Assessing newly developed and published vegetation indices for estimating rice leaf nitrogen concentration with ground- and space-based hyperspectral reflectance

Non-destructive and quick assessment of leaf nitrogen (N) status is important for dynamic management of nitrogen nutrition and productivity forecast in crop production. This research was undertaken to make a systematic analysis on the quantitative relationship of leaf nitrogen concentrations (LNCs) to different hyperspectral vegetation indices with multiple field experiments under varied nitrogen rates and varied types in rice (Oryza sativa L.). The results showed that some published indices had good relations with LNC such as two-band indices, R₇₅₀/R₇₁₀ (ZM), Gitelson and Merzlyak index two (GM-2), R₇₃₅/R₇₂₀ (RI-1dB), R₇₃₈/R₇₂₀ (RI-2dB) and the normalized difference red edge index (NDRE), three-band indices, adjusted normalized index 705 (mND705), physiological reflectance index c (PRI_c), terrestrial chlorophyll index (MTCI), and red edge position derived with four point linear interpolation (REP_LI). Three-band indices performed better than two-band indices, with MTCI exhibiting the best logarithmic relation to LNC in rice. Then, hyper-spectral vegetation indices computed with random two bands (λ₁ and λ₂) from 400 to 2500 nm range were related to LNC of rice. The results indicated that two-band indices combined with bands of 550–600 nm and 500–550 nm in green region had good relationships with LNC, and simple ratio index SR(533,565) performed the best in all two-band indices, similar to the published three-band indices (mND705, PRI_c and MTCI). New three-band indices R₄₃₄/(R₄₉₆ + R₄₀₁) and R₇₀₅/(R₇₁₇ + R₄₉₁) were proposed for prediction of LNC with improved ability over the SR(533,565) and published spectral indices. Moreover, R₇₀₅/(R₇₁₇ + R₄₉₁) performed well in all the data from ground spectra, modeled AVIRIS and Hyperion spectra, and acquired Hyperion image hyperspectra. The R₄₃₄/(R₄₉₆ + R₄₀₁) also exhibited well in both ground and modeled AVIRIS and Hyperion image spectra, but could not be tested with the acquired Hyperion image because of the absence in radiometric calibration of the bands less than 416 nm. Overall, the newly developed three-band spectral index R₇₀₅/(R₇₁₇ + R₄₉₁) should be a good indicator of LNC at ground and space scales in rice. Yet, these new indices still need to be tested with more remote sensors based on ground, airborne and spaceborne, and verified widely in other ecological locations involving different cultivars and production systems.     

Measuring and predicting canopy nitrogen nutrition in wheat using a spectral index—The canopy chlorophyll content index (CCCI)

Varying the spatial distribution of applied nitrogen (N) fertilizer to match demand in crops has been shown to increase profits in Australia. Better matching the timing of N inputs to plant requirements has been shown to improve nitrogen use efficiency and crop yields and could reduce nitrous oxide emissions from broad acre grains. Farmers in the wheat production area of south eastern Australia are increasingly splitting N application with the second timing applied at stem elongation (Zadoks 30). Spectral indices have shown the ability to detect crop canopy N status but a robust method using a consistent calibration that functions across seasons has been lacking. One spectral index, the canopy chlorophyll content index (CCCI) designed to detect canopy N using three wavebands along the “red edge” of the spectrum was combined with the canopy nitrogen index (CNI), which was developed to normalize for crop biomass and correct for the N dilution effect of crop canopies. The CCCI–CNI index approach was applied to a 3-year study to develop a single calibration derived from a wheat crop sown in research plots near Horsham, Victoria, Australia. The index was able to predict canopy N (g m⁻²) from Zadoks 14–37 with an r² of 0.97 and RMSE of 0.65 g N m⁻² when dry weight biomass by area was also considered. We suggest that measures of N estimated from remote methods use N per unit area as the metric and that reference directly to canopy %N is not an appropriate method for estimating plant concentration without first accounting for the N dilution effect. This approach provides a link to crop development rather than creating a purely numerical relationship. The sole biophysical input, biomass, is challenging to quantify robustly via spectral methods. Combining remote sensing with crop modelling could provide a robust method for estimating biomass and therefore a method to estimate canopy N remotely. Future research will explore this and the use of active and passive sensor technologies for use in precision farming for targeted N management.     

基于优化光谱指数的新疆春小麦冠层叶绿素含量估算

为筛选可用于干旱半干旱区春小麦冠层叶绿素含量估算的高光谱植被指数,2017年通过测定春小麦关键生育时期冠层的田间高光谱与叶绿素含量,利用光谱指数波段优化算法分别计算400～1 300 nm光谱波段中不同波段两两组合的比值光谱指数(ration spectral index,RSI)、归一化光谱指数(normalized difference spectral index,NDSI)、叶绿素指数(chlorophyll index,CI)、简化光谱指数(CI/NDSI,NPDI),并将这些参数及其他17个不同高光谱植被指数分别与实测冠层叶绿素含量进行Pearson相关分析,通过变量重要性准则筛选最优光谱参数,使用偏最小二乘回归法建立冠层叶绿素含量的预测模型。结果表明:(1)RSIs、NDSIs、CIs和NPDIs与冠层叶绿素含量的相关性都优于前人研究中定义的17种高光谱植被指数,并且冠层叶绿素含量与NDSI(R_(849),R_(850))、RSI(R_(849),R_(850)),CI(R_(849),R_(850))和NPDI(R_(849),R_(850))表现出强相关性。(2)用此4个优化光谱指数分别建模时,以CI(R_(849),R_(850))、 CI(R_(539),R_(553))、 CI(R_(540),R_(553))、 CI(R_(536),R_(553))为自变量的X-3模型预测精度最高(r~2=0.74,RMSE=0.272 mg·g~(-1))。(3)结合4个优化光谱指数构建的组合模型预测精度,其r~2=0.83,RMSE=0.187 mg·g~(-1)。     

Spectral measurements of the total aerial N and biomass dry weight in maize using a quadrilateral-view optic

Heterogeneous crop stands require locally adapted nitrogen fertilizer application based on rapid and precise measurements of the local crop nitrogen status. In the present study, we validated a promising technique for the latter, namely a tractor-mounted field spectrometer with an oblique quadrilateral-view measuring optic, measuring solar radiation and canopy reflectance in four directions simultaneously. Dry matter yield (kg ha⁻¹), total N content (g N g⁻¹ dry matter) and total aerial N (aboveground N-uptake) (kg N ha⁻¹) in maize were determined in 10 m² calibration areas in 60 plots differing in their N treatment and seeding density three times in each of three years under field conditions. Results show that the sensor used can reliably determine total aerial N ranging from as little as 5 kg N to 150 kg N ha⁻¹ with R²-values ≥0.81 in 2002 and 2004, and with R²-values ranging from ≥0.57 to 0.84 in 2003. Dry matter yields from as low as 0.3–4.2 t ha⁻¹ could be determined with R²-values ranging from 0.67 to 0.91 in 2002 to 2004. The capacity to ascertain DM yield spectrally was drastically reduced in the higher yield range (>6 t ha⁻¹) probably due to decreased sensitivity of the spectral signal. N-contents were generally not well determined. Taken together there is a good potential to determine reliably differences in total aerial N or DM yield from the five leaf stages unfolded to the five node stage where typically nitrogen applications are carried out.     

Water and nitrogen balance of sweet sorghum (Sorghum bicolor moench (L.)) cv. Keller under semi-arid conditions

In the framework of the E.U. project Fair CT 96-1913 “Environmental studies on sweet and fibre sorghum, sustainable crops for biomass and energy”, a research has been carried out with the aim to study the water and nitrogen balance and determine the critical N dilution curve of sweet sorghum cv. Keller. A field experiment was performed, where three irrigation treatments (I₀ = dry control, I₅₀ = 50% ETm restoration, I₁₀₀ = 100% ETm restoration) and four nitrogen fertilization levels (N₀ = no nitrogen control, N₆₀ = 60 kg ha⁻¹, N₁₂₀ = 120 kg ha⁻¹; N₁₈₀ = 180 kg ha⁻¹) were studied. The final yield was significantly affected by the amount of water distributed but not by the nitrogen level. The treatments watered up to crop establishment (I₀) produced, in the average, 7.5 t ha⁻¹ of dry matter, against 21.1 and 27.1 t ha⁻¹ of I₅₀ and I₁₀₀, respectively. The crop determined a great reduction in nitrate concentration of soil water, irrespective of nitrogen supplied. The variation between N output and input (Δ) was negative in N₀, N₆₀ and N₁₂₀ and positive in N₁₈₀. The critical value of nitrogen uptake change in relation to the water availability. The amount of nitrogen supplied did not determine significant differences upon WUE. The crop seems to have a great potentiality in Mediterranean environment in terms of yield production.     

Estimating N status of winter wheat using a handheld spectrometer in the North China Plain

Excessive nitrogen (N) fertilizer application is very common in the North China Plain. Diagnosis of in-season N status in crops is critical for precision N management in this area. Remote sensing, as a timely and nondestructive tool, could be an alternative to traditional plant testing for diagnosing crop N status. The objectives of this study were to determine which vegetation indices could be used to estimate N status in winter wheat (Triticum aestivum L.) under high N input conditions, develop models to predict winter wheat N uptake using spectral vegetation indices and validate the models with data from farmers’ fields. An N rate experiment and a variety-N experiment were conducted in Huimin, Shandong Province from 2005/2006 to 2006/2007 to develop the models. Positive linear relationships between simple ratio vegetation indices (red vegetation index, RVI and green vegetation index, GVI) and N uptake were observed independent of growth stages and varieties (R², 0.48–0.74). In contrast, the relationships between normalized difference vegetation indices (NDVI and GNDVI), red and green normalized difference vegetation index (RGNDI), and red and green ratio vegetation index (RGVI) were exponentially related to N uptake (R², 0.43–0.79). Subsequently, 69 farmers’ fields in four different villages were selected as datasets to validate the developed models. The results indicated that the prediction using RVI had the highest coefficient of determination (R², 0.60), the lowest root mean square error (RMSE, 39.7 kg N ha⁻¹) and relative error (RE, 30.5%) across different years, varieties and growth stages. We conclude that RVI can be used to estimate nitrogen status for winter wheat in over-fertilized farmers’ fields before heading.     

Relationship between P and N concentrations in maize and wheat leaves

Simple plant-based diagnostic tools can be used to determine crop P status. Our objectives were to establish the relationships between P and N concentrations of the uppermost collared leaf (P_L and N_L) of spring wheat (Triticum aestivum L.) and maize (Zea mays L.) during the growing season and, in particular, to determine the critical leaf P concentrations required to diagnose P deficiencies. Various N applications were evaluated over six site-years for wheat and eight site-years for maize (2004-2006) with adequate soil P for growth. Phosphorus and N concentrations of the uppermost collared leaf were determined weekly and the relationships between leaf N and P concentrations were established using only the sampling dates from the stem elongation stage for wheat and from the V8 stage of development for maize. Leaf P concentration generally decreased with decreasing N fertilization. Relationships between P_L and N_L concentrations (mg g⁻¹ DM) using all site-years and sampling dates were described by significant linear-plateau functions in both maize (P_L = 0.82 + 0.089 N_L if N_L ≤ 32.1 and P_L = 3.7 if N_L > 32.1; R² = 0.41; P < 0.001) and wheat (P_L = 0.02 + 0.106 N_L if N_L ≤ 33.2 and P_L = 3.5 if N_L > 33.2; R² = 0.42; P < 0.001). Variation among sampling dates in the relationships were noted. By restricting the sampling dates [413-496 growing degree days (5 °C basis) in wheat (i.e., stem elongation) and 1494-1579 crop heat units in maize (i.e., silking), relationships for wheat (P_L = 0.29 + 0.073 N_L, R² = 0.66; P < 0.001) and maize (P_L = 1.04 + 0.084 N_L, R² = 0.66; P < 0.001) were improved. In maize, expressing P and N concentrations on a leaf area basis (P_LA and N_LA) at silking further improved the relationship (P_LA = 0.002 + 0.101 N_LA, R² = 0.80; P < 0.001). Predictive models of critical P concentration as a function of N concentration in the uppermost collared leaf of wheat and maize were established which could be used for diagnostic purposes.     

施氮对滴灌春小麦干物质、氮素积累和产量的影响

为给北疆地区滴灌春小麦生产中氮素管理提供依据,以新春6号为材料,设置5个施氮水平(施纯氮0、150、300、450和600 kg·hm-2,分别用N0、N1、N2、N3、N4表示),分析了施氮量对滴灌春小麦干物质、氮素积累和产量的影响.结果表明,滴灌春小麦植株干物质和氮素积累特征符合Logistic曲线,施氮能促进其干物质和氮素积累,以N2处理表现最佳,其干物质量和氮素积累量分别达到19 745.03和310.97kg·hm-2,比其他处理分别高4.42％～60.74％和3.68％～79.65％.滴灌春小麦产量和氮肥当季利用率受施氮量影响均显著,且均随施氮量的增加呈先增加后降低的趋势,其中产量以N2最大,比N0增产45.04％.经函数拟合,施氮量为366.83 kg·hm-2时,滴灌春小麦产量最高.     

Hyperspectral remote sensing of yellow mosaic severity and associated pigment losses in Vigna mungo using multinomial logistic regression models

Yellow mosaic disease (YMD) has been a serious threat to blackgram cultivation especially during post-monsoon season. Visual assessment of disease severity is qualitative and time consuming. Rapid and non-destructive estimation of YMD by hyperspectral remote sensing has not been attempted so far on any of its hosts. Field studies were conducted for two seasons with eight blackgram genotypes having differential response to YMD. Comparison of mean reflectance spectra of the healthy and YMD infested leaves showed changes in all the broad band regions. However, reflectance sensitivity analysis of the narrow-band hyperspectral data revealed a sharp increase in reflectance from the diseased leaves compare to healthy at 669 (red), 505 and 510 nm (blue). ANOVA showed a significant decrease in leaf chlorophyll (p < 0.0001) with increase in disease severity, while no such relationship was observed for relative water content. By plotting coefficients of determination (R²) between leaf chlorophyll and percent reflectance at one nm wavelength interval, two individual bands (R₅₇₁; R₇₀₅) and two band ratios (R₅₇₁/R₇₂₁; R₇₀₅/R₅₉₃) with highest R² values were selected. These bands showed a significant linear relationship with SPAD chlorophyll readings (R² range 0.781–0.814) and spectrometric estimates of total chlorophyll content (R² range 0.477–0.565). Further, the relationship was stronger for band ratios compared to single bands. With optimal spectral reflectance ratios as inputs, disease prediction models were built using multinomial logistic regression (MLR) technique. Based on model fit statistics, reflectance ratios R₅₇₁/R₇₂₁ and R₇₀₅/R₅₉₃ were found better than the individual bands R₅₇₁ and R₇₀₅. Validation of MLR models using an independent test data set showed that the overall percentage of correct classification of the plant into one of the diseased categories was essentially same for both the ratios (68.75%). However, the MLR model using R₇₀₅/R₅₉₃ as dependent variable was of greater accuracy as it gave lower values of standard errors for slopes (β_G range 9.79–36.73) and highly significant estimates of intercept and slope (p < 0.05). Thus the models developed in this study have potential use for rapid and non-destructive estimation of leaf chlorophyll and yellow mosaic disease severity in blackgram.     

Temporal dynamics of light and nitrogen vertical distributions in canopies of sunflower, kenaf and cynara

To enhance eco-physiological and modelling studies, we quantified vertical distributions of light and nitrogen in canopies of three Mediterranean bio-energy crops: sunflower (Helianthus annuus), kenaf (Hibiscus cannabinus) and cynara (Cynara cardunculus). Field crops were grown with and without water stress in 2008 and 2009. Canopy vertical distributions of leaf area index (LAI), photosynthetically active radiation (PAR), specific leaf area (SLA), nitrogen concentration (N_conc) and specific leaf nitrogen (SLN) were assessed over time for each crop × year × water input combination. Light and nitrogen distributions were quantified by the Beer's law (exponential model) and extinction coefficients for light (K_L) and nitrogen (K_N) were calculated. Within a year, K_L did not change significantly over the studied period in all irrigated crops, but differences in K_L were significant between years (sunflower: 0.74 vs. 0.89; kenaf: 0.62 vs. 0.71; cynara: 0.77). K_L estimates were always lower (−48 to −65%) in water-stressed sunflower and kenaf crops because of the reduction in leaf angle. These results should be taken into account, when simulating water-limited biomass production. Vertical SLN distributions were found in canopies when LAI was >1.5 (40 from 51 cases). These distributions were significantly correlated with the cumulative LAI from the top (r² = 0.75-0.81; P < 0.05), providing parameters to upscale photosynthesis from leaf to canopy levels. Vertical SLN distributions followed species-specific patterns over the crop cycle and varied less compared to PAR distributions between years. Lastly, we observed strong associations between SLN and PAR distributions in irrigated sunflower and kenaf canopies (r² > 0.66; P < 0.001). However, observed SLN distributions were less steep than the distributions that would maximize canopy photosynthesis.     

SPAD Values and Nitrogen Nutrition Index for the Evaluation of Rice Nitrogen Status

Abstract

Plant-based diagnosis is one of the most important methods to determine nitrogen (N) content of crops. Our objective was to establish the relationship between soil-plant analysis development (SPAD) values and N nutrition index (NNI) during the three developmental stages of rice and apply the SPAD meter as diagnostic tools for predicting grain yield response to N fertilization. We determined the SPAD values of four uppermost fully expanded leaves of two rice cultivars at six N fertilization levels at three growth stages and examined the relationship between SPAD values and NNI. The critical N concentration (N_c) was 5.31 W^–0.5 in Xiushui63, and 5.38 W^–0.49 in Hang43, where W is the total shoot biomass. The correlation between SPAD value and NNI varied with the leaf position, developmental stage, and variety. The lower leaf appeared to be more sensitive to the N level than the upper leaf in the response of biomass, and could be more suitable as a test sample for N status diagnosis, especially in the booting and heading stage. The dependence of grain yield on SPAD values of the fourth fully expanded leaf (L4) was significant at booting stage (R²_L4 = 0.82** in 2011, R²_L4 = 0.72** in 2012). Ratio of SPAD values of L4 to that in the N-saturated plot (RSPAD) (R²_L4 = 0.92** in 2011, R²_L4 = 0.77** in 2012) and NNI (R² = 0.96** in 2011, R² = 0.86** in 2012) at booting stage demonstrated a closer relationship with grain yield.     

施氮对稻茬冬小麦氮肥吸收利用及转运的影响

为推动稻茬冬小麦氮肥高效利用,采取15N微区试验,研究了施氮量(N₀、N_{120、N210、N300)对稻茬小麦氮素吸收、转运、产量和氮肥利用的影响。结果表明,增加施氮量能够显著提高成熟期植株对肥料氮和土壤氮的吸收量。小麦对基肥氮的吸收以越冬至拔节期最高,对追肥氮的吸收以拔节至开花期最高。植株对追肥氮的积累量均高于基肥氮,对土壤氮的积累量在N120 处理下高于肥料氮,在N210、N300 处理下则相反;N120、N210、N300 处理下植株中土壤氮积累量占总吸氮量的比例分别为57%、48%、45%。成熟期叶片、茎鞘、穗轴+颖壳和籽粒中的氮素分配比例分别为6.09%~9.70%、9.01%~11.14%、7.19%~7.48%、71.96%~ 77.42%。肥料氮对籽粒氮素的贡献率随施氮量增加而显著增加,N120、N210、N300 处理分别为45.78%、 56.22%、61.25%。植株中肥料氮的转运量、花后积累量和土壤氮的花后积累量均随施氮量增加而显著增加,而土壤氮的转运量则随施氮量的增加而下降。基肥氮、追肥氮、肥料氮和土壤氮的转运效率分别为 77.31%~79.96%、77.89%~81.80%、77.61%~81.13%、51.55%~67.64%。植株花后氮积累量对籽粒氮素的贡献率约为1/5,肥料氮和土壤氮花后积累量对籽粒中肥料氮和土壤氮的贡献率分别为9.59%~ 14.56% 和 24.11%~34.48%。施氮量超过210 kg·hm^-2 时产量增加不显著,N120、N210、N300 处理氮肥回收率分别为54.48%、48.15%、41.64%。}     

基于GF-6/WFV卫星遥感的大田冬小麦叶片氮素含量估测

为对大田冬小麦叶片氮素含量（LNC）进行快速、准确及无损监测,通过在江苏省泰州泰兴市、盐城大丰区和南通如皋市布设冬小麦遥感监测大田试验,在获取试验样点冬小麦冠层红光波段反射率（RED_ref）、近红外波段反射率（NIR_ref）和计算的十个光谱指数（RVI、NDVI、DVI、SAVI、OSAVI、MSR、RDVI、EVI2、NLI和SVI）基础上,将12个遥感光谱指标与冬小麦LNC进行相关分析,选出与LNC相关性较好的作为模型输入变量,构建基于BP神经网络的冬小麦LNC估测模型, 并利用GF-6/WFV卫星遥感影像对县域冬小麦LNC的空间分布开展监测。结果表明,12个遥感光谱指标与冬小麦LNC之间存在不同程度的相关性,其中NDVI、RVI、MSR、OSAVI和NLI与冬小麦LNC的相关性较好（相关系数不低于0.65）。将优选的5个遥感光谱指标作为模型输入变量,构建基于BP神经网络的冬小麦LNC估测模型（LNC-BPEM）,模型的估测精度r²=0.866,RMSE=0.246%,ARE=12.9%。将冬小麦LNC-BPEM估测模型和GF-6/WFV影像结合对县域冬小麦LNC的空间信息监测,获得了如皋县域冬小麦LNC的空间分布特征,该区域冬小麦LNC范围在0.9%~2.0%（长势正常）的种植面积为29 693.3 hm²,占冬小麦总种植面积的74%。这说明利用GF-6/WFV卫星的多个遥感光谱指标与神经网络结合建模可有效估测县域大田冬小麦叶片氮素含量。     

Biomass production and nitrogen accumulation and remobilisation by Miscanthus × giganteus as influenced by nitrogen stocks in belowground organs

The nitrogen (N) requirement of dedicated crops for bioenergy production is a particularly significant issue, since N fertilisers are energy-intensive to make and have environmental impacts on the local level (NO₃ leaching) and global level (N₂O gas emissions). Nitrogen nutrition of Miscanthus × giganteus aboveground organs is assumed to be dependent on N stocks in belowground organs, but the precise quantities involved are unknown. A kinetic study was carried out on the effect of harvest date (early harvest in October or late harvest in February) and nitrogen fertilisation (0 or 120 kg N ha⁻¹) on aboveground and belowground biomass production and N accumulation in established crops. Apparent N fluxes within the crop and their variability were also studied.Aboveground biomass varied between 24 and 28 t DM ha⁻¹ in early harvest treatments, and between 19 and 21 t DM ha⁻¹ in late harvest treatments. Nitrogen fertilisation had no effect on crop yield in late harvest treatments, but enhanced crop yield in early harvest treatments due to lower belowground biomass nitrogen content. Spring remobilisation, i.e. nitrogen flux from belowground to aboveground biomass, varied between 36 and 175 kg N ha⁻¹, due to the variability of initial belowground nitrogen stocks in the different treatments. Autumn remobilisation, i.e. nitrogen flux from aboveground to belowground organs, varied between 107 and 145 kg N ha⁻¹ in late harvest treatments, and between 39 and 93 kg N ha⁻¹ in early harvest treatments. Autumn remobilisation for a given harvest date was linked to aboveground nitrogen accumulation in the different treatments. Nitrogen accumulation in aboveground biomass was shown to be dependent firstly on initial belowground biomass nitrogen stocks and secondly on nitrogen uptake by the whole crop.The study demonstrated the key role of belowground nitrogen stocks on aboveground biomass nitrogen requirements. Early harvest depletes belowground nitrogen stocks and thus increases the need for nitrogen fertiliser.     

施氮量对新疆滴灌冬小麦根系生长及产量的影响

为探明滴灌冬小麦高产需氮肥规律,利用大田试验研究了N_0(0 kg·hm~(-2))、N_1(90kg·h~(-2))、N_2(180kg·h~(-2))、N_3(270kg·h~(-2))、N_4(360kg·h~(-2))施氮量对新冬18号0~60cm土层根系生长的影响及其与产量和氮肥利用率的关系。结果表明,随着施氮量的增加,拔节至成熟期间0~60cm土层根系干重、根长和根系活力均增加,N_3处理孕穗期小麦0~60cm土层根干重、根长分别较N_0处理增加11.93%、29.0%,增幅基本表现为0~20cm20~40cm40~60cm土层;N_3处理较N_0处理小麦产量增加30.35%,氮肥农学利用效率为6.90kg·kg-1。拔节期前后施适量氮肥可促进0~60cm土层根系生长和活力增强,是氮肥增产的重要原因。本试验条件下最适宜施氮量为180~270kg·h~(-2),可获得产量7 591.49~8 004.85kg·h~(-2),氮肥农学利用效率为6.90~8.06。     

Nitrogen uptake,fixation and response to fertilizer N in soybeans: A review

Although relationships among soybean (Glycine max [L.] Merr) seed yield, nitrogen (N) uptake, biological N₂ fixation (BNF), and response to N fertilization have received considerable coverage in the scientific literature, a comprehensive summary and interpretation of these interactions with specific emphasis on high yield environments is lacking. Six hundred and thirty-seven data sets (site–year–treatment combinations) were analyzed from field studies that had examined these variables and had been published in refereed journals from 1966 to 2006. A mean linear increase of 0.013 Mg soybean seed yield per kg increase in N accumulation in aboveground biomass was evident in these data. The lower (maximum N accumulation) and upper (maximum N dilution) boundaries for this relationship had slopes of 0.0064 and 0.0188 Mg grain kg⁻¹ N, respectively. On an average, 50–60% of soybean N demand was met by biological N₂ fixation. In most situations the amount of N fixed was not sufficient to replace N export from the field in harvested seed. The partial N balance (fixed N in aboveground biomass − N in seeds) was negative in 80% of all data sets, with a mean net soil N mining of −40 kg N ha⁻¹. However, when an average estimated belowground N contribution of 24% of total plant N was included, the average N balance was close to neutral (−4 kg N ha⁻¹). The gap between crop N uptake and N supplied by BNF tended to increase at higher seed yields for which the associated crop N demand is higher. Soybean yield was more likely to respond to N fertilization in high-yield (>4.5 Mg ha⁻¹) environments. A negative exponential relationship was observed between N fertilizer rate and N₂ fixation when N was applied on the surface or incorporated in the topmost soil layers. Deep placement of slow-release fertilizer below the nodulation zone, or late N applications during reproductive stages, may be promising alternatives for achieving a yield response to N fertilization in high-yielding environments. The results from many N fertilization studies are often confounded by insufficiently optimized BNF or other management factors that may have precluded achieving BNF-mediated yields near the yield potential ceiling. More studies will be needed to fully understand the extent to which the N requirements of soybean grown at potential yields levels can be met by optimizing BNF alone as opposed to supplementing BNF with applied N. Such optimization will require evaluating new inoculant technologies, greater temporal precision in crop and soil management, and most importantly, detailed measurements of the contributions of soil N, BNF, and the efficiency of fertilizer N uptake throughout the crop cycle. Such information is required to develop more reliable guidelines for managing both BNF and fertilizer N in high-yielding environments, and also to improve soybean simulation models.     

Drought tolerance and yield increase of soybean resulting from improved symbiotic N2 fixation

Drought is by far the most important environmental factor contributing to crop yield loss, especially in soybean [Glycine max (L.) Merr.] where symbiotic fixation of atmospheric nitrogen (N₂) is sensitive to even modest soil water deficits. Decline of N₂ fixation with soil drying causes yield reductions due to inadequate N for protein production, which is the critical seed product. In this paper, we present a combined physiological and breeding research effort to develop soybean lines that have diminished sensitivity of N₂ fixation to drought. A preliminary physiological screen was used to identify lines that potentially expressed N₂ fixation drought tolerance. One hundred progeny lines derived from a cross between Jackson, a cultivar proven to have N₂ fixation tolerance to drought, and KS4895, a high-yielding line, were tested in the screen. Seventeen lines were identified for subsequent yield trials in moderate- and low-yielding rainfed environments. Two lines, found to have higher yields than commercial checks in these environments were then tested in the greenhouse for their N₂ fixation activity in drying soil. Nitrogen fixation activity was found to persist at lower soil water contents than exhibited by the sensitive parent. These two soybean lines offer a genetic resource for increased yields under rainfed conditions as a result of decreased sensitivity of N₂ fixation to water deficit.     

施氮量对滴灌冬小麦茎部特征及其抗倒伏性的影响

为了研究施氮量对滴灌冬小麦茎部形态特征及其抗倒伏能力的影响,在2014-2015年冬小麦生长季,以新冬18号为试验材料,在大田滴灌条件下研究了300(N_1)、360(N_2)、420(N_3)和480(N_4)kg·hm~(-2)四个不同氮肥水平对冬小麦茎部形态特征、力学特征及抗倒伏性能的影响。结果表明,随着施氮量的增加,滴灌冬小麦的株高逐渐增高,重心高度升高,平均节间长度增长,单株鲜重增加,而基部节间直径减小,茎秆基部的机械强度及抗倒伏指数降低;随着生育进程的推进,冬小麦茎秆基部的机械强度及抗倒伏指数均呈降低的趋势。茎秆的机械强度和抗倒伏指数与株高、重心高度、单茎鲜重显著负相关,与基部节间直径呈显著正相关。N_2处理小麦倒伏率较低,产量最高,为6 315.76kg·hm~(-2),分别较N_1、N_3、N_4处理产量高4.72%、6.69%和13.59%。在本试验条件下,适当控制施氮量可以降低滴灌小麦倒伏率,增加产量。     

氮水运筹对苏北平原稻茬麦干物质积累、产量和氮肥利用的影响

为明确苏北平原稻茬麦的最优氮水运筹模式,以淮麦30为材料,在大田测土施肥条件下,设置0 kg·hm^-2（N₀）、180 kg·hm^-2（N₁）、270 kg·hm^-2（N₂）3个施氮量和生育期不灌水（W₀）、灌拔节水（W₁）、灌拔节水+孕穗水（W₂）3个灌水处理,研究小麦干物质积累与转运、产量形成和氮素吸收与利用对不同氮水运筹的响应。结果表明,小麦干物质积累量、转运量和转运效率,氮素积累量、转运量和转运效率,花后干物质贡献率及氮素贡献率均随施氮量和灌水次数的增加而增加,各处理均以N₂W₂效果最佳。氮肥和灌水次数的增加对小麦成穗数、穗粒数、千粒重和产量、氮素收获指数与氮素利用效率均有显著促进作用,以N₂W₂效果最佳。氮肥农学效率、氮肥表观利用率和氮肥偏生产力则随施氮量增加而降低,以N₁W₂效果最佳;在相同氮肥水平下,灌水处理的上述三个指标较不灌水处理高。对本试验条件下各测定指标,氮肥在氮水运筹中起主导作用,且氮肥和灌水有显著的互作效应。综上,在苏北平原稻茬麦区,施氮量180 kg·hm^-2结合浇灌拔节水和孕穗水（W₂）的氮水模式可在协调小麦干物质和氮素的积累、转运与分配、促进增产的同时,提高氮肥利用效率,从而实现节氮增产的目标。     

Analysis of hyperspectral reflectance data for monitoring growth and development of lesquerella

Seed oil from lesquerella (Lesquerella fendleri (Gray) Wats.) is currently being developed as a biorenewable petroleum substitute, but several issues related to crop management and breeding must be resolved before the crop will be commercially viable. Due particularly to the prominent yellow flowers exhibited by lesquerella canopies, remote sensing may be a useful tool for monitoring and managing the crop. In this study, we used a hand-held spectroradiometer to measure spectral reflectance over lesquerella canopies in 512 narrow wavebands from 268 to 1095 nm over two growing seasons at Maricopa, Arizona. Biomass samples were also regularly collected and processed to obtain aboveground dry weight, flower counts, and silique counts. Partial least squares regression was used to develop predictive models for estimating the three lesquerella biophysical variables from canopy spectral reflectance. For model fitting and model testing, the root mean squared prediction errors between measured and modeled aboveground dry weight, flower counts, and silique counts were 2.1 and 2.3 Mg ha⁻¹, 251 and 304 flowers, and 1018 and 1019 siliques, respectively. Analysis of partial least squares regression coefficients and loadings highlighted the most sensitive spectral wavebands for estimating each biophysical variable. For example, the flower count model heavily emphasized the reflectance of yellow light at 583 nm, and contrasted that with reflectance in the blue (483 nm) and at the red edge (721 nm). Because of the indeterminate nature of lesquerella flowering patterns, remote sensing methods that monitor flowering progression may aid management decisions related to the timing of irrigations, desiccant application, and crop harvest.