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.     

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.     

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.     

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).     

Development and validation of fuzzy logic inference to determine optimum rates of N for corn on the basis of field and crop features

A fuzzy inference system (FIS) was developed to generate recommendations for spatially variable applications of N fertilizer. Key soil and plant properties were identified based on experiments with rates ranging from 0 to 250 kg N ha⁻¹ conducted over three seasons (2005, 2006 and 2007) on fields with contrasting apparent soil electrical conductivity (EC_a), elevation (ELE) and slope (SLP) features. Mid-season growth was assessed from remotely sensed imagery at 1-m² resolution. Optimization of N rate by the FIS was defined against maximum corn growth in the weeks following in-season N application. The best mid-season growth was in areas of low EC_a, high ELE and low SLP. Under favourable soil conditions, maximum mid-season growth was obtained with low in-season N. Responses to N fertilizer application were better where soil conditions were naturally unfavourable to growth. The N sufficiency index (NSI) was used to judge plant N status just prior to in-season N application. Expert knowledge was formalized as a set of rules involving EC_a, ELE, SLP and NSI levels to deliver economically optimal N rates (EONRs). The resulting FIS was tested on an independent set of data (2008). A simulation revealed that using the FIS would have led to an average N saving of 41 kg N ha⁻¹ compared to the recommended uniform rate of 170 kg N ha⁻¹, without a loss of yield. The FIS therefore appears to be useful for incorporating expert knowledge into spatially variable N recommendations.     

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.     

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.     

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.     

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.     

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.     

Spring Wheat Response to Fertilizer Nitrogen Following a Sugar Beet Crop Varying in Canopy Color

Experiments were conducted in the Red River Valley (RRV) of Minnesota to determine the responses of hard red spring wheat (Triticum aerstivum L.) to fertilizer N after a sugar beet (Beta vulgaris L.) crop that varied spatially in canopy color and N content. A color aerial photograph was acquired of the sugar beet field just prior to root harvest, and six sites were selected that varied in sugar beet canopy color, three each of green and yellow canopy sites. The three green sugar beet canopies returned 369, 265, and 266 kg N ha^–1 to the soil while the three yellow sugar beet canopies returned 124, 71, and 73 kg N ha^–1 to the soil. Spring wheat response to fall-applied urea-N fertilizer (0, 45, 90, 135, and 180 kg N ha^–1) was determined the following year at each of the above antecedent canopy sites. Soil NO₃-N in the top 0.6 m of soil varied among the locations with a range of 35 to 407 kg NO₃-N ha^–1 at the green canopy sites and 12 to 23 kg NO₃-N ha^–1 at the yellow canopy sites. Application of fertilizer N according to traditional recommendation methods would have resulted in fertilizer applications at all three yellow canopy sites and two of the three green canopy sites. At the antecedent green sugar beet canopy sites, fertilizer N had little or no effect on spring wheat grain yields, grain N concentration, anthesis dry matter, and anthesis N content. In contrast, fertilizer N increased all four parameters at the antecedent yellow sugar beet canopy sites. The data indicate that fertilizer N management can be improved by using remote sensing to delineate management zones according to antecedent sugar beet canopy color.     

Can Landform Stratification Improve Our Understanding of Crop Yield Variability?

Farmers account for yield and soil variability to optimize their production under mainly economic considerations using the technology of precision farming. Therefore, understanding of the spatial variation of crop yield and crop yield development within arable fields is important for spatially variable management. Our aim was to classify landform units based on a digital elevation model, and to identify their impact on biomass development. Yield components were measured by harvesting spring barley (Hordeum vulgare, L.) in 1999, and winter rye (Secale cereale, L.) in 2000 and 2001, respectively, at 192 sampling points in a field in Saxony, Germany. The field was stratified into four landform units, i.e., shoulder, backslope, footslope and level. At each landform unit, a characteristic yield development could be observed. Spring barley grain yields were highest at the level positions with 6.7 t ha⁻¹ and approximately 0.15 t ha⁻¹ below that at shoulder and footslope positions in 1999. In 2000, winter rye harvest exhibited a reduction at backslope positions of around 0.2 t ha⁻¹ as compared to the highest yield obtained again at level positions with 11.1 t ha⁻¹. The distribution of winter rye grain yield across the different landforms was completely different in 2001 from that observed in 2000. Winter rye showed the highest yields at shoulder positions with 11.1 t ha⁻¹, followed by the level position with 0.5 t ha⁻¹ less grain yield. Different developments throughout the years were assumed to be due to soil water and meteorological conditions, as well as management history. Generally, crop yield differences of up to 0.7 t ha⁻¹ were found between landform elements with appropriate consideration of the respective seasonal weather conditions. Landform analysis proved to be helpful in explaining variation in grain yield within the field between different years.     

Growth and yield response of wheat (<Emphasis Type="Italic">Triticum aestivum</Emphasis> L.) to phosphobacterial inoculation

In this study growth and yield response of wheat crop to phosphobacterium inoculum was observed under sandy loam conditions. The investigations were carried out at field experiment. The experiment was laid out in Randomized Complete Block Design. The treatments were; 120-0-0 NPK kg/ha⁻¹ (T ₁), 120-50-0 kg/ha⁻¹ (T ₂), 120-100-0 NPK kg/ha⁻¹ (T ₃), T ₁ + Phosphobacterium inoculum (T ₄), T ₂ + Phosphobacterium inoculum (T ₅) and T ₃ + Phosphobacterium inoculum (T ₆).The results showed that bacterial strain (Pseudomonas spp.) was able to effect on yield and its attributes in wheat crop. The crop showed significant positive results. The inoculation significantly stimulates the germination count (m⁻²), number of tillers and spikes (m⁻²), 1000 grains weight (g) and grain yield (kg/ha⁻¹). We suggest that application of 120-100-0 kg/ha⁻¹ NPK along with coating of seed with phosphobacterium (Pseudomonas spp.) all the way through inoculation is a better practice to reduce the exploit of phosphatic fertilizers which are much costly.     

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.     

稳定氮肥用量对夏玉米产量和氮肥利用率的影响

通过大田小区试验,研究了稳定氮肥不同用量对夏玉米产量、养分累积量、氮肥利用效率及经济效益的影响。结果表明,与不施稳定氮肥相比,稳定氮肥施氮量90、150、210 kg·hm^-2和270 kg·hm^-2分别增产36.7%、62.1%、76.6%和81.9%,地上部氮素总累积量分别增加39.0%、60.3%、79.0%和113.4%,经济效益分别增加36.1%、61.2%、72.7%和77.1%;与农民习惯施用氮肥相比,高量稳定氮肥用量210 kg·hm^-2和270 kg·hm^-2分别增产7.3%和10.5%,地上部氮素总累积量分别增加3.2%和23.0%,经济效益分别增加9.7%和11.4%。施用稳定氮肥促进夏玉米对氮素的吸收累积,高量210 kg·hm^-2和270kg·hm^-2处理较习惯施氮提高总吸氮量。施用稳定氮肥各处理氮肥表观利用率和农学效率显著高于农民习惯施氮,偏生产力高于农民习惯施氮,生理效率除270 kg·hm^-2处理外,高于农民习惯施氮。稳定氮肥施氮量在210 kg·hm^-2时,能较好地协调玉米高产与稳定氮肥合理利用的统一。     

不同施氮水平和杂草清除时间对半湿润地区农田氮素利用及产量的影响

在半湿润地区中等肥力土垫旱耕人为土上进行田间试验,通过对冬小麦不同生育期杂草和作物样品的采集与分析,研究不同施肥及杂草处理对氮肥肥效的影响。结果表明:作物吸氮量随施氮量增加而增加,杂草吸氮量随吸氮量增加而降低;在不同杂草处理全生育期不清除杂草(A)、越冬前清除杂草(B)、返青期清除杂草(C)和拔节期清除杂草(D)的各个处理中,A、B、C和D杂草吸氮量分别占农田植物(作物 杂草)地上部分总吸氮量的1.98%、1.39%、3.99%和3.82%。籽粒产量随施氮量增加而增加,施氮量为135 kg N.hm-2时产量最高,达5 645.1 kg.hm-2,施氮量高于135 kg N.hm-2时,产量趋于稳定。氮肥利用率、氮肥利用效率、氮肥农学效率和氮肥生理效率均随施氮量增加而降低;从不同杂草处理看,以全生育期不清除杂草处理氮肥利用率最高,达到43.8%,返青期清除杂草处理氮肥利用率最低,为26.3%,二者间差异达显著水平;氮肥利用效率以越冬期清除杂草处理最高,为42.8 kg.kg-1N,全生育期不清除杂草处理最低,为40.6kg.kg-1N;氮肥生理效率以返青期清除杂草处理最高,为57.5 kg.kg-1N,显著高于其他杂草处理。综合氮效率及产量效率,小麦农田杂草处理时间应该相对较早,以越冬期和返青期清除杂草较好。     

应用于水稻生产的增效减负环保型施肥技术比对——以宁夏引黄灌区为例

过量施肥及盲目灌溉导致宁夏引黄灌区水稻种植中氮素淋失严重,氮肥利用率低下.探索能够在保障水稻产量前提下减少氮素淋失、提高氮素利用率的环保型施肥技术是该区域实现农业可持续发展的现实需求.本研究在前期研究的基础上,就不同施肥技术对灌区水稻生育期内氮素淋失、氮素利用率及水稻产量的影响效果进行比对,旨在为后续工作中技术筛选及推广提供依据.试验共设置4个处理,分别是(1)无肥对照(CK):不施氮肥;(2)常规施肥(FP):施用氮肥300 kg N·hm^-2, 60%作为基肥,分蘖和孕穗期各追肥20%;(3)侧条施肥(SD):施用水稻专用控释肥120 kg N·hm^-2,水稻插秧时将肥料一次性施入;(4)育苗箱全量施肥(NB):施用水稻专用控释肥,用量为120 kg N·hm^-2,育秧时一次性全量施入育秧盘.结果表明,采用SD和NB在氮素用量较FP降低60%的情况下,水稻产量都不会下降.SD可以显着降低稻田氮素淋溶损失,FP水稻生育期内可溶性总氮(TN)、硝态氮(NO₃-N)和铵态氮(NH₄⁺-N)淋失量分别为39.89、26.22 kg·hm^-2和5.49 kg·hm^-2,SD和FP相比,TN、NO₃-N和NH₄⁺-N的淋失量分别减少18.97、11.18 kg·hm^-2和2.27 kg·hm^-2;同时SD可以显着提高宁夏灌区水稻氮素利用率,较FP提高21.4%. NB和FP相比,TN、NO₃-N和NH₄⁺-N淋失量分别减少14.36、10.14 kg·hm^-2和1.84 kg·hm^-2,氮素利用率亦提高15.7%,但是TN、NO₃-N和NH₄⁺-N淋失量较SD处理分别增加4.61、1.04 kg·hm^-2和0.43 kg·hm^-2,同时氮素利用率亦减少5.7%.综合考虑水稻产量和环境效益,SD更适合在宁夏灌区水稻种植中推广应用.     

氮肥施用对四川紫色土矿质态氮淋失特征及春玉米产量的影响

为探究不同施氮量下春玉米季土壤矿质态氮淋失特征及产量变化,以春玉米为研究对象,设置不同施氮量(0、90、180、270、360 kg·hm-2,分别用N0、N90、N180、N270、N360表示),采用地下淋溶原位监测的方法,测定了玉米生育期间的土壤氮素淋失动态、玉米产量及氮肥利用率.结果 表明:硝态氮(NO-3-N)是春玉米季旱地土壤矿质态氮淋失的主要形态,占总淋失量的90％～91％;施用基肥和苗期追肥后1～3周出现氮素淋失高峰,是防控氮素淋失的关键时期;随施氮量增加,矿质态氮淋失量呈指数上升趋势,表现为N360(70.46 kg·hm-2)>N270(39.65 kg·hm-2)>N180(26.33 kg·hm-2)>N90(18.55 kg·hm-2)>N0(6.54 kg·hm-2),各处理间差异达显著水平(P<0.05).氮肥表观淋失率随施氮量增加呈先降后升趋势,在N180处理下,淋失率最低,为10.99％,较N270、N360处理分别降低1.27、6.76个百分点;玉米籽粒产量先随施氮量增加而显著提高(P<0.05),施氮超过180 kg·hm-2后进入平台期,N180处理下氮肥表观利用率达到最高,较其他处理增加14.50～27.75个百分点.总体来看,该研究区域春玉米的最佳施氮量为180 kg·hm-2,既能稳产也能保肥,同时土壤的氮素淋失率最低.     

关中夏玉米区陕单308高产栽培技术研究

采用二次饱和D-最优设计,以关中夏玉米区对陕单308产量影响最主要的密度及氮、磷肥施用量为试验因子,建立了陕单308产量回归模型;分析了产量的主效因子及各因子对产量的效应。结果表明,陕单308在关中夏玉米区有着严格的留苗密度区间,一般留苗50784~56250株/hm2。氮肥不但是产量的主效因子,而且分别与密度、磷肥交互作用密切,足量的氮肥(N 343.3 kg/hm2)与适量的密度(50784~59859株/hm2)互作能够产生较大的增产效果。氮磷搭配施用有利于增加粒重提高产量;提出了目标产量分别为7500~8249 kg/hm2和8250~9000 kg/hm2的高产栽培最佳农艺技术措施。     

Comparison of passive and active canopy sensors for the estimation of vine biomass production

Recent advances in optical designs and electronic circuits have allowed the transition from passive to active proximal sensors. Instead of relying on the reflectance of natural sunlight, the active sensors measure the reflectance of modulated light from the crop and so they can operate under all lighting conditions. This study compared the potential of active and passive canopy sensors for predicting biomass production in 25–32 randomly selected positions of a Merlot vineyard. Both sensors provided estimates of the normalized difference vegetation index (NDVI) from a nadir view of the canopy at veraison that were good predictors of pruning weight. Although the red NDVI of the passive sensors explained more of the variation in biomass (R ² = 0.82), its relationship to pruning weight was nonlinear and was best described by a quadratic regression (NDVI = 0.55 + 0.50 wt−0.21 wt²). The theoretically greater linearity of the amber NDVI-biomass relationship could not be verified under conditions of high biomass. The linear correlation to stable isotope content in leaves (¹³C and ¹⁵N) provided evidence that canopy reflectance detected plant stresses as a result of water shortage and limited fertilizer N uptake. Thus, the canopy reflectance data provided by these mobile sensors can be used to improve site-specific management practices of vineyards.