Nondestructive Estimation of Standing Crop and Fuel Moisture Content in Tallgrass Prairie

Accurate estimation of standing crop and herbaceous fuel moisture content (FMC) are important for grazing management and wildfire preparedness. Destructive sampling techniques have been used to accurately estimate standing crop and FMC, but those techniques are laborious and time consuming. Existing nondestructive methods for estimating standing crop in tallgrass prairie have limitations, and few studies have examined nondestructive estimation techniques for FMC in this environment. Therefore, our objective was to develop robust models for nondestructive estimation of standing crop and FMC in tallgrass prairie. We calibrated and validated stepwise multiple linear regression (SMLR) and artificial neural network (ANN) models for standing crop and FMC using data collected in tallgrass prairies near Stillwater, Oklahoma. Day of year (DOY), canopy height (CH), Normalized Difference Vegetation Index (NDVI), and percent reflectance in five wavelength bands were candidate input variables for the models. The study spanned two growing seasons and nine patches located within three pastures under patch burn management, and the resulting data set with > 3 000 observations was split randomly with 85% for model calibration and 15% withheld for validation. Standing crop ranged from 0 to 852 g m^? 2, and FMC ranged from 0% to 204%. With DOY, CH, and NDVI as predictors, the SMLR model for standing crop produced a root mean squared error (RMSE) of 119 g m^? 2 on the validation data, while the RMSE of the corresponding ANN model was 116 g m^? 2. With the same predictors, the SMLR model for FMC produced an RMSE of 26.7% compared with 23.8% for the corresponding ANN model. Thus, the ANN models provided better prediction accuracy but at the cost of added computational complexity. Given the large variability in the underlying datasets, the models developed here may prove useful for nondestructive estimation of standing crop and FMC in other similar grassland environments.     

Fusing multi-source data to map spatio-temporal dynamics of winter rape on the Jianghan Plain and Dongting Lake Plain,China

Mapping crop distribution with remote sensing data is of great importance for agricultural production, food security and agricultural sustainability. Winter rape is an important oil crop, which plays an important role in the cooking oil market of China. The Jianghan Plain and Dongting Lake Plain(JPDLP) are major agricultural production areas in China. Essential changes in winter rape distribution have taken place in this area during the 21 st century. However, the pattern of these changes remains unknown. In this study, the spatial and temporal dynamics of winter rape from 2000 to 2017 on the JPDLP were analyzed. An artificial neural network(ANN)-based classification method was proposed to map fractional winter rape distribution by fusing moderate resolution imaging spectrometer(MODIS) data and high-resolution imagery. The results are as follows:(1) The total winter rape acreages on the JPDLP dropped significantly, especially on the Jianghan Plain with a decline of about 45% during 2000 and 2017.(2) The winter rape abundance keeps changing with about 20–30% croplands changing their abundance drastically in every two consecutive observation years.(3) The winter rape has obvious regional differentiation for the trend of its change at the county level, and the decreasing trend was observed more strongly in the traditionally dominant agricultural counties.     

Dynamic changes of root proteome reveal diverse responsive proteins in maize subjected to cadmium stress

Toxic symptoms and tolerance mechanisms of heavy metal in maize are well documented. However, limited information is available regarding the changes in the proteome of maize seedling roots in response to cadmium(Cd) stress. Here, we employed an i TRAQ-based quantitative proteomic approach to characterize the dynamic alterations in the root proteome during early developmental in maize seedling. We conducted our proteomic experiments in three-day seedling subjected to Cd stress, using roots in four time points. We identified a total of 733, 307, 499, and 576 differentially abundant proteins after 12, 24, 48, or 72 h of treatment, respectively. These proteins displayed different functions, such as ribosomal synthesis, reactive oxygen species homeostasis, cell wall organization, cellular metabolism, and carbohydrate and energy metabolism. Of the 166 and 177 proteins with higher and lower abundance identified in at least two time points, 14 were common for three time points. We selected nine proteins to verify their expression using quantitative real-time PCR. Proteins involved in the ribosome pathway were especially responsive to Cd stress. Functional characterization of the proteins and the pathways identified in this study could help our understanding of the complicated molecular mechanism involved in Cd stress responses and create a list of candidate gene responsible for Cd tolerance in maize seeding roots.     

Genetic dissection of hexanol content in soybean seed through genome-wide association analysis

Hexanol is a major compound contributing to the off-flavors(the bean-like odor) of soybean derived soymilk. The most effective way to reduce the off-flavors of soymilk is the screening and utilization of soybean cultivars with improved hexanol content. However, no genome-wide genetic analysis for this particular trait has been conducted to date. The objective of the present study was to dissect the genetic basis of hexanol content in soybean seed through genome-wide association analysis(GWAS). A total of 105 soybean accessions were analyzed for hexanol content in a three-year experiments and genotyped by sequencing using the specific locus amplified fragment sequencing(SLAF-seq) approach. A total of 25 724 single nucleotide polymorphisms(SNPs) were obtained with minor allele frequencies(MAF)5%. GWAS showed that 25 quantitative trait nucleotides(QTNs) were significantly associated with the hexanol concentration in soybean seed. These identified QTNs distributed on different genomic regions of the 15 chromosomes. A total of 91 genes were predicted as candidate genes underlying the seed hexanol level and six candidates were predicted possibly underlying the seed hexanol by gene based association. In this study, GWAS has been proven to be an effective way to dissect the genetic basis of the hexanol concentration in multiple genetic backgrounds. The identified beneficial alleles and candidate genes might be valuable for the improvement of marker-assisted breeding efficiency for low hexanol level and help to explore possible molecular mechanisms underlying hexanol content in soybean seed.     

Gene bank scheduling of seed regeneration: Interim report on a long term storage study

A major challenge for the management of gene banks is the maintenance of good seed health in the collections. Large germplasm collections 10 000 accessions often have been acquired from different sources over a range of dates, may differ in germination at time of deposition in the gene bank, and may have genetic differences in seed longevity. The major storage variables affecting seed longevity are temperature and seed moisture content. Two varieties of each pea(Pisum sativus L.), lentil(Lens culinaris Medikus subsp. culinaris), and chickpea(Cicer arietinum L.), were stored at three temperatures; 40, 20, and 2°C, each with three seed moisture levels of 10.9–13.8%(high), 7.9–10.3%(medium), and 7–7.8%(low), in the Australian Temperate Field Crops Collection gene bank. Seed longevity at a given storage period was estimated by the corresponding germination percentage for each treatment. This paper is an interim report on seed viability decline in the first seven years of this seed longevity study, in which viability decline towards zero was almost completed in the three seed moisture treatments at 40°C and the 20°C high seed moisture treatment, but had not declined in the other treatments. Seed longevity positively responded to a reduction in temperature and then to a reduction in seed moisture. The number of days in storage for seed germination decline to 85%(p85), and to 50%(p50) for mean seed viability, are reported by storage/varietal treatment. Both p85 and p50 showed significant inverse linear responses with seed moisture at 40°C for pea and lentil varieties, with intra-specific variation for pea. This long term trial aims to provide informed timing of seed regeneration for accessions in a gene bank.     

心理健康教育与大学生思想政治教育契合的可行性研究

心理健康教育与大学生思想政治教育在理论基础、学科体系、教育层次、教育内容、教育本质等五个方面存在共同点和内在的联系,这决定了二者在服务大学生全面成长的过程中能够而且应该相互融合、不可分割。     

青海白刺和枸杞微量元素的对应聚类分析

应用对应聚类分析对青海白刺和枸杞中微量元素的分布特征进行了研究。该方法可用于青海白刺和枸杞样品元素分析数据的直接处理,以深入研究这些样品的质量与它们的微量元素组成和样品来源的相关关系。实证分析结果表明,对应聚类分析能够揭示出样品来源与变量之间的内在联系,是一种有优势的分析方法。     

从心理创伤看张爱玲及其文学创作

在四十年代的上海,张爱玲红极一时,其作品备受追捧.作家生活在清末逐渐衰败的无爱家庭中,儿童及成年后的个人经历使其形成严重的心理创伤.本文以此为切入点,分析心理创伤对张爱玲及其文学创作呈现的苍凉风格及作品中女性悲剧主题的影响.     

西藏灌木林空间分布影响因素分析

以西藏主要类型灌木林为研究对象,基于全区2002年森林资源分布图,分析了影响西藏各主要类型灌木林空间分布的主要环境因子,提取了包括经度、纬度、海拔、坡向、坡位和坡度等6个环境因子的数据,并对数据进行梯度划分,应用多重对应分析方法,定量研究了环境因子对西藏各主要类型灌木林空间分布的影响程度,并进行了影响因子排序。研究结果表明,总体上看,西藏主要类型灌木林的空间分布均在不同程度上受大尺度环境因子的影响,主要表现在经纬度和海拔上;在小尺度上,各环境因子通常表现为共同影响灌木林的分布。     

张惠言词论的独特性

张惠言是常州词派的开山鼻祖,其词论在词史上的独特之处表现为:对词的美感特质有相当的体认与把握;因时乘势,力纠浙西、阳羡之流弊,使词走向健康的发展道路;其词论中含有浓厚的词史意识。