A Simple Model for Predicting Daily Mean Soil Temperatures

Based on measurements in 3 different types of soil (clay, sand, peat) linear regression equations between daily air temperature (2 m) and soil temperature (2, 5, 10, 20, 50 cm depth) are calculated for all months of the growing season. The equations show a significant seasonal dependence and the best correlations in the upper 10 cm of soil. Differences depending on the type of soil are relatively small. Correction terms involving cloudiness and thermal inertia of the soil during a sudden warming or cooling period complete the prediction model. Standard deviations between predicted and measured values have been found within 1.5 K in most cases. Lastly a generally applicable method for calculating regression equations at any station is introduced. The application of this method to different sites and types of soil in Bavaria and other regions of Germany shows a good agreement with measured values.     

成都市休闲农业模式的对比研究——基于直接主体和间接主体2种模式

成都市休闲农业作为农村经济的新增长点,呈现出蓬勃发展的势头,其发展模式对未来的发展路径和方向起着至关重要的作用。基于成都市休闲农业直接主体和间接主体2种模式对比分析,分别以郫县农科村和锦江区三圣花乡为典型,对其组织形式、经营形式、产品形式以及营销形式4个方面进行对比研究,分别分析2种模式各自的优劣势,并总结经验和启示：注重政府的角色定位;产品开发营造特色,增强竞争力;注重经营理念的创新及经营水平的提升。最后,提出成都市休闲农业可持续发展的建议。     

应用灰板校正提高计算机视觉预测棉花植株含水量的精确度

利用灰板校正以消除棉花不同生育期图片颜色特征值的亮度差异,建立适用于不同生育期预测植株含水量的通用模型,以提高运用计算机视觉技术进行棉花植株含水量预测的精度。研究结果表明,由灰板校正前、后颜色特征值G-B建立的最佳预测模型,决定系数分别为0.746和0.782。有效性检验结果表明,灰板校正前、后计算预测值与实测值的决定系数分别为0.739和0.783;RMSE分别为2.218和2.03,RE分别为2.13%和1.79%。基于计算机视觉提取的冠层图片颜色特征值能够预测植株含水量,应用灰板校正颜色特征值能够提高模型预测精度,可为提高计算机视觉预测植株水分状况的精度提供技术支撑和方法补充。     

盘锦冬季日光温室光合有效辐射预报模型研究

为了探索盘锦地区冬季日光温室光合有效辐射变化规律,更好地为本地区设施农业服务,利用2012 年冬季日光温室内小气候和附近气象站观测资料,采用相关统计和逐步回归分析方法分析了冬季不同天气类型日光温室中光合有效辐射特征及光合有效辐射占太阳总辐射的比值,建立了冬季不同天气类型日光温室光合有效辐射的预报模型,并对其进行拟合检验。结果表明：（1）晴天和多云天日光温室内PAR具有明显的日变化。阴天时日光温室内接受到的PAR 最大值一般在1~38 W/m2。（2）冬季典型多云天ηPAR最高,阴天次之,晴天最低。（3）采用逐步回归分析方法分别建立日光温室内日最高光合有效辐射、日光合有效辐射总量、日最大总辐射、日总辐射总量与外界气象要素的相关模型均通过了0.01 的显著性水平检验,并进行了拟合检验,晴天和多云天4个要素的拟合效果较好,阴天4个要素的拟合效果较差。     

对两个亚热带优质蛋白玉米群体的适应性混合选择研究——Ⅰ.开花期性状的直接选择响应

用混合选择法改良亚热带优质蛋白玉米(QPM)群体在我国北方长日照条件下的适应性。经过4轮选择,中群13和中群14两个群体在北京三年试验的平均抽丝日期分别从85.1和86.9天缩短为67.5和68.8天,平均每轮提早4.1和4.5天。散粉日期的变化幅度较小,平均每轮提早2.2和2.3天。由于这两个性状的选择响应有差异,使散粉至抽丝的间隔天数(PSSl)分别从11.2和12.2天缩短为2.4和2.5天,平均海轮缩短2.0和2.3天,大大改善了雌雄协调性。1991年在北京春播,三亚秋播和济南、武功、成都夏播所做的多点联合评价试验表现相同的趋势,两个群体的抽丝日期平均每轮提早2.0和1.6天,PSSI则平均每轮缩短1.11和0.97天。在北京长日照条件下积累的改良效果,在短日照和夏播条件下仍然表现极显著的选择响应。这表明,混合选择法是改良外来玉米种质适应性,提早开花和改善雌雄协调性的有效途径。     

基于支持向量机的北京市湿地变化预测研究

为了实现北京市湿地的可持续发展与科学管理,利用遥感和GIS技术对北京区域遥感数据进行分析,进而获取湿地不同类型数据,由于湿地面积是典型的小样本数据,将支持向量机引入到时间序列模型定阶的方法中,然后采用K交叉验证方法寻找最优参数,建立北京湿地变化预测模型。通过对北京湿地历年数据进行模拟,并与RBF神经网络的预测模型作比较来验证SVM预测模型的有效性,运用此模型预测北京湿地未来的变化。结果表明：时间序列模型预测湿地变化有较高的预测精度和较强的泛化能力。预测结果显示：北京湿地在未来几年内,水库、河流,运河,沟渠面积将逐年减少,水稻田面积将持续下降,养殖面积将增大。其预测结果符合现实北京湿地变化趋势,研究结果为北京湿地的可持续发展和科学管理提供了依据。     

基于SEBAL模型的北京市日蒸散发区域分布规律

为了对北京市地表水转换过程中的分量-蒸散发进行定量研究，基于Landsat7 ETM+遥感影像信息并结合气象数据，通过ERDAS构建了SEBAL模型，并通过模型计算得到北京市2014 年7 月26 日的平均蒸散发为2.49 mm，同时利用彭曼公式和MOD16 产品数据对SEBAL 反演结果的可靠性进行验证。结果表明，通过SEBAL 模型计算得到的蒸散发与彭曼公式法和MOD16 数据产品的误差分别为3.2%和3.3%，其结果具有一定的可靠性，且通过Landsat7 数据反演具有数据获取便捷、空间分辨率高的优点。通过对比各区域蒸散发分布，得出北京市蒸散发整体呈现西北山区高、东南平原低的趋势，西北山区林草植被覆盖率较高是导致这一趋势的主要原因。通过统计分析，水域的蒸散发最高，硬化面积及建筑物的蒸散发接近于0，在除去水体及硬化面积后，蒸散发的大小与NDVI呈现极显著的正相关关系，两者的决定系数达到0.9233，故下垫面类型是影响某一时刻区域蒸散发大小的主要因素之一。     

利用EPIC模型模拟北京春播紫花苜蓿的当年生长

本研究利用EPIC模型对北京顺义地区的春播紫花苜蓿当年生长中的地上部生物量的累积和刈割进行了模拟。结果表明,EPIC模型可以较好的模拟地上生物量累积;在对刈割的模拟中,地上部生物量和产量的模拟结果可以接受,但对于留茬的模拟结果不理想。     

Obtaining Outdoor Illuminance Values with Solar Irradiation Transformation Models

Daylighting is one of the important aspects of sustainable building, but architectural daylighting in China is obstructed because of shortage of daylight meteorological measurement record. However, there are many data of solar irradiation. Therefore solar irradiance values are used to calculate outdoor illumination values. Luminous efficacy is introduced to show the relation between solar irradiance and outdoor illumination. Sunny index is used to represent the meteorological states of the sky. On the basis of measurement data in Chongqing from 1991 to 1992, new luminous efficacy calculation model is built to obtain the outdoor global illuminance values and the diffuse illuminance values. Measurement data in Chongqing in 1993 is used to evaluate the proposed mode, which shows the proposed models are reliable. In order to prove possibility of calculating illuminance in other places in China, the measurement data records of annually average global illuminance values in 32 cites are used to examine the calculation results. If the real-time solar irradiation data was input, the real-time illuminance values could be obtained with this model in China, thus millions of illuminance values could be used in future daylighting design.     

北京地区春季木本植物花粉起始期预报模型研究

为解决城市花粉期预报的问题,以北京城区春季榆科、柏科、杨柳科、松科4类主要的木本植物为研究对象,利用2012—2019年北京市气象局的花粉浓度观测数据,分别基于Spring Warming、Alternating、Sequential和Parallel 4种积温物候模型进行植物花粉期建模。模型结果表明,4类木本植物的花粉期起始日期均明显受到春化作用影响,即冬季的低温刺激会促使春季植物花粉期的提前。对比不同模型的结果认为,榆科、柏科、松科植物的最适模型为Alternating模型,RMSE介于1~3天,判定系数R²介于91%~95%;杨柳科植物的最适模型为Sequential模型,RMSE小于2天,判定系数R²为92.8%。说明基于积温原理的物候模型,能够较为准确地模拟北京地区春季木本植物的花粉起始期,对于植物物候期的模拟研究具有参考意义。     

玉米种子萌发相关性状的全基因组关联分析

种子萌发是出苗的前提, 对玉米产量影响重大。为了解玉米种子萌发相关性状的遗传机制, 本研究对476份玉米自交系种子萌发相关的6个性状进行调查, 结合125万个(1.25M) SNP标记, 利用3种统计模型(Q, K, Q+K)进行全基因关联分析(GWAS)。结果表明K模型能够较好地评价吸胀前重量、吸胀前体积、吸胀后重量、吸胀后体积和吸胀体积5个性状; Q+K模型能更好地评价吸胀重量性状。基于这6个性状的最优模型的GWAS结果, 共检测到15个种子萌发相关性状的显著SNP, 15个SNP对应6个QTL, 集中分布在玉米第3、第6、第7和第10染色体上, QTL内单个SNP能解释的表型变异为5.09%~7.85%。其中5个QTL可在多个生物学重复中被检测到。以最显著SNP所在基因或附近基因作为QTL的候选基因, 共筛选到6个最可能的候选基因。GRMZM2G148411是吸胀后重量、吸胀重量和吸胀体积3个性状共同鉴定到的QTL候选基因, 根据基因的功能注释, 该基因编码一个包含TLD-domain的钙离子结合蛋白, 可能是一种调控种子休眠与萌发的信号分子。本研究鉴定的QTL为解析玉米种子萌发的遗传机制和相应功能标记的开发奠定了基础。     

日光温室小气候要素预报模型研究

了解日光温室小气候要素变化规律,建立小气候要素预报模型,可以对日光温室资源合理开发,为日光温室小气候调控提供依据。应用辽宁省沈阳市东陵区日光温室暖棚内农田小气候观测仪采集的逐小时气温、相对湿度数据,将冬季、春季、秋季和晴天、多云、阴天几种情况进行组合,计算棚内日最高气温、日最低气温、日平均相对湿度,分析其变化规律,并利用自动气象观测站数据,建立基于逐步回归方法的预报模型。分析结果表明,日光温室内日最高气温和日最低气温呈现春季、秋季温度值接近,冬季明显低于春秋两季的特征;而冬季日平均相对湿度高于春秋两季。日最高气温具有显著的从晴天至多云至阴天减少的变化特征,日最低气温特征不如日最高气温明显;日平均相对湿度为从晴天至多云至阴天增加的变化特征。所建立的日光温室小气候要素逐步回归预报模型,均通过了显著性检验,相关系数为0.608~0.933,相对误差范围为0.1%~19.0%,相对误差平均值为2.7%~9.9%。     

基于高光谱数据的滴灌甜菜叶片全氮含量估算

本文旨在明确甜菜叶片全氮含量与高光谱地面植被遥感的定量关系,建立干旱区甜菜叶片全氮含量精确估测模型,及时监测甜菜生长状况。本研究选取新疆滴灌甜菜(Beta356)为材料,利用ASD野外高光谱仪在甜菜叶丛快速生长期、块根膨大期与糖分积累期采集各处理反射光谱,并同时测定全氮含量,分析原始光谱反射率及一阶微分光谱反射率与全氮含量的相关性,并进一步建立光谱特征参数与敏感波段植被指数全氮含量估算模型。结果表明,光谱特征参数Dr762幂函数下估算模型具有较好估算甜菜叶片全氮含量的能力,其决定系数R2=0.747,验证相对误差RE(%)为21.635,验证均方根误差RMSE为4.914;通过植被指数与叶片全氮含量建立多种函数估测模型,其中差值植被指数Dr762–Dr496下一元线性函数具有较好估算甜菜叶片全氮含量的能力,其决定系数R2=0.794,验证相对误差RE(%)为23.008,验证均方根误差为5.372。     

成都市秋桂开花期气象指标及预测

为开展成都市秋桂花期精细化气象服务,建立秋桂花期气象预测模式,本研究基于成都市2004—2016年桂花物候观测与气象资料,运用数理统计法开展成都市秋桂花前、花期与气象因子的关系研究,结合桂树生育特性建立秋桂始花期预测模型。结果表明：花前降雨充沛,5日滑动平均气温稳定通过23℃后,秋桂3~6天进入始花期;秋桂花期喜雨晴相间,花期日平均气温20~24℃,雨日、降水量、日照是影响花期长短的主要气象因子;秋桂始花早晚与2月下旬旬最高气温、旬日照时数和7月下旬雨日呈正相关;与10月下旬雨量、5月下旬雨日呈负相关。研究建立的成都市秋桂始花期预测模型经回代验证历史拟合率较高,具有较好的预报效果,能提前20天预测,可用于秋桂初花期中长期预报,为成都市桂花观赏提供精准化的气象服务。     

Modeling for recommending panicle nitrogen topdressing rates for yield and milled-rice protein content

This experiment was conducted to calibrate models for recommending panicle N fertilizer rate for target grain yield and milled-rice protein content based on not only rice growth and N nutrition status at panicle initiation stage (PIS) but also on weather conditions. Five rice cultivars; Chucheongbyeo, Daeanbyeo, Hwasungbyeo, Surabyeo, and Juanbyeo, were grown under various N fertilizer application rates. Shoot N accumulation at PIS (Pnup) was measured before panicle N application at PIS and at harvest. Grain yield, yield component, and milled-rice protein content were measured at harvest. Three models for prescribing panicle N fertilizer rate were calibrated by stepwise multiple linear regression (SMLR) analysis. The model for shoot N accumulation from PIS to harvest (PHnup) was calibrated using Pnup, panicle N application rate, and weather variables like air temperature and solar radiation. Models for grain yield and milled-rice protein content were calibrated using Pnup, PHnup, and weather variables. The models for PHnup, grain yield, and milled-rice protein content showed acceptable accuracy and precision with R² of 0.78, 0.85, and 0.77, respectively. The stability of the models was tested through the comparison of slopes between the observed and the predicted values in different conditions of temperature, radiation, and cultivar. The models for PHnup and grain yield showed homogeneity of slopes between the observed and the predicted values regardless of different temperature, radiation conditions, and cultivars. The model for milled-rice protein content showed homogeneity of slopes between the observed and the predicted values across low and high temperature and radiation conditions while the slopes were significantly different among cultivars. The oldest cultivar “Chucheongbyeo” being significantly different from the other four cultivars recently improved. In conclusion, the three models were precise and accurate enough to be used effectively for prescribing panicle N topdressing rate if Pnup could be measured timely with a cost-effective method.     

Geostatistical interpolation and aggregation of crop growth model outputs

Many crop growth models require daily meteorological data. Consequently, model simulations can be obtained only at a limited number of locations, i.e. at weather stations with long-term records of daily data. To estimate the potential crop production at country level, we present in this study a geostatistical approach for spatial interpolation and aggregation of crop growth model outputs. As case study, we interpolated, simulated and aggregated crop growth model outputs of sorghum and millet in West-Africa. We used crop growth model outputs to calibrate a linear regression model using environmental covariates as predictors. The spatial regression residuals were investigated for spatial correlation. The linear regression model and the spatial correlation of residuals together were used to predict theoretical crop yield at all locations using kriging with external drift. A spatial standard deviation comes along with this prediction, indicating the uncertainty of the prediction. In combination with land use data and country borders, we summed the crop yield predictions to determine an area total. With spatial stochastic simulation, we estimated the uncertainty of that total production potential as well as the spatial cumulative distribution function. We compared our results with the prevailing agro-ecological Climate Zones approach used for spatial aggregation. Linear regression could explain up to 70% of the spatial variation of the yield. In three out of four cases the regression residuals showed spatial correlation. The potential crop production per country according to the Climate Zones approach was in all countries and cases except one within the 95% prediction interval as obtained after yield aggregation. We concluded that the geostatistical approach can estimate a country’s crop production, including a quantification of uncertainty. In addition, we stress the importance of the use of geostatistics to create tools for crop modelling scientists to explore relationships between yields and spatial environmental variables and to assist policy makers with tangible results on yield gaps at multiple levels of spatial aggregation.     

四川不同生态区高产栽培条件下的杂交籼稻的稻米品质

郫县、汉源、射洪、邻水是四川具代表性的4个生态区,郫县位于成都平原区,土壤肥沃但受弱光限制;汉源位于攀西高海拔地区,温光充足;射洪位于川中丘陵区,受地形制约而气温日差较小;邻水则位于川东丘陵区,水资源缺乏且受干旱等灾害制约。本文以位于这4个典型生态区实施的水稻高产示范片为研究对象,分别对4个生态区及各生态区不同栽培方式、不同高产水平的杂交籼稻稻米碾米品质、外观品质、蛋白质含量、直链淀粉含量及淀粉RVA谱特征值进行比较研究。结果表明:(1)生态条件与稻米品质有密切关系,受气温和土壤肥力影响较大,郫县的稻米品质最优,邻水相对较劣;齐穗前后气温略高及较高的土壤全氮、全钾、速效磷含量有利于高碾米品质的形成;土壤全磷含量的降低可显著增加米粒长宽比;灌浆成熟期的高温会增加稻米的垩白粒率和垩白度,而土壤速效磷含量高则有利于降低垩白粒率和垩白度;灌浆结实期的高温也会降低稻米蛋白质含量;直链淀粉含量随土壤有机质含量的升高而升高;峰值黏度与土壤全钾含量显著负相关,崩解值与土壤全钾、速效磷显著负相关,还与齐穗前8~21 d的日最高气温显著正相关,回复值、峰值时间与齐穗前14~21 d日最高气温、抽穗至成熟期日最高气温呈显著或极显著负相关,与土壤碱解氮呈显著正相关。(2)各栽培方式间,机直播的碾米品质较优,优化定抛的直链淀粉含量较高,而机插的峰值黏度、崩解值较高,消减值较低,蒸煮食味品质较好。(3)高产及超高产田块的碾米品质整体较优,而外观品质和蒸煮食味品质相对较差。本研究可为四川杂交中籼稻高产优质栽培技术提供理论参考。     

Exploring opportunities for reducing complexity of genotype-by-environment interaction models

Heterogeneity in genetic effects among environments (G × E) is a common phenomenon in crop plants and can arise from heterogeneity in variance (scale effects) and/or crossover interaction. Here, a study of yield of macadamia progeny in 15 trials established at 9 locations and assessed for yield at 7 years is used to explore the impact on prediction of clonal values (additive + dominance effects) from (i) scaling observations by phenotypic standard deviation of each trial, and (ii) reducing complexity of the pattern of genotype-by-environment interaction. The initial fit of an unconstrained G × E model to unscaled observations indicated significant G × E, which was supported by the fit of the same model to scaled data. Scaling observations reduced heterogeneity of genetic parameter estimates among locations. Clustering of the additive and dominance genetic-by-environment covariance matrices from the fit of G × E models to scaled observations and log-likelihood testing was used to identify reduced models where locations with apparent homogeneous genetic effects (genetic variance not significantly different, and genetic correlations not significantly different from 1) were grouped into single environments. Complexity reduction condensed the additive genetic-by-environment covariance matrix to 3 environments, and 4 environments for the dominance matrix, and the accuracy of parameters estimates increased, although accuracy of prediction as assessed by generalised heritability only improved for a few locations. On the other hand, accuracies of clonal values predicted from a main effects only G + E model were lower. Nevertheless, correlations of the averages of predicted clonal values across locations from different models were very high suggesting models are robust to parameter estimates. These results support the use of scaling by the phenotypic standard deviation to reduce heterogeneity in parameter estimates, and complexity reduction to improve accuracy of estimating parameters required to predict genetic effects.     

Research on the Urban Agriculture Planning Models of Metropolis:A Case Study of Chengdu

With the accelerating urbanization, ecological environment of the city has attracted increasing attention, so the resulting problems have become key research focuses in all countries. Against this background, urban agriculture has been applied as one of the effective approaches for relieving urbanization. From the perspective of industrial form of urban agriculture, planning models of urban agriculture were explored, industrial form and planning model of Chengdu urban agriculture were analyzed to forecast its development prospects. Multi-dimensional development, and sustainable development measures were given to guarantee the sustainable development of urban agriculture.     

典型草原的光合有效辐射特征

为了合理利用太阳能和调整农牧业产业结构提供依据,利用2010年平均光合有效辐射(PAR)和太阳总辐射(Rs)资料,采用线性关系进行最小二乘拟合,分析该区的光合有效辐射特征。结果表明：典型晴天日和阴天日的PAR和Rs曲线变化趋势基本一致,且前者的值明显大于后者;PAR的月平均总量为8.15 MJ/m2,年总量为2983.1 MJ/m2,春、夏、秋、冬四季的平均日总量季节变化较明显,夏季最大,冬季最小;PAR/Rs晴天日的值明显小于阴天日,全年平均值为0.497,月平均值在0.422~0.544之间,最大值出现在夏末的8月,为0.544,最小值出现在冬季的1月,为0.42。PAR/Rs的变化幅度和当地的天气气候有关,受天空云、大气气溶胶、大气中水汽含量等因素的影响。