著降低耗水量,说明有利于节约灌水而获得较高产量。(3)相同施氮处理下,补灌量的增加可显著提高冬小麦水分利用效率,当补灌量增至土壤田间持水量的60%时,冬小麦水分利用效率达到最大值,为14.7 kg·hm^-2·mm^-1。相同补灌处理下,增施氮肥可显著提高冬小麦水分利用效率,但施氮量不宜超过240 kg·hm^-2,否则将导致水分利用效率降低。(4)相同施氮处理下,应控制补灌量至土壤田间持水量的60%时冬小麦氮素干物质生产效率及氮素利用效率最高,为60.1 kg·kg^-1、22.4 kg·kg^-1。相同补灌处理下,施氮量应控制在240 kg·hm^-2时可获得较高的氮素干物质利用效率及冬小麦氮素利用效率最高,为63.9 kg·kg^-1、23.5 kg·kg^-1。【结论】本试验条件下当施氮量为240 kg·hm^-2、冬小麦拔节期、开花期补灌至土壤田间持水量的60%时冬小麦籽粒产量、水分利用效率、氮素干物质利用效率、氮素利用效率均最高,为最优的节水、节氮、高产组合,推荐其作为该区域适宜水、氮用量。     

Calibration of a capacitance probe for measurement and mapping of dry matter yield in Mediterranean pastures

The main objective of this study was to calibrate a commercial capacitance probe for measuring pasture dry matter yields under Mediterranean conditions. The standard method of assessing pasture biomass is based on cutting all the forage within a specified area and requires great effort and expense to collect enough samples to accurately represent a pasture. The field tests were carried out in 2007, 2008 and 2009 on different dates (phenological stages), and on five dairy farms, representing typical pastures in the region (grasses; legumes; and bio-diverse flora, mixture of grasses, legumes and others species). The linear regression techniques used in 2007 to relate the weight of the herbage (direct measurements) to the meter reading of capacitance (indirect measurements) led to high regression coefficients in grasses (R² = 0.90; P < 0.01) and heterogeneous botanical composition (R² = 0.87; P < 0.001) and moderate regression coefficient in legumes species (R² = 0.48; P < 0.05). The validation of the calibration equations in 2008 and 2009 in two sites showed RSME values of 130 kg ha⁻¹ in heterogeneous botanical composition and 456 kg ha⁻¹ in legumes. The results indicated that the capacitance probe together with a GPS receiver might support site-specific management of pastures which would be useful in large areas.