基于深度学习算法的京津冀地区综合干旱评估模型构建

及时准确的干旱评估对社会经济发展和农业生产具有重要的指导意义,当前的干旱评估指标通常仅考虑植被或降水等单方面影响因素,在实际干旱评估中存在一定的局限性。本研究综合考虑降水、温度、地形等多个干旱致灾因子,以主要产粮基地京津冀地区为例,基于2007-2017年地表温度（Land Surface Temperature,LST）、归一化植被指数（Normalized Difference Vegetation Index,NDVI）以及降水等多源数据,利用深度学习框架Tensorflow构建以标准化降水蒸散发指数（Standardized Precipitation Evapotranspiration Index,SPEI）为目标值的综合干旱评估模型。利用决定系数（R2）和均方根误差（RMSE）对模型进行测试;利用站点标准化降水指数（Standardized Precipitation Index,SPI）、土壤相对湿度数据以及2016年京津冀地区的气象灾害数据,从时间和空间上对模型的可靠性进行验证。结果表明：模型的训练集和测试集在不同月份上均表现较好（R2均大于0.5而RMSE均小于0.55）。模型输出的综合干旱指数（Comprehensive Drought Index,CDI）在密云站上与SPI和SPEI接近,变化趋势基本一致,并且与站点SPI和土壤相对湿度的相关系数分别大于0.7和0.4,均通过了0.01水平的显著性检验。空间上,相较于SPEI,CDI计算的2016年3-7月京津冀地区干旱事件结果与实际情况符合度更高,表明该模型适用于京津冀地区干旱评估。     

塑料连栋温室黄瓜生长温度数学模型的研究

为提高塑料连栋温室黄瓜的栽培水平,以能量平衡理论为分析平台,将温室中的空气温度拟合于栽培环境模型中,运用MATLAB程序模拟,并以试验验证模型。结果表明,该模型物理意义明确,便于数值模拟,且模拟结果与试验吻合好。就温室内5月份空气温度模拟而言,回归直线拟合度高,R2=0．8999,绝对误差在±0．85℃之内,平均相对误差9．1％。对回归方母=ax＋b,a与b的标准误差Sa=0．0352〈a／2,Sb=0．1053〈b／2。     

不同采收时期吴茱萸果实活性成分变化研究

采用HPLC法同时精密测定江西省吴茱萸规范化种植基地的吴茱萸果实在不同采收时期果实内吴茱萸内酯、吴茱萸碱和吴茱萸次碱3种有效成分含量。结果表明:吴茱萸果实中吴茱萸内酯、吴茱萸碱和吴茱萸次碱的含量在不同采收时期存在较大差异,呈现出在采收初期含量快速增加,随后开始逐渐降低的变化规律。确定江西省吴茱萸果实的最佳采收期为8月初。     

党参种子的离散元仿真参数标定与试验验证

为设计及优化党参机械化播种设备,提供基础仿真参数,本文对甘肃省种植的两种党参种子(渭党1号和甘党2号)通过试验法确定其基本物理参数(形状尺寸、质量密度、体积密度、千粒重、含水率)和接触力学参数(恢复系数、静摩擦系数);通过斜面滚动试验结合EDEM仿真,预测党参种子与ABS塑料板间的滚动摩擦系数;通过调整党参种子模型间的...     

A comparative study on Striga hermonthica interaction with a sensitive and a tolerant sorghum cultivar

In this study, the effects of Striga hermonthica (Del.) Benth. on a sensitive and a tolerant sorghum genotype were investigated, and the underlying tolerance mechanisms were distinguished. The sensitive sorghum cv. CK60-B and the tolerant sorghum landrace Tiemarifing were grown in pots with and without seed infestation. Both sorghum genotypes responded to infection by the parasite, but it was evident that CK60-B was more strongly affected than Tiemarifing. Sorghum plant height, final leaf number, green leaf area, kernel yield, number of kernels and 1000-kernel weight were significantly reduced by infection, which also had a marked effect on the phenological development of CK60-B; the majority of the plants remained vegetative and, in the remaining plants, flowering was delayed by about 2 weeks. No effect on the phenological development of Tiemarifing was observed. The tolerant landrace showed significantly lower and delayed emergence of S. hermonthica than the sensitive cultivar, and this could be explained by a delay in the onset of attachment. Significantly higher numbers of reproductive parasitic plants were found in the pots with the sensitive sorghum plants. It is concluded that differences in root architecture and the resulting early infection and higher S. hermonthica numbers are partly responsible for the stronger effects of the parasite on the sensitive cultivar.     

气候变化条件下木瓜秀粉蚧在中国的潜在适生区预测

为明确木瓜秀粉蚧Paracoccus marginatus Williams et Granara de Willink 1922在中国的潜在适生区,基于中国820个气象站点的气象数据和未来气候变化数据,结合木瓜秀粉蚧的生物学特性,利用CLIMEX模型对该虫在中国当前气候以及未来气候条件下的潜在适生区进行预测。结果显示,木瓜秀粉蚧在中国的潜在适生区主要在南方,适生区面积占全国陆地总面积的9.07%。高适生区主要包括海南省、广东省南部、广西壮族自治区南部以及福建省和云南省小部分地区。在未来气候条件下,2050年木瓜秀粉蚧的潜在适生区将进一步扩大,适生区面积所占比例将增加至15.46%,且有向北移动的趋势。表明木瓜秀粉蚧对中国南方地区的农业潜在威胁巨大,建议将该虫增补为检疫对象,并加强检疫监管和种群动态监测。     

Host status and reaction of <Emphasis Type="Italic">Medicago truncatula</Emphasis> accessions to infection by three major pathogens of pea (<Emphasis Type="Italic">Pisum sativum</Emphasis>) and alfalfa (<Emphasis Type="Italic">Medicago sativa</Emphasis>)

Ditylenchus dipsaci, the stem nematode of alfalfa (Medicago sativa), Mycosphaerella pinodes, cause of Ascochyta blight in pea (Pisum sativum) and Aphanomyces euteiches, cause of pea root rot, result in major yield losses in French alfalfa and pea crops. These diseases are difficult to control and the partial resistances currently available are not effective enough. Medicago truncatula, the barrel medic, is the legume model for genetic studies, which should lead to the identification and characterization of new resistance genes for pathogens. We evaluated a collection of 34 accessions of M. truncatula and nine accessions from three other species (two from M. italica, six from M. littoralis and one from M. polymorpha) for resistance to these three major diseases. We developed screening tests, including standard host references, for each pathogen. Most of the accessions tested were resistant to D. dipsaci, with only three accessions classified as susceptible. A very high level of resistance to M. pinodes was observed among the accessions, none of which was susceptible to this pathogen. Conversely, a high level of variation, from resistant to susceptible accessions, was identified in response to infection by A. euteiches.     

小麦生长模型WCSODS在河南的应用研究（征文）

基于WCSODS的需求，分别设置了播期和氮肥试验，调试了小麦品种参数，检验了WCSODS在河南麦区的应用效果。结果表明： 1) WCSODS系统对河南麦区小麦生育期和产量的模拟精度较高，全生育期模拟值与实际观测值仅相差1～2d，拔节期和抽穗期模拟相差较大，分别为4～6d和2～5d，产量模拟相差4.5～20kg/667m2; 2)WCSODS以绿叶分配指数和地上部干重为基础，对小麦叶面积指数的变化动态进行模拟，它从方法上避免了因对叶面积定量计算而造成的误差，同时也考虑了叶面积指数的增大对茎蘖动态的限制，涵盖了不同茎蘖能力的小麦品种，具有较好的通用性。结果显示其对叶面积、茎蘖数及干物重的模拟值与实测值比较吻合，相关系数达到0.9877～0.9995；3)WCSODS需要改进的问题是没有考虑氮肥胁迫对小麦生长发育的影响。     

基于Landsat的高山松地上生物量动态变化估测模型构建

以香格里拉市高山松为研究对象,基于1987—2017年的国家森林资源清查固定样地和对应年的Landsat TM/OLI数据提取对应的遥感因子,计算30 a期间生物量和遥感因子的5、10 a定期变化量、年平均变化量、5、10 a变化率;采用多元线性回归（MLR）和随机森林（RF）方法构建地上生物量模型,提高高山松森林AGB动态变化遥感估测的精度。结果表明：基于5种变化量类型的RF模型效果均优于相应的MLR模型,RF模型中采用5 a变化率效果最好,其拟合R²为0.956,RMSE为0.664 t/(hm²·a),预测结果中RMSE为2.285 t/(hm²·a);纹理因子在高山松地上生物量变化量建模中贡献最大。采用遥感因子变化率构建的高山松地上生物量动态变化估测模型,提高了生物量变化的估测精度,可为森林地上生物量的动态估测研究提供参考。     

Prediction of irrigation return flows through a hierarchical modeling approach

The quantity of water available for irrigation is getting scarce in many countries and it assumes great importance for assured crop production, especially in view of the erratic behavior of the monsoon. Thus, there is a pressing need to improve the water efficiency of irrigation systems. One-way of improving the efficiency of the irrigation system is reusing the return flow from the irrigation system. This task requires quantification of return flow, which still remains as a grey area in irrigation water management. The estimation of return flow from the irrigation system is usually obtained using thumb rules depending upon the site-specific conditions like command area conditions and soil properties. In this paper, a hierarchical modeling technique, namely, regression tree is developed for return flow estimation. Regression tree is built through binary recursive partitioning. The effective rainfall, inflow, consumptive water demand, and percolation loss are taken as predictor variables and return flow is treated as the target variable. The applicability of the hierarchical model is demonstrated through a case study of Periyar-Vaigai Irrigation System in Tamil Nadu, India. The model performance shows a good match between the simulated and the field measured return flow values. Results of statistical analysis indicated that the correlation coefficients are high for both single as well as double crop seasons.