Effects of Seeding Rate and Nitrogen Application Rate on Grain Yield and Protein Content of the Bread Wheat Cultivar ‘Minaminokaori’ in Southwestern Japan

Abstract

We examined the effects of seeding rate, 50 or 150 seeds m-², nitrogen (N) application rate at active tillering and jointing, 4 and 2 g N m-², respectively, or none, and N application rate at anthesis, 0, 2, 4, or 6 g N m-², on grain yield and protein content of a bread wheat cultivar, ‘Minaminokaori’, during the 2004–2005 crop season in southwestern Japan. Grain yield was similar at a seeding rate of 50 and 150 seeds m-². It was higher when 4 and 2 g N m-² were applied at active tillering and jointing, respectively (4–2N), than when no N was applied at these stages (0–0N). However, it was not influenced by N application rate at anthesis. Grain protein content was similar at 50 and 150 seeds m-². It was higher in 4–2N than in 0–0N. It was the highest when 6 g N m-² was applied at anthesis, followed by 4, 2, and 0 g N m-². The SPAD value at anthesis was higher at 50 than 150 seeds m-², but leaf area index (LAI) at anthesis was similar at 50 and 150 seeds m-² and protein content of grain was nearly the same at 50 and 150 seeds m-² irrespective of N application rate at anthesis. LAI and the SPAD value were higher in 4–2N than in 0–0N and the protein content of grain was also higher in 4–2N than in 0–0N irrespective of N application rate at anthesis. Therefore, both LAI and the SPAD value may be important traits related to the N application rate at anthesis suitable for yielding wheat grain with a high protein content.     

基于PROSAIL模型和无人机高光谱数据的冬小麦LAI反演

为及时准确高效监测小麦叶面积指数(leaf area index, LAI),获取了冬小麦挑旗期和开花期地面实测光谱与无人机高光谱遥感影像数据,并基于查找表建立PROSAIL辐射传输模型得到冬小麦冠层模拟光谱数据,利用数学统计回归模型与偏最小二乘回归法分别构建冬小麦LAI单变量、多变量预测模型,以实测LAI数据对预测结果进行精度评价,将最佳预测模型应用于无人机高光谱影像以分析LAI空间分布情况。结果表明,冬小麦各生育时期的预测模型均具有较高的预测精度,单变量预测模型和多变量预测模型的决定系数分别为0.598～0.717和0.577～0.755,其中以基于植被指数的多变量预测模型表现最优,其在开花期的验证精度最高,RMSE和MAPE分别为0.405和12.90%。在LAI空间分布图中,开花期预测效果优于挑旗期,各试验小区的LAI分布较为均匀。     

冬小麦叶面积指数真实性检验尺度扩展方法研究

为在空间尺度上实现冬小麦LAI地面观测与遥感观测直接匹配,从1 m×1 m范围的实测LAI出发,通过优化采样方法扩展得到16 m×16 m范围的冬小麦LAI,然后利用空间分辨率为16 m的高分1号卫星的多光谱数据计算样本点的植被指数,建立其与冬小麦LAI的拟合模型,从四种植被指数的拟合模型中挑选表现最好的LAI估测模型,获得16 m×16 m尺度的LAI分布图,并经过重采样聚合为250 m×250 m尺度的LAI格点图,从而实现从地面点测量数据到卫星尺度数据的扩展。检验结果表明,16 m×16 m和250 m×250 m两个研究区域模拟点值和实测点值的相对误差分别为4.18%和3.64%,说明这种尺度扩展方法是科学可行的。     

县域冬小麦生物量动态变化遥感估测研究

为给生产管理中及时掌握县域冬小麦长势的动态变化提供有效手段,以江苏省沭阳县为研究区,基于冬小麦生物量形成的生理生态过程,重构冬小麦生物量遥感估测模型。选用两景不同时相的HJ星影像数据,利用植被指数反演的LAI数据,对冬小麦生物量模型进行参数修订,并对县域冬小麦拔节期生物量的空间分布进行估测。在此基础上,进一步估测冬小麦抽穗期生物量分布特征及其动态变化特点。结果表明：（1）冬小麦拔节期生物量估测值和观测值范围分别为2 054.3~4 828.3 和1 962.5~4 568.4 kg·hm^-2 ,平均值分别为3 148和3 045.5 kg·hm^-2 ,RMSE为214.8 kg·hm^-2 ,决定系数为0.919 1,表明冬小麦生物量模型模拟精度较好;（2）冬小麦抽穗期生物量较拔节期发生明显变化,其中长势变化快的田块面积为20 108.7hm,占总种植面积的23.4%。春季气候因素的转好以及肥水措施的实施对冬小麦营养与生殖共生阶段的生长起到明显促进作用。说明本研究提出的基于遥感反演信息与生长模型协同的冬小麦生物量估测方法能有效估测县域冬小麦不同生长时期生物量的空间分布及其动态变化。     

基于遥感信息和WOFOST模型参数同化的冬小麦单产估算方法研究

为探讨遥感信息和作物生长模型在作物估产方面的优势互补特性,选取河北省藁城市冬小麦作为研究对象,采集多个关键生育时期的生理生化、农田环境、气象等数据,并获取准同步的环境减灾小卫星HJ-CCD影像数据,采用植被指数反演冬小麦叶面积指数（LAI）,基于扩展傅里叶振幅灵敏度检验法(EFAST)对WOFOST作物模型的26个初始参数进行全局敏感性分析,筛选敏感性参数,调整WOFOST模型的核心参数,利用查找表优化算法构建基于WOFOST模型和遥感LAI数据同化的区域尺度冬小麦单产预测模型,并定量预测区域冬小麦单产水平。结果表明,增强型植被指数（EVI）是遥感反演LAI的最佳植被指数(开花期建模r=0.913,RMSE=0.410,灌浆期建模r=0.798,RMSE=0.470),预测能力最强(开花期r=0.858,RMSE=0.531,灌浆期r=0.861,RMSE=0.428);筛选出6个待优化参数,即TSUM1、SLATB1、SLATB2、SPAN、EFFTB3和TMPF4;产量预测精度r=0.914,RMSE=253.67 kg·hm_-2,找到了待优化参数的最佳取值,最终完成了单产模拟。     

Effects of Planting Time and Nitrogen Application on Dry Matter Yield of the Forage Rice Cultivar Tachiaoba in Southwestern Japan

Abstract

We examined the effects of planting time on the dry matter (DM) yield of the forage rice cultivar Tachiaoba in southwestern Japan. DM yield was much higher with early planting than with normal planting. Dry weight (DW) per tiller was much higher with early planting than with normal planting. Thus, early planting is effective to obtain high DM yield. DM yield was closely related to the DW increase from transplanting to the full-heading stage (DW increase before heading) and DW per tiller. These results suggest that early planting leads to an increase in DW at the full-heading stage through an increase in DW per tiller and gives a high DM yield at the yellow-ripe stage. We also examined the effects of nitrogen (N) application rate and method on DM yield at the yellow-ripe stage. DM yield was higher with application of 22.5 g N m-² than with 15.0 g N m-². Although DW per tiller was slightly lower with application of 22.5 g N m-² than with 15.0 g N m-², the number of tillers per square meter was much higher with application of 22.5 g N m-² than with 15.0 g N m-². DM yield was the highest with N application method 1 that was applied more N early, followed by methods 2 that was applied more N evenly over time and 3 that was applied more N later. The number of tillers per square meter was much higher with method 1 than with method 2 or 3. Thus, application of 22.5 g N m-² by method 1 is effective to obtain high DM yield. With both early and normal plantings, DM yield was closely related to the DW increase before heading and the number of tillers per square meter. These results suggest that application of 22.5 g N m-² by method 1 lead to an increase in DW at the full-heading stage through an increase in the number of tillers per square meter resulting in a high DM yield at the yellow-ripe stage.     

基于Sentinel-2多光谱数据和机器学习算法的冬小麦LAI遥感估算

为了丰富大田尺度下冬小麦叶面积指数的遥感估算方法并提高估算精度,以关中地区冬小麦为对象,基于Sentinel-2多光谱卫星数据与地面同步观测的冬小麦叶面积指数样点数据,应用偏最小二乘回归(PLSR)、反向传播神经网络(BPNN)和随机森林(RF)法构建冬小麦叶面积指数估算模型,进行区域冬小麦叶面积指数遥感反演.结果表明...     

冬小麦叶面积指数的品种差异性与高光谱估算研究

为给小麦叶面积指数（LAI）的高光谱估算提供技术支持,基于2年大田试验,以4个河南主推品种为材料,对小麦LAI和冠层光谱变化特点、估算模型及其品种间的差异等进行了系统分析。结果表明,在生育期内不同冬小麦品种冠层光谱反射率的变化与LAI变化有差异;在相同LAI下,不同冬小麦品种的光谱曲线存在差异。利用400~900 nm范围内冠层光谱反射率的任意两波段组合的比值光谱指数（RSI）、归一化差值光谱指数（NDSI）和差值光谱指数（DSI）所建立的单品种模型以及不同品种综合模型的决定系数（r）均达到0.84以上,单品种模型的r和调整r分别较综合模型高出3.1%~4.8%和2.0%~4.2%。利用独立于建模样本以外的数据对上述模型进行检验,单品种模型预测的r较综合模型提高了0.6%~11.0%,而均方根误差降低了10.0%~37.0%。因此,在利用高光谱遥感技术估算冬小麦LAI时,可以通过建立单品种模型来提高估算精度。     

Yielding Performance of “Kita-aoba”, High-yielding Rice Variety for Hokkaido Region,Northern Japan

Abstract

The yielding performance of the first high-yielding rice variety for Hokkaido, Kita-aoba, after application of various amounts of nitrogen (9.0 to 23.7 g m-² in 2008 and 10.5 to 16.5 g m-² in 2010) and under various planting densities (13.2 to 33.2 hills m-² in 2008 and 17.5 to 36.8 hills m-² in 2010) was examined in comparison with that of the common variety, Kirara397. Kita-aoba had higher grain yield than Kirara397 owing to its large sink capacity through larger sink capacity per unit biomass at heading. Kita-aoba had a high yield potential (the maximum grain yield of 1081 g m-²), and achieved a high grain yield even in Hokkaido where the rice-growing season is short. Kita-aoba had a large sink size, but, judging from the relationship between sink capacity and percentage of sink filled, further increase of sink size might not result in increase of grain yield. Kita-aoba showed a great increase in shoot dry matter from heading to maturity, but it was not enough to fill its large sink.     

Yield Stability of Aromatic Upland Rice with High Yielding Ability in Indonesia

Abstract

Aromatic rice variety, Mentikwangi, was crossed with high-yielding upland rice variety, Poso, and the pedigree was selected to obtain lines with high yielding and aromatic characters. The objectives of the research were to study the yield stability of aromatic upland genotypes across different locations and to select aromatic upland rice genotypes having wide adaptability, and or specific location adaptability. Yield stability of genotypes was estimated by using regression lines proposed by Finlay and Wilkinson. Some genotypes showed high yield stability and wide adaptability in different locations, and others showed good adaptability to a specific location. The lines having high yield stability and wide adaptability were G10 (405 g m-²), G19 (400 g m-²), G39 (418 g m-²), and G136 (411 g m-²), which may be considered as candidates of new aromatic upland rice cultivars. Situpatenggang had specific adaptability at the fertile locations; and Poso and G13 at the infertile locations. Genotype x location interactions for the yield and its components performance were observed.     

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。     

利用RADARSAT-2雷达数据与改进的水云模型反演冬小麦叶面积指数

利用微波遥感反演植被参数往往受到植被分布不均、稀疏植被覆盖、地表裸土等因素影响,导致微波遥感用于农业参数估计的效果不佳。为解决微波遥感反演地表植被参数的问题,本研究在原有的水云模型基础上引入植被覆盖度以及裸土对于雷达后向散射系数的直接作用信息,提出一种改进的水云模型,并充分考虑地表植被的覆盖分布情况,结合地面实测数据及RADARSAT-2雷达数据对改进模型进行验证,然后根据改进模型通过查找表法反演出植被含水量,最后利用叶面积指数与植被含水量的经验关系间接得到叶面积指数的估测值。结果表明,改进的水云模型对后向散射系数的模拟精度比原有的水云模型精度高,模拟的决定系数在HH和VV极化时分别为0.850和0.739,均方根误差分别为0.918dB和1.475dB。由此可见,改进的模型对研究区植被条件更为敏感,能够较好地分离出植被与土壤信息对雷达后向散射系数的影响,同时利用其反演得到的叶面积指数精度较高,决定系数达到0.841,均方根误差为0.233。     

星机协同的冬小麦长势遥感监测研究—以陕西省咸阳市为例

为了解决作物长势遥感监测中星机协同性问题，在田块尺度上通过设置小麦氮素和灌溉梯度试验，在各关键生育时期测定SPAD和LAI两个长势指标并获取无人机遥感数据，构建小麦长势多光谱监测模型，并将优化的波段比值修正法与Sentinel-2A影像结合进行模型升尺度应用。结果表明，在拔节期、孕穗期、开花期和灌浆期，分别利用Clgreen、Clrededge、OSAVI和OSAVI构建的三次函数、指数函数、指数函数和幂函数对小麦SPAD的拟合效果最佳，升尺度应用至孕穗期、开花期和灌浆期卫星遥感监测后验证精度均较好；上述四个生育时期分别利用Clgreen、Clrededge、DATT和OSAVI构建的幂函数、二次函数、指数函数和指数函数对LAI拟合效果最佳，升尺度应用验证精度均较好。基于该星机协同方法对咸阳市冬小麦长势进行监测发现，2021年武功县、兴平市、三原县等区域小麦各生育时期长势均较优，永寿县、淳化县、彬州市等地的小麦长势均较差。这说明通过对无人机和卫星遥感影像融合方法的完善，可提高冬小麦长势监测中星机协同性。     

Farmers’ Management Practices and Grain Yield of Rice in Response to Different Water Environments in Kamping Puoy Irrigation Rehabilitation Area in Northwest Cambodia

Abstract

The farmers’ management practices and grain yield were examined in the consecutive 4 cropping seasons from wet season rice (WSR) in 2008 to dry season rice (DSR) in 2010 across upstream, midstream and downstream fields, along two secondary drainage canals (located either upstream or downstream side along the main canal) in the Kamping Puoy Irrigation Rehabilitation area (KPIR). In WSR, standing water depth was much deeper in downstream fields where medium and late maturing varieties were planted from May than in upstream fields where early and early medium maturing varieties were planted later (mostly in July and August). In DSR there was less difference in water conditions between upstream and downstream fields and variation in planting and harvesting time was small. As the area percentage of fields where DSR was introduced increased from 2008 (54%) to 2010 (100%), planting time in WSR was later (e.g., from May to July) with declining proportion of dry seeding method and mid-season tillage. Grain yield was low in DSR, particularly in 2010 (287 and 247 g m-² in 2009 and 2010 on average, respectively), due to insufficient weed control and small amount of fertilizer, and the yield was lowest in fields which practiced DSR for the first time. Grain yield in WSR (286 and 291 g m-² in 2008 and 2009 respectively) increased by transplanting, use of high yielding Raing Chey variety, and application of a larger amount of N chemical fertilizer. These findings indicated that the agriculture extension support to farmers, particularly in DSR, is a key important factor for rice yield improvement in KPIR.     

Historical Changes in Urban Rice Production Systems in Tokyo,Japan

Abstract

Historical changes in planting area, yield improvements, and production of both paddy and upland rice (Oryza sativa L.) in Tokyo and the whole of Japan from 1877 to 2003 were reviewed. The area of rice in Tokyo was at its peak (17,000 ha) at the beginning of the 20th century but dramatically reduced thereafter except for the period of 1950s, to200 and 30 ha for paddy and upland rice, respectively, in 2003, due to urbanization. After the 1950s, the land-use efficiency rate in Tokyo was reduced from 180 to 100% and rice self-sufficiency rate from 4 to 0.1%. There was historical yield improvement of paddy rice in Tokyo particularly after 1960s in the Southern and Northern Tama regions, but the current yield level in Tokyo (ca. 400 g m-²) is lower than that in the whole of Japan (more than 500 g m-²) eventhough crop damage due to low temperatures is not serious.The reasons were discussed from the viewpoints of (1) less agricultural inputs and agronomic management, (2) declining rice research after the 1970s, (3) higher elevating air temperature(e.g. 1.4°C for the last 40 years), in Tokyo, and (4) yield component differences. Upland rice in Tokyo has a planting area comparable with paddy rice (ca. 7,000 to 8,000 ha) during the 1950s, but yield improvement during the last 50 yearsis not noticeable (ca. 150 g m-²) with no development of cultivars, and with greater fluctuation of crop situation index due to drought compared with paddy rice. This review paper discusses the importance of urban rice production system, along with a proposal of the alternatives.     

多遥感光谱指标结合进行大田冬小麦叶片叶绿素含量估测研究

为解决大田冬小麦叶片叶绿素含量估测模型精度低、通用性弱的问题,在获取冬小麦拔节期和抽穗期冠层红光波段反射率(BR_red)和近红外波段反射率(BR_nir)的基础上,计算归一化差值植被指数(NDVI)、差值植被指数(DVI)、比值植被指数(RVI)、土壤调节植被指数(SAVI)、改进型比值植被指数(MSR)、重归一化植被指数(RDVI)、II型增强植被指数(EVI2)和非线性植被指数(NLI)等8个植被指数。经统计分析,选择与叶片叶绿素含量(SPAD值)相关性较好的5个遥感光谱指标(NDVI、MSR、NLI、BR_red和RVI)作为输入变量,建立了冬小麦叶片叶绿素含量的BP神经网络估测模型(WWLCC_BP),并对估测模型进行精度验证。结果表明,WWLCC_BP估测模型在拔节期估测的决定系数(r²)为0.84,均方根误差(RMSE)为5.39,平均相对误差(ARE)为9.87%。抽穗期的估测效果与拔节期较为一致。将WWLCC_BP和高分六号影像...     

基于RapidSCAN CS-45的新疆滴灌冬小麦氮肥推荐研究

为给滴灌小麦氮营养状况实时评估和氮肥合理施用提供参考,通过2年田间定位试验,以当地主栽品种新冬22号为试验材料,设置5个施氮水平(0、120、240、360、480 kg· hm-2),利用主动式光谱仪RapidScan CS-45获取各生育时期冠层归一化植被指数(NDVI)和归一化红边植被指数(NDRE),分析其与滴...     

Continuous Monitoring of Visible and Near-Infrared Band Reflectance from a Rice Paddy for Determining Nitrogen Uptake Using Digital Cameras

Abstract

A two-band digital imaging system —one band for the visible red band (RED, 630?670 nm) and the other for the near infrared band (NIR, 820?900 nm)— was devised and positioned at a height of 12 m above a rice field of 300 m² in area during the 2007 growing season. The imaging system automatically logged bird’seye view images at 10-min intervals from 0800?1600 every day. Radiometric corrections for the pairs of two-band images were done using solar irradiance sensors and preceding calibrations to calculate daily band-reflectance and the normalized difference vegetation index (NDVI) values for 9 plots of rice plants, with 3 levels of planting density and basal fertilization. The daily- averaged reflectance values in the RED and the NIR bands showed different but smooth seasonal changing patterns according to the growth of plants. At the maximum tiller number and the panicle formation stages, the RED and NIR reflectance values had correlation coefficients (r) of 0.79 and 0.81 with above-ground nitrogen absorption per unit land area (NA, g m-²), respectively, whereas the NDVI using the two band reflectance values showed r-value of -0.13. An empirically derived equation for the NA using two band reflectance values showed r-value of 0.96 and a root mean square of error (RMSE) 0.5 g m^–2 (10% of the mean observed NA) in the estimation for the original (not validated) data set acquired at the maximum tiller number and the panicle formation stages. The results indicated that reflectance observation in the RED and NIR bands using the digital imaging system was potentially effective for assessing rice growth.     

基于无人机多光谱遥感的冬小麦冠层叶绿素含量估测研究

为探讨利用无人机多光谱影像监测冬小麦叶绿素含量的可行性,基于北京市大兴区中国水科院试验基地的2019年冬小麦无人机多光谱影像和田间实测冠层叶绿素含量数据,选取16种光谱植被指数,确定对冬小麦冠层叶绿素含量显著相关的植被指数,采用一元二次线性回归和逐步回归分析方法建立各生育时期及全生育期的SPAD值估测模型,通过精度检验确定对冬小麦冠层叶绿素含量监测的最优模型。结果表明,两种分析方法中逐步回归建模效果最佳。拔节期选取4个植被指数(MSR、CARI、NGBDI、TVI)建模效果最好,模型率定的决定系数(r~2)为0.73,模型验证的r~2、相对误差(RE)和均方根误差(RMSE)分别为0.63、2.83%、1.68;抽穗期选取3个植被指数(GNDVI、GOSAVI、CARI)建模效果最好,模型率定的r~2为0.81,模型验证的r~2、RE、RMSE分别为0.63、2.83%、1.68;灌浆期选取2个植被指数(MSR、NGBDI)建模效果最好,模型率定的r~2为0.67,模型验证的r~2、RE、RMSE分别为0.65、2.83%、1.88。因此,无人机多光谱影像结合逐步回归模型可以很好地监测冬小麦SPAD值动态变化。