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.     

冬小麦返青期主要生长指标的HJ-1A/1B遥感影像监测

为进一步深化作物长势遥感监测机理与方法,给大田管理及时提供信息与技术,结合2011-2013年定点观测试验,以HJ-1A/1B数据为遥感影像源,研究了返青期冬小麦主要生长指标、籽粒品质参数和产量间及其与遥感变量间的定量关系,分别构建及评价基于HJ-1A/1B影像遥感变量的返青期叶面积指数、生物量、SPAD值和叶片含氮量监测模型。结果表明,返青期,归一化植被指数（NDVI）、比值植被指数（RVI）、蓝光波段反射率（B₁）和RVI可分别作为监测冬小麦叶面积指数、生物量、SPAD和叶片含氮量的敏感遥感变量,所构建的遥感监测模型可靠且精度较高,模型的决定系数（R²）分别为0.62、0.56、0.46和0.58,均方根误差（RMSE）分别为0.42、452.3 kg·hm^-2、4.39和0.54%。同时,对冬小麦不同等级主要生长指标进行遥感监测并制图,量化表达了主要生长指标区域空间分布。     

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.     

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.     

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.     

基于多源遥感数据和机器学习算法的冬小麦产量预测研究

为探讨基于多源遥感数据和机器学习算法预测冬小麦产量的可行性,利用中麦175/轮选987重组自交系F₇代群体中70个家系开展田间试验,通过无人机遥感平台和地面表型车平台及手持式冠层鉴定平台,获取冬小麦灌浆期光谱数据,分别用4种机器学习方法和集成方法建立产量预测模型。结果表明,在61个光谱指数中,除MCARI、DSI、PVI外,其余指数均与产量显著相关或极显著相关,700 nm和800 nm组合的高光谱指数能够比较准确地预测产量。相对于高光谱和多光谱,RGB传感器预测产量精度最高,平均决定系数(r²)为0.74,平均均方根误差(RMSE)为517.78 kg·hm^-2。相对于决策树(DT)、随机森林(RF)、支持向量机(SVM)三种传统机器学习算法,岭回归(RR)算法预测产量的精度最高,平均r²为0.73,平均RMSE为516.1 kg·hm^-2。与单一的传统机器学习算法相比,DT、RF、SVM、RR结合集成算法的预测精度高且稳定,r²高达0.77,RMSE也...     

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.     

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%。}     

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.     

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.     

Estimating Rice Leaf Greenness (SPAD) Using Fixed-Point Continuous Observations of Visible Red and Near Infrared Narrow-Band Digital Images

Abstract

A narrow-band dual camera system demonstrated a new close-range sensing technique to seasonally track trends in leaf greenness in rice paddies. A weatherproof digital imaging system for the visible red (RED, 620?650 nm) and near infrared band (NIR, 820?900 nm) was positioned 12 m above a 600-m² rice field. During the 2009 and 2010 paddyrice seasons, the system automatically logged images at 10-min intervals throughout the day. Radiometric corrections for the images utilized solar irradiance sensors and prior calibration to calculate 0900-1500 JST daily-averaged reflectance factors (DARF). The DARF in RED (DARF-RED) and NIR (DARF-NIR) values were transformed to provide a daily-averaged normalizeddifference vegetation index (DA-NDVI). The DA-NDVI increased more rapidly in the vegetative growth period, and reached an asymptotic plateau earlier than the DARF-NIR. From transplanting to harvest, leaf greenness values (measured by the SPAD index) were measured for the central part of the uppermost leaves of targeted canopies weekly with a chlorophyll meter. We developed a leaf greenness index (LGI), the ratio of DA-NDVI to DARF-NIR, and a simple calculation method for area means to reduce the background effect. The modified area means of LGI followed the seasonal trend in SPAD value well; its patternwas inherently different from the patterns of any of the original three parameters: DARF-RED, DARF-NIR or DA-NDVI. Throughout the paddy seasons in the two years, a regression equation for estimating SPAD values using the LGI, daily solar radiation, the cosine of angle between the view and the meridian directions and the cosine of culmination solar zenith angle performed favorably (R²=0.815). The nitrogen concentration per dry plant hill (g kg-¹) had a close relation to the SPAD values estimated using the equation.     

施氮量对强筋小麦物质积累与籽粒产量的影响

为探究冀东地区强筋小麦适宜施氮量,选用2个强筋小麦品种津农7号(氮高效型)和中麦998(氮低效型)为试验材料,设置0 kg·hm^-2(N₀)、180 kg·hm^-2(N₁)、210 kg·hm^-2(N₂)和240 kg·hm^-2(N₃)4个施氮量处理,研究施氮量对强筋小麦籽粒产量和干物质与氮素积累转运的影响。结果表明,在N₀～N₂处理范围内,2个强筋小麦品种的籽粒产量、花前干物质转运量和氮素转运量随施肥量增加均显著增加,N₃处理下2品种的籽粒产量和花前氮素转运量较N₂处理无显著变化,说明适量施氮可促进强筋小麦氮素转运与籽粒产量的提高。增加施氮量可促进花前干物质向籽粒的转运,津农7号的干物质转运率高于中麦998,2个品种的花后干物质对籽粒的贡献率为60.59%～77.16%,说明小麦籽粒产量主要来源于花后干物质积累。2个品种开花...     

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.     

Al toxicity effects on radiation interception and radiation use efficiency of Al-tolerant and Al-sensitive wheat cultivars under field conditions

Soil acidity and Al toxicity are highly extended in agricultural lands of Chile, especially where wheat is widely sown. To evaluate quantitatively the response of wheat biomass and its physiological determinants (intercepted radiation and radiation use efficiency) to Al toxicity, two field experiments were conducted in an Andisol in Valdivia (39°47′S, 73°14′W), Chile, during the 2005–2006 and 2006–2007 growing seasons. Treatments consisted of a factorial arrangement of: (i) two spring wheat cultivars with different sensitivity to Al toxicity (the sensitive cultivar: Domo.INIA and the tolerant cultivar: Dalcahue.INIA) and (ii) five exchangeable Al levels (from 0 to 2.7 cmol₍₊₎ kg⁻¹) with three replicates. Crop phenology and intercepted radiation (IR) were registered during the entire crop cycle, while 10 samples of above-ground biomass were taken at different stages between double ridge and maturity. Both biomass and leaf area index (LAI) were recorded in these 10 stages. Radiation use efficiency (RUE) was calculated as the slope of the relationship between accumulated above-ground biomass and accumulated photosynthetically active radiation intercepted by the canopy (IPARa). Crop phenology was little affected by soil Al treatments, showing only up to 17 days delay in the Al-sensitive cultivar under extreme Al treatments. Above-ground biomass at harvest was closely associated (R² = 0.92) with the crop growth rate but no relationship (R² = 0.14) was found between the crop cycle length. IPARa explained almost completely (R² = 0.93) the above-ground biomass reached by the crop at harvest under the wide range of soil Al concentrations explored in both experiments. On the other hand, a weaker relationship was found between above-ground biomass and RUE. The effect of soil Al concentration on IPARa was mainly explained by LAI as a single relationship (R² = 0.93) between IR (%) and LAI at maximum radiation interception showing a common light attenuation coefficient (k = 0.33).