稻麦复种模式下氮肥与稻秸互作对小麦产量和N_(2)O排放影响及推荐施肥研究

优化氮肥施用和秸秆还田技术为途径的农业管理措施被认为是提升农业可持续性的有效手段,然而当前关于氮肥和秸秆还田对小麦产量和N_(2)O排放影响的研究仍十分有限。为此,本研究基于2000—2022年发表的关于长江中下游流域氮肥和秸秆投入下小麦产量和N_(2)O排放变化的文献,运用随机森林建模,定量分析氮肥和秸秆还田对小麦产量和N_(2)O排放的影响,并结合情景设置进行了特定地点的小麦产量和N_(2)O排放模拟,同时评估了碳排放强度(CEE)和净生态系统经济效益(NEEB)。结果表明,建立的区域尺度小麦产量与N_(2)O排放对氮秸互作响应的随机森林模型,验证结果R^(2)分别为0.66和0.65,RMSE分别为0.70和1.11。结果表明施氮量和土壤有机质是影响小麦产量和N_(2)O排放的重要因素。综合来看,达到最大产量所需的氮肥量为208~212 kg hm^(-2),达到最小CEE所需的氮肥量为113~130 kg hm^(-2),达到最高的NEEB所需的氮肥量为202~205 kg hm^(-2),其中在6.75 t hm^(-2)的秸秆投入下施用202 kg hm^(-2)的氮肥可以获得最高的生态收益1.37万元。优化氮肥和秸秆投入具备减少作物碳排放强度并获得最大净生态环境效益的潜力。

二向反射和方向半球反射光谱差异及其对小麦叶片叶绿素含量反演的影响

二向反射率因子(bidirectional reflectance factor,BRF)和方向半球反射率因子(directional-hemispherical reflectance factor,DHRF)是反射光谱的两种形式,但在生化参数监测过程中,多数研究忽略了BRF和DHRF光谱的差异及其对叶片叶绿素含量(leaf chlorophyll content,LCC)反演的影响。本研究以不同品种、密度及氮素处理的小麦田间小区试验为基础,在叶片尺度获取了BRF和DHRF光谱,并计算相应的植被指数和小波系数,建立了基于植被指数和小波系数的LCC监测模型,定量分析BRF和DHRF光谱、植被指数和小波系数的差异及其对LCC反演的影响。结果表明,1)BRF和DHRF随LCC变化趋势一致,但两种光谱存在显著差异,且BRF光谱值高于DHRF光谱值;2)在一定程度上,应用植被指数和小波系数均可消除BRF和DHRF光谱差异的影响,其中归一化红边植被指数(normalized differential red edge vegetation index,NDRE)和红边叶绿素指数(red edge chlorophyll index,C_(Ired-edge))可以消除BRF和DHRF光谱差异的影响(R^(2)=0.930),但小波系数的性能要优于植被指数(R^(2)=0.995);3)基于DHRF光谱的植被指数和小波系数对LCC的估测能力优于BRF光谱,所有植被指数中NDRE反演效果最好(DHRF:R^(2)=0.957;BRF:R^(2)=0.938;All:R^(2)=0.892),第4尺度765 nm处的小波系数WF(4,675)反演LCC的效果优于NDRE(DHRF:R^(2)=0.985;BRF:R^(2)=0.971;All:R^(2)=0.973),且WF(4,675)消除BRF和DHRF光谱差异对LCC反演的影响能力强于NDRE(WF(4,675):R^(2)=0.973;NDRE:R^(2)=0.892)。综上所述,BRF和DHRF光谱存在差异,且这种差异不能直接忽略。研究明确了BRF和DHRF光谱的差异,为构建基于BRF和DHRF光谱的统一模型及提升冠层尺度LCC精确反演提供理论基础。

“语用型课堂”教学内容的研制和编排

语文教学要重视教学内容的研制,因为教学内容是教学目标的载体,每一项教学目标的达成都是通过对一定教学内容的学习来实现的。“语用型课堂”是指以语言为中介,以言语为对象,引导学生结合具体语境,探讨言和意的内在关系以及生成、转换的过程和规律,并通过具体语境中丰富的言语实践活动,促进学生言语智慧发展的语文课堂教学。

统编教材落实语文要素谨防“五化”

统编教材以语文要素与人文主题双线并行的方式编排单元,为一线教师准确把握单元教学重点、落实语用教学提供了凭借和参照。但在落实语文要素的过程中出现了方法简单化、讲解概念化、推进碎片化、巩固知识化、发展平面化等现象。防范这些现象须注重语文要素落实过程的方法分解、语境融合,强化整体实践和迁移应用,并形成层递发展,才能使语文要素更好地落地,促进学生语文素养的真正提升。

不同产量水平稻茬小麦氮素需求特征研究

明确长江中下游地区不同产量水平稻茬小麦氮素需求特征,可为小麦施肥管理提供理论依据。本研究通过在江苏开展的多年多点不同品种、氮肥水平以及播期播量的小麦试验,构建不同产量水平的实测数据集,分析不同产量水平下单位籽粒需氮量、干物质积累量、植株氮积累量、氮浓度(植株氮浓度、秸秆氮浓度、籽粒氮浓度)、收获指数、氮收获指数和氮营养指数的变化规律。结果表明,不同产量水平下单位籽粒需氮量无显著差异,中低产的单位籽粒需氮量最高,其值为27.8 kg t–1;低产水平最低,其值为24.8 kg t–1。随着产量水平的提高,成熟期干物质积累量、植株氮积累量、植株氮浓度均呈上升趋势,不同产量水平间差异显著。小麦产量与植株氮积累量呈显著正相关,播种期—拔节期、拔节期—开花期和开花期—成熟期的干物质积累量和氮积累量均随着产量的提高而提高,但不同生育阶段的植株干物质积累和氮积累占比呈现不同变化趋势。秸秆和籽粒氮浓度均随产量水平的提高而提高,高产水平下的秸秆氮浓度与中产无显著差异,但显著高于中低产和低产水平;而对于籽粒氮浓度,除中产和中低产水平外均存在显著差异。收获指数随产量水平的提高而逐渐提高,其变化范围为0.39~0.49,其中低产和中低产显著低于中产和高产;而不同产量水平间氮收获指数无显著差异,其变化范围为0.60~0.96。氮营养指数随着产量水平的提高逐渐提高,且在不同产量水平间差异显著,高产水平的氮营养指数较高,部分值大于1,表明有的试验氮肥供应过量。随着产量水平的提高,单位籽粒需氮量呈现先增加后下降趋势,而干物质积累量、植株氮积累量、植株氮浓度、秸秆氮浓度和籽粒氮浓度均逐渐提高,其中秸秆氮浓度增幅高于籽粒氮浓度,田间施肥应注意避免小麦对氮素的奢侈吸收。收获指数和氮收获指数的变化范围与前人研究一致,生长后期较高的干物质积累量和植株氮积累量是小麦获得高产的主要原因,利用氮营养指数可以对小麦田间氮肥管理起到较好的指导作用。

不同产量水平下稻茬小麦的氮素营养指标特征

【目的】明确长江中下游地区不同产量水平稻茬小麦氮营养指标变化规律,为小麦氮素营养状况实时诊断提供理论依据。【方法】本研究通过江苏省多年多点田间不同氮肥、播期、密度和品种试验,构建不同产量水平小麦大数据,分析不同产量水平小麦在不同生育时期的干物质积累量、植株氮积累量和植株氮浓度的变化规律,并通过计算小麦临界氮浓度,得到累积氮亏缺和氮营养指数的动态变化规律,进而明确高产稻茬小麦氮素营养指标特征。【结果】干物质积累量和植株氮积累量的变化趋势一致,随着小麦生育进程的推进均逐渐增加,植株氮浓度逐渐减小,累积氮亏缺和氮营养指数会出现波动。整个生育期内,干物质积累量和植株氮积累量在高产小麦和中产小麦之间的差异不显著,但二者植株氮积累量均显著高于中低产小麦,中低产小麦又显著高于低产小麦。在抽穗期、开花期和灌浆期,高产和中产小麦干物质积累量显著高于中低产小麦,中低产小麦又显著高于低产小麦。依据累积氮亏缺值判断氮素营养状况,高产和中产小麦的累积氮亏缺变化趋势一致,在起身—孕穗期,高产小麦的累积氮亏缺值由0.3 kg/hm^2降低为-23.0 kg/hm^2,中产小麦由7.0 kg/hm^2降低为-14.6kg/hm^2,孕穗—抽穗期又呈升高趋势,高产小麦由-23.0 kg/hm^2升高为-11.4 kg/hm^2,中产小麦由-14.6 kg/hm^2升高为2.4 kg/hm^2,开花—灌浆期的波动较小。表明高产小麦氮营养除起身期之外均为过剩,中产小麦在拔节—孕穗期的累积氮亏缺小于0,其余时期累积氮亏缺均大于0,但该水平的累积氮亏缺值一直在适宜范围内波动。中低产小麦在起身—拔节期,累积氮亏缺值由14.2 kg/hm^2降低为9.5 kg/hm^2,之后逐渐升高,灌浆期达到最大为43.9 kg/hm^2;低产小麦在起身期到灌浆期,累积氮亏缺值由17.3 kg/hm^2升高为71.1 kg/hm^2。表明中低产和低产的小麦氮营养水平在整个生育期内逐渐降低,且整个生育期均处于亏缺状态(累积氮亏缺值>0)。在拔节期、孕穗期、抽穗期和灌浆期,高产水平的小麦植株实际氮浓度高于植株临界氮浓度,中产小麦在孕穗期的植株实际氮浓度高于临界氮浓度,而中低产和低产的小麦在整个生育期植株实际氮浓度低于植株临界氮浓度。高产和中产的小麦氮营养指数在1附近波动,其中高产小麦的氮营养指数在起身—孕穗期由0.9升高为1.1,在抽穗—灌浆期,氮营养指数呈现先降低后升高趋势,其值分别为1.0、0.9和1.0,中产小麦与高产小麦的变化趋势一致,起身—孕穗期的氮营养指数由0.8升高为1.0,之后逐渐下降,其值均小于1,抽穗—灌浆期分别为0.9、0.9和0.9。中低产和低产的小麦氮营养指数始终低于1,中低产小麦在起身—拔节期氮营养指数由0.7升高为0.8,之后则逐渐下降,低产小麦从起身—开花期均逐渐下降,而这两个产量水平的氮营养指数在灌浆期会呈现略微上升趋势。【结论】随着产量水平的提高,小麦植株干物质和氮积累量、植株氮浓度、氮营养指数等都相应增加,累积氮亏缺相应下降。较高的干物质积累量和植株氮积累量是提高小麦产量的主要原因,在小麦生长过程中氮营养指数和累积氮亏缺均能准确诊断小麦氮营养状况,可为小麦氮肥精准管理提供理论支持。

播期播量及施氮量对冬小麦生长及光谱指标的影响

为阐明播期、播量及施氮量对冬小麦生长与光谱指标的影响规律,本研究通过开展连续两年不同播期、播量及施氮量的冬小麦田间试验,系统地研究了三因素及其互作对冬小麦产量、关键生育时期叶面积指数(leaf area index,LAI)和归一化红边指数(normalized difference red edge,NDRE)的影响,并进一步分析了三因素对冬小麦冠层NDRE时序曲线的影响。另一方面建立了不同产量水平下冬小麦冠层NDRE适宜时序曲线,以便于实时监测不同产量水平下冬小麦长势动态。结果表明,冬小麦冠层NDRE与LAI随关键生育期的变化相似,且三因素对关键生育时期2个指标的影响规律基本一致。2018—2019年冬小麦产量、不同生育时期LAI和冠层NDRE均随播期推迟而下降;2019—2020年除灌浆期外,晚播冬小麦产量、LAI及冠层NDRE峰值最大。2年冬小麦不同生育时期LAI、冠层NDRE随施氮量增加而增加;而不同播量间无明显差异。三因素中播期、施氮量对冬小麦冠层NDRE时序曲线有显著影响。冬小麦冠层NDRE时序曲线随施氮量增加被纵向拉长;曲线下降部分随播期推迟向左平移,同时2018—2019年随播期推迟曲线峰值下降,2019—2020年晚播、过晚播冬小麦曲线峰值高于适播期冬小麦。将2个年份数据融合在一起建立了3个产量水平下冬小麦冠层NDRE适宜时序曲线(产量水平分别为:小于6.75、6.75~8.25、大于8.25 t hm^(-2));发现随产量水平升高,NDRE时序曲线峰值及幅宽均增大。综上所述,冬小麦应适期早播,但若冬前积温较高,应适当推迟播期;且可通过增加一定播量和施氮量来改善晚播冬小麦群体长势。研究结果可为不同播期及不同产量水平下冬小麦长势监测提供技术支撑。

Long-Term Effects of Manure and Inorganic Fertilizers on Yield and Soil Fertility for a Winter Wheat-Maize System in Jiangsu, China

Winter wheat-maize rotations are dominant cropping systems on the North China Plain, where recently the use of organic manure with grain crops has almost disappeared. This could reduce soil fertility and crop productivity in the long run. A 20-year field experiment was conducted to 1) assess the effect of inorganic and organic nutrient sources on yield and yield trends of both winter wheat and maize, 2) monitor the changes in soil organic matter content under continuous wheat-maize cropping with different soil fertility management schemes, and 3) identify reasons for yield trends observed in Xuzhou City, Jiangsu Province, over a 20-year period. There were eight treatments applied to both wheat and maize seasons: a control treatment (C); three inorganic fertilizers, that is, nitrogen (N), nitrogen and phosphorus (NP), and nitrogen, phosphorus and potassium (NPK); and addition of farmyard manure (FYM) to these four treatments, that is, M, MN, MNP, and MNPK. At the end of the experiment the MN, MNP, and MNPK treatments had the highest yields, about 7 t wheat ha-1 and 7.5 t maize ha-1, with each about 1 t ha-1 more than the NPK treatments. Over 20 years with FYM soil organic matter increased by 80% compared to only 10% with NPK, which explained yield increases. However, from an environmental and agronomic perspective, manure application was not a superior strategy to NPK fertilizers. If manure was to be applied, though, it would be best applied to the wheat crop, which showed a better response than maize.

Postponed and reduced basal nitrogen application improves nitrogen use efficiency and plant growth of winter wheat

Excessive nitrogen(N) fertilization with a high basal N ratio in wheat can result in lower N use efficiency(NUE) and has led to environmental problems in the Yangtze River Basin, China. However, wheat requires less N fertilizer at seedling growth stage, and its basal N fertilizer utilization efficiency is relatively low; therefore, reducing the N application rate at the seedling stage and postponing the N fertilization period may be effective for reducing N application and increasing wheat yield and NUE. A 4-year field experiment was conducted with two cultivars under four N rates(240 kg N ha–1(N240), 180 kg N ha–1(N180), 150 kg N ha–1(N150), and 0 kg N ha–1(N0)) and three basal N application stages(seeding(L0), fourleaf stage(L4), and six-leaf stage(L6)) to investigate the effects of reducing the basal N application rate and postponing the basal N fertilization period on grain yield, NUE, and N balance in a soil-wheat system. There was no significant difference in grain yield between the N180 L4 and N240 L0(control) treatments, and the maximum N recovery efficiency and N agronomy efficiency were observed in the N180 L4 treatment. Grain yield and NUE were the highest in the L4 treatment. The leaf area index, flag leaf photosynthesis rate, flag leaf nitrate reductase and glutamine synthase activities, dry matter accumulation, and N uptake post-jointing under N180 L4 did not differ significantly from those under N240 L0. Reduced N application decreased the inorganic N content in the 0–60-cm soil layer, and the inorganic N content of the L6 treatment was higher than those of the L0 and L4 treatments at the same N level. Surplus N was low under the reduced N rates and delayed basal N application treatments. Therefore, postponing and reducing basal N fertilization could maintain a high yield and improve NUE by improving the photosynthetic production capacity, promoting N uptake and assimilation, and reducing surplus N in soil-wheat systems.

Predicting Grain Yield and Protein Content in Winter Wheat at Different N Supply Levels Using Canopy Reflectance Spectra

用一个裂口阴谋的一个地实验使随机化有三复制的完全的块设计被执行决定在之间的关系光谱索引和小麦谷物产量( GY )，为 GY 比较四个植被索引(力)的表演预言，并且到学习，到估计谷物蛋白质的 VI 的可行性满足( GPC )在里面冬小麦。二典型冬小麦( Triticum aestivum L.)栽培变种 ‘X uzhou 26'(高蛋白质内容)和 ‘H uaimai 18'(低蛋白质内容)被用作著处理和四 N 率，即， 0 ， 120 ， 210 ，和 300 kg N 哈? 1 ，作为次要情节处理。增加的土壤 N 供应显著地增加了 GY 和 GPC (P ≤ 0.05 ) 。为联合的二栽培变种，重要并且正相关在四个力和 GY 之间被发现，当使用绿比率植被索引(GRVI ) 在时，观察的最强壮的关系地中间充满。累积 VI 实质地估计改进产量预测，与正在出发到成熟舞台的最好的间隔。类似的结果在 VI 和谷物蛋白质产量之间被发现。然而，当使用累积 VI 时， GPC 没显示出重要改进。在叶 N 地位和 GPC 之间的强壮的关系(R2 = 0.9144 为‘ X uzhou 26' 和 R2 = 0.8285 为‘ H uaimai 18') 显示华盖系列能被用来预言 GPC。强壮在估计并且观察的 GPC 之间合适(R2 = 0.7939 ) 显示遥感技术在小麦是谷物蛋白质内容和质量的潜在地有用的预言者。

Common Spectral Bands and Optimum Vegetation Indices for Monitoring Leaf Nitrogen Accumulation in Rice and Wheat

Real-time monitoring of nitrogen status in rice and wheat plant is of significant importance for nitrogen diagnosis, fertilization recommendation, and productivity prediction. With 11 field experiments involving different cultivars, nitrogen rates, and water regimes, time-course measurements were taken of canopy hyperspeetral reflectance between 350-2 500 nm and leaf nitrogen accumulation （LNA） in rice and wheat. A new spectral analysis method through the consideration of characteristics of canopy components and plant growth status varied with phenological growth stages was designed to explore the common central bands in rice and wheat. Comprehensive analyses were made on the quantitative relationships of LNA to soil adjusted vegetation index （SAVI） and ratio vegetation index （RVI） composed of any two bands between 350-2 500 nm in rice and wheat. The results showed that the ranges of indicative spectral reflectance were largely located in 770-913 and 729-742 nm in both rice and wheat. The optimum spectral vegetation index for estimating LNA was SAVI （R822, R738） during the early-mid period （from jointing to booting）, and it was RVI （Rs22, R73s） during the mid-late period （from heading to filling） with the common central bands of 822 and 738 nm in rice and wheat. Comparison of the present spectral vegetation indices with previously reported vegetation indices gave a satisfactory performance in estimating LNA. It is concluded that the spectral bands of 822 and 738 nm can be used as common reflectance indicators for monitoring leaf nitrogen accumulation in rice and wheat.

Quantifying the spatial variation in the potential productivity and yield gap of winter wheat in China

Despite the improvement in cultivar characters and management practices, large gaps between the attainable and potential yields still exist in winter wheat of China. Quantifying the crop potential yield is essential for estimating the food production capacity and improving agricultural policies to ensure food security. Gradually descending models and geographic infor- mation system （GIS） technology were employed to characterize the spatial variability of potential yields and yield gaps in winter wheat across the main production region of China. The results showed that during 2000-2010, the average potential yield limited by thermal resource （YGT） was 23.2 Mg ha-1, with larger value in the northern area relative to the southern area. The potential yield limited by the water supply （YGw） generally decreased from north to south, with an average value of 1.9 Mg ha-1 across the entire study region. The highest YGw in the north sub-region （NS） implied that the irrigation and drainage conditions in this sub-region must be improved. The averaged yield loss of winter wheat from nutrient deficiency （YGH） varied between 2.1 and 3.1 Mg ha-1 in the study area, which was greater than the yield loss caused by water limitation. The potential decrease in yield from photo-thermal-water-nutrient-limited production to actual yield （YGo） was over 6.0 Mg ha-1, ranging from 4.9 to 8.3 Mg ha^-1 across the entire study region, and it was more obvious in the southern area than in the northern area. These findings suggest that across the main winter wheat production region, the highest yield gap was induced by thermal resources, followed by other factors, such as the level of farming technology, social policy and economic feasibility. Furthermore, there are opportunities to narrow the yield gaps by making full use of climatic resources and developing a reasonable production plan for winter wheat crops. Thus, meeting the challenges of food security and sustainability in the coming decades is possible but will require considerable changes in water and nutrient management and socio-economic policies.

Spatial and Temporal Characteristics of Rice Potential Productivity and Potential Yield Increment in Main Production Regions of China

The vast area and marked variation of China make it difficult to predict the impact of climate changes on rice productivity in different regions.Therefore,analyzing the spatial and temporal characteristics of rice potential productivity and predicting the possible yield increment in main rice production regions of China is important for guiding rice production and ensuring food security.Using meteorological data of main rice production regions from 1961 to 1970（the 1960s） and from 1996 to 2005（the 2000s） provided by 333 stations,the potential photosynthetic,photo-thermal and climatic productivities in rice crop of the 1960s and 2000s in main rice production regions of China were predicted,and differences in the spatial and temporal distribution characteristics between two decades were analyzed.Additionally,the potential yield increment based on the high yield target and actual yield of rice in the 2000s were predicted.Compared with the 1960s,the potential photosynthetic productivity of the 2000s was seen to have decreased by 5.40%,with rates in northeastern and southwestern China found to be lower than those in central and southern China.The potential photo-thermal productivity was generally seen to decrease（2.56%） throughout main rice production regions,decreasing most in central and southern China.However,an increase was seen in northeastern and southwestern China.The potential climatic productivity was observed to be lower（7.44%） in the 2000s compared to the 1960s,but increased in parts of central and southern China.The potential yield increment from the actual yield to high yield target in the 2000s were no more than 6×103 kg ha-1 and ranged from 6×103 to 12×103 kg ha-1 in most of the single-and double-cropping rice growing regions,respectively.The yield increasing potential from the high yield target to the potential photo-thermal productivity in 2000s were less than 10×103 kg ha-1 and ranged from 10×103 to 30×103 kg ha-1 in most of the single-and double-cropping rice growing regions,respectively.The potential yield increment contributed by irrigation was between 5×103 and 20×103 kg ha-1,and between 20×103 and 40×103 kg ha-1 in most of the single-and double-cropping rice growing regions,respectively.These findings suggested that the high yield could be optimized by making full use of climatic resources and through a reasonable management plan in rice crop.

Modeling Dynamics of Leaf Color Based on RGB Value in Rice

This paper was to develop a model for simulating the leaf color changes in rice （Oryza sativa L.） based on RGB （red, green, and blue） values. Based on rice experiment data with different cultivars and nitrogen （N） rates, the time-course RGB values of each leaf on main stem were collected during the growth period in rice, and a model for simulating the dynamics of leaf color in rice was then developed using quantitative modeling technology. The results showed that the RGB values of leaf color gradually decreased from the initial values （light green） to the steady values （green） during the first stage, remained the steady values （green） during the second stage, then gradually increased to the final values （from green to yellow） during the third stage. The decreasing linear functions, constant functions and increasing linear functions were used to simulate the changes in RGB values of leaf color at the first, second and third stages with growing degree days （GDD）, respectively; two cultivar parameters, MatRGB （leaf color matrix） and AR （a vector composed of the ratio of the cumulative GDD of each stage during color change process of leaf n to that during leaf n drawn under adequate N status）, were introduced to quantify the genetic characters in RGB values of leaf color and in durations of different stages during leaf color change, respectively; FN （N impact factor） was used to quantify the effects of N levels on RGB values of leaf color and on durations of different stages during leaf color change; linear functions were applied to simulate the changes in leaf color along the leaf midvein direction during leaf development process. Validation of the models with the independent experiment dataset exhibited that the root mean square errors （RMSE） between the observed and simulated RGB values were among 8 to 13, the relative RMSE （RRMSE） were among 8 to 10%, the mean absolute differences （da） were among 3.85 to 6.90, and the ratio of da to the mean observation values （Clap） were among 3.04 to 4.90%. In addition, the leaf color model was used to render the leaf color change over growth progress using the technology of visualization, with a good performance on predicting dynamic changes in rice leaf color. These results would provide a technical support for further developing virtual plant during rice growth and development.

A Knowledge Model System for Wheat Production Management

A knowledge model with temporal and spatial characteristics for the quantitative design of a cultural pattern in wheat production, using systems analysis and dynamic modeling techniques, was developed for wheat management, as a decision-making tool in digital farming. The fundamental relationships and algorithms of wheat growth indices and management criteria to cultivars, ecological environments, and production levels were derived from the existing literature and research data to establish a knowledge model system for quantitative wheat management using Visual C++. The system designed a cultural management plan for general management guidelines and crop regulation indices for time-course control criteria during the wheat-growing period. The cultural management plan module included submodels to determine target grain yield and quality, cultivar choice, sowing date, population density, sowing rate, fertilization strategy, and water management, whereas the crop regulation indices module included submodels for suitable development stages, dynamic growth indices, source-sink indices, and nutrient indices. Evaluation of the knowledge model by design studies on the basis of data sets of different eco-sites, cultivars, and soil types indicated a favorable performance of the model system in recommending growth indices and management criteria under diverse conditions. Practical application of the knowledge model system in comparative field experiments produced yield gains of 2.4% to 16.5%. Thus, the presented knowledge model system overcame some of the difficulties of the traditional wheat management patterns and expert systems, and laid a foundation for facilitating the digitization of wheat management.

Methods on Identification and Screening of Rice Genotypes with High Nitrogen Efficiency

In order to establish methods for indentification and screening of rice genotypes with high nitrogen （N） efficiency, N absorption efficiency （NAE）, N utilization efficiency （NUE） and N harvest index （NHI） in ten rice genotypes were investgated at the elongation, booting, heading and maturity stages under six N levels in a pot experiment with soil-sand mixtures at various ratios. NAE in various rice genotypes firstly increased, peaked under a medium nitrogen rate of 0.177 g/kg and then decreased, but NUE and NHI always decreased with increasing nitrogen levels. NAE in various rice genotypes ever increased with growing process and NUE indicated a descending tendency of elongation stage〉heading stage〉maturity stage〉booting stage. N level influenced rice NAE, NUE and NHI most, followed by genotype, and the both effects were significant at 0.01 level. In addition, the interaction effects of genotype and nitrogen level on rice NAE and NUE were significant at 0.01 level, but not significant on rice NHI. Because the maximum differences of NAE and NUE were found at the elongation stage, it was thought to be the most suitable stage for identification and screening these two paremeters. Therefore, the optimum conditions for identification and screening of rice NAE, NUE and NHI in a pot experiment were the nitrogen rate of 0.157 g/kg at the elongation stage, low nitrogen at the elongation stage, and the nitrogen rate of 0.277 g/kg at the maturity stage, respectively.

A New Method to Determine Central Wavelength and Optimal Bandwidth for Predicting Plant Nitrogen Uptake in Winter Wheat

Plant nitrogen （N） uptake is a good indicator of crop N status. In this study, a new method was designed to determine the central wavelength, optimal bandwidth and vegetation indices for predicting plant N uptake （g N m-2） in winter wheat （Triticum aestivum L.）. The data were collected from the ground-based hyperspectral reflectance measurements in eight field experiments on winter wheat of different years, eco-sites, varieties, N rates, sowing dates, and densities. The plant N uptake index （PNUI） based on NDVI of 807 nm combined with 736 nm was selected as the optimal vegetation index, and a linear model was developed with R2 of 0.870 and RMSE of 1.546 g N m-2 for calibration, and R2 of 0.834, RMSE of 1.316 g N m-2, slope of 0.934, and intercept of 0.001 for validation. Then, the effect of the bandwidth of central wavelengths on model performance was determined based on the interaction between central wavelength and bandwidth expansion. The results indicated that the optimal bandwidth varies with the changes of the central wavelength and with the interaction between the two bands in one vegetation index. These findings are important for prediction and diagnosis of plant N uptake more precise and accurate in crop management.

Modeling curve dynamics and spatial geometry characteristics of rice leaves

The objective of this work was to develop a dynamic model for describing leaf curves and a the rice leaf （including sub-models for unexpanded leaf blades, expanded leaf blades, and dimensional （3D） dynamic visualization of rice leaves by combining relevant models detailed spatial geometry model of leaf sheaths）, and to realize three- Based on the experimental data of different cultivars and nitrogen （N） rates, the time-course spatial data of leaf curves on the main stem were collected during the rice development stage, then a dynamic model of the rice leaf curve was developed using quantitative modeling technology. Further, a detailed 3D geometric model of rice leaves was built based on the spatial geometry technique and the non-uniform rational B-spline （NURBS） method. Validating the rice leaf curve model with independent field experiment data showed that the average distances between observed and predicted curves were less than 0.89 and 1.20 cm at the tilling and jointing stages, respectively. The proposed leaf curve model and leaf spatial geometry model together with the relevant previous models were used to simulate the spatial morphology and the color dynamics of a single leaf and of leaves on the rice plant after different growing days by 3D visualization technology. The validation of the leaf curve model and the results of leaf 3D visualization indicated that our leaf curve model and leaf spatial geometry model could efficiently predict the dynamics of rice leaf spatial morphology during leaf development stages. These results provide a technical support for related research on virtual rice.

Spatiotemporal Changes in Soil Nutrients:A Case Study in Taihu Region of China

The accurate assessment of the spatiotemporal changes in soil nutrients influenced by agricultural production provides the basis for development of management strategies to maintain soil fertility and balance soil nutrients. In this paper, we combined spatial measurements from 2 157 soil samples and geostatistical analysis to assess the spatiotemporal changes in soil organic carbon （SOC）, total nitrogen （TN）, available phosphorus （AP） and available potassium content （AK） from the first soil survey （in the 1980s） to the second soil survey （in the 2000s） in the Taihu region of Jiangsu Province in China. The results showed that average soil nutrients in three soil types all exhibited the increased levels in the 2000s （except for AK in the yellow brown soil）. The standard deviation of soil nutrient contents increased （except for TN in the paddy soil）. Agricultural production in the 20 years led to increases in SOC, TN, AP and AK by 74, 82, 89 and 65%, respectively, of the Taihu areas analyzed. From the 1980s to 2000s all the nugget/sill ratios of soil nutrients indices were between 25 and 75% （except for AK in the yellow brown soil in the 2000s）, indicating moderate spatial dependence. The ratio of AP in the yellow brown soil in the 2000s was 88.74%, showing weak spatial dependence. The spatial correlation range values for SOC, TN, AP and AK in the 2000s all decreased. The main areas showing declines in SOC, TN and AP were in the northwest. For AK, the main region with declining levels was in the east and middle of western areas. Apparently, the increase in soil nutrients in the Taihu region can be mainly attributed to the large increase in fertilizer inputs, change in crop systems and enhanced residues management since the 1980s. Future emphasis should be placed on avoiding excess fertilizer inputs and balancing the effects of the fertilizers in soils.

Leaf area index based nitrogen diagnosis in irrigated lowland rice

Leaf area index （LAI） is used for crop growth monitoring in agronomic research, and is promising to diagnose the nitrogen （N） status of crops. This study was conducted to develop appropriate LAI-based N diagnostic models in irrigated lowland rice. Four field experiments were carried out in Jiangsu Province of East China from 2009 to 2014. Different N application rates and plant densities were used to generate contrasting conditions of N availability or population densities in rice. LAI was determined by LI-3000, and estimated indirectly by LAI-2000 during vegetative growth period. Group and individual plant characters （e.g., tiller number （TN） and plant height （H）） were investigated simultaneously. Two N indicators of plant N accumulation （NA） and N nutrition index （NNI） were measured as well. A calibration equation （LAI=1.7787LAI2o00-0.8816, R2=0.870＂） was developed for LAI-2000. The linear regression analysis showed a significant relationship between NA and actual LAI （R2=0.863^＊＊）. For the NNI, the relative LAI （R2=0.808-） was a relatively unbiased variable in the regression than the LAI （R^2=0.33^＊＊）. The results were used to formulate two LAI-based N diagnostic models for irrigated lowland rice （NA=29.778LAI-5.9397; NNI=0.7705RLAI＋0.2764）. Finally, a simple LAI deterministic model was developed to estimate the actual LAI using the characters of TN and H （LAI=-0.3375（THxHx0.01）2＋3.665（TH×H×0.01）-1.8249, R2=0.875＊＊）. With these models, the N status of rice can be diagnosed conveniently in the field.