花生黄曲霉生长预测模型的研究

通过对分离自花生的黄曲霉LYYSS03-3在不同温度(15-35℃)、不同相对湿度(水活度分别为0.5,0.7,0.9)下的菌落生长特性进行检测,采用Boltzmann和Logistic 模型对黄曲霉的生长曲线进行拟合,结果表明,在适宜温湿度阶段,花生黄曲霉的生长曲线更适合用Boltzmann模型拟合.     

土耳其斯坦裂体吸虫23kDa蛋白基因的序列分析及抗原表位预测

为研究土耳其斯坦裂体吸虫23 kDa蛋白的生物学特性,以土耳其斯坦裂体吸虫cDNA为模版,利用PCR对23 kDa基因进行扩增,并将其克隆到T-easy载体后进行序列测定。利用生物信息学对其结构、抗原指数进行分析,并对其抗原表位进行预测。序列分析结果表明,该虫体的23 kDa基因长度为657 bp,A+T含量为57.38%,与曼氏血吸虫、埃及血吸虫和日本血吸虫的23 kDa基因的相似性分别为85.24%、83.71%和81.89%。蛋白二级结构分析表明,23 kDa蛋白经过4次跨膜,主要由6个α-螺旋、3个β-折叠、7个β转角和若干个无规则卷曲构成。抗原表位预测结果表明,该蛋白有3个B细胞抗原表位。综合分析土耳其斯坦裂体吸虫23 kDa蛋白是一种较好的抗原分子,是土耳其斯坦裂体吸虫疫苗的重要候选分子。     

Soil enzyme activities during the 2011 Texas record drought/heat wave and implications to biogeochemical cycling and organic matter dynamics

Extreme droughts and heat waves due to climate change may have permanent consequences on soil quality and functioning in agroecosystems. During November 2010 to August 2011, the Southern High Plains (SHP) region of Texas, U.S., a large cotton producing area, received only 39.6 mm of precipitation (vs. the historical avg. of 373 mm) and experienced the hottest summer since record keeping began in 1911. Several enzyme activities (EAs) important in biogeochemical cycling were evaluated in two soils (a loam and a sandy loam at 0–10 cm) with a management history of monoculture (continuous cotton) or rotation (cotton and sorghum or millet). Samplings occurred under the most extreme drought and heat conditions (July 2011), after precipitation resulted in a reduction in a drought severity index (March 2012), and 12 months after the initial sampling (July 2012; loam only). Eight out of ten EAs, were significantly higher in July 2011 compared to March 2012 for some combinations of soil type and management history. Among these eight EAs, enzymes key to C (β-glucosidase, β-glucosaminidase) and P cycling (phosphodiesterase, acid and alkaline phosphatases) were significantly higher (19–79%) in July 2011 than in March 2012 for both management histories regardless of the soil type (P > 0.05). When comparing all sampling times, the activities of alkaline phosphatase, aspartase and urease (rotation only) showed this trend: July 2011 > March 2012 > July 2012. Activities of phosphodiesterase, acid phosphatase, α-galactosidase, β-glucosidase and β-glucosaminidase were higher in July 2011 than July 2012 in at least one of the two management histories. Total C was reduced significantly from July 2011 to March 2012 in the rotation for both soils. Only the activities of arylsulfatase (avg. 36%) and asparaginase showed an increase from July 2011 to March 2012 for both soil types, which may indicate they have a different origin/location than the other enzymes. EAs continued to be a fingerprint of the soil management history (i.e., higher EAs in the rotation than in monoculture) during the drought/heat wave. This study provided some of the first evidence of the adverse effects of a natural, extreme drought and heat wave on soil quality in agroecosystems as indicated by EAs involved in biogeochemical cycling.     

湖南省粮食产量波动的影响因素分析及预测

旨在维护国家稳定,为预判粮食生产前景、提高粮食生产效率、保障粮食安全提供理论依据。利用湖南省统计数据,运用灰色关联分析法筛选关联性较强的影响因素,并建立GM(1,N)预测模型预测粮食产量。2008—2017年与湖南省粮食产量关联度最大的影响因素是粮食作物播种面积和农业机械总动力;科技因素是影响2008—2017年湖南省粮食产量的主要因素,其次是自然因素,社会因素;2018—2027年湖南省粮食产量有较小波动,且农业机械总动力和财政农业支出影响较大;农业机械总动力在前后十年对粮食产量都有较重要的影响,越来越占据主导地位。粮食产量受国家政策的影响,受农业机械总动力影响最大,维持产量水平需高度重视农业机械化水平,稳步提高粮食作物播种面积。     

基于改进GM(1,N)模型的我国大豆价格影响因素分析及预测研究

大豆是我国重要的粮食作物和油料作物,其价格对于国民经济尤其是农业经济的影响意义深远。大豆价格的稳定对于我国大豆市场的健康发展有着重要的现实意义。在灰色理论的基础上,提出了一种改进GM(1,N)大豆价格预测模型,首先运用灰色关联分析法对我国大豆价格的影响因素进行分析,选择主要的影响因素;再将这些影响因素作为模型的相关因素变量,构建GM(1,N)大豆价格预测模型。采用2010-2015年的大豆数据进行实证研究,模型选取国内大豆自给量、世界大豆产量、国民消费价格指数、消费者信心指数4个变量作为相关因素变量;模型预测误差为2.10%,预测精度较高,能够较好地掌握大豆价格的变化规律,可以为大豆价格市场预测及国家宏观政策的制定提供理论指导。     

Analysis on Target Genes with Mutation in microRNA of Blue-shelled Chicken and White Leghorn

The study was conducted to explore the potential different characters between Blue-shelled chicken and White leghorn.Global genome microRNA was combined the identified microRNA with complementary lab-predicted microRNA.Then the two breed chicken's SNP data got by GGRS were mapped to the microRNA and focused on SNP that deliberately located in mature-microRNA.Bioinformatics method was adopted for target prediction on microRNA which had SNPs.By further gene enrichment analysis,the study found these genes enriched in 22 GO terms,10 KEGG pathways,and 3 IPA important networks.And they enriched in traits which associated with growth,such as mTOR signaling pathways,Wnt signaling pathways,growth hormone receptor networks and insulin-like growth factor Ⅰ receptor networks.And they also enriched in some laying traits,such as oocyte meiotic signaling pathways and progesterone mature oocytes signaling pathways.The methods and the results might provide references for further studies.     

Simulation of future dissolved oxygen distribution in pond culture based on sliding window-temporal convolutional network and trend surface analysis

Dissolved oxygen (DO) is a key ecological factor to measure the quality of water in the aquaculture. As the pond water body is affected by the breeding environment, the spatial distribution of DO shows a certain law in the entire pond. Therefore, to simulate the distribution of DO in aquaculture waters and grasp the temporal and spatial variation of DO is the key to achieving precise regulation of DO. For this purpose, this paper proposed a method for simulating the temporal and spatial distribution of DO in pond culture based on a sliding window-temporal convolutional network together with trend surface analysis (SW-TCN-TSA). This paper first utilized SW to construct DO data sets with different prediction durations, and then used the improved TCN model to realize one-dimensional time series prediction for DO at single monitoring point. Based on the prediction results of DO, a TSA method was performed on the predicted values of DO at the extreme moments of all discrete monitoring points, so as to realize the simulation of the temporal and spatial distribution of DO in the pond. Experimental results show that the SW-TCN model has better prediction performance for one-dimensional time series prediction of DO. Compared with traditional deep networks, such as CNN, GRU, LSTM, CNN-GRU and CNN-LSTM, the values of evaluation indicators (MSE, MAE and RMSE) have been greatly improved. In the process of trend surface fitting, all fitting R² of DO at different water depths are higher than 0.9, indicating that the TSA can accurately reflect the temporal and spatial distribution of DO. This method can provide a basis for the prediction and early warning of DO in the three-dimensional space of the pond and has high practicability in aquaculture.     

Mass balanced based LCA of a common carp-lettuce aquaponics system

An aquaponics system (AS) is an integrated system that combines a recirculating aquaculture system and a hydroponics system (HS). It is designed to recover nutrients released from fish and transfer them to plants to provide a system more environmentally-friendly than the two systems working separately. As a result, several AS are under development, but little information is available about their overall performances. The aim of this study was to assess nutrient-use efficiency and environmental impacts of an AS, specifically a common carp-lettuce AS located in a greenhouse. Nutrient budgets of nitrogen (N) and phosphorus (P) were calculated and Life Cycle Assessment (LCA) was performed for the AS and for a lettuce Individual Hydroponics System (IHS), similar to the HS of the AS, operating in the greenhouse at the same time. The experiment was performed over a 52-day cycle, which corresponds to the growing time required to harvest marketable lettuce. The nutrient budgets were well balanced, with 24.6% of the N unaccounted-for, most likely due to N2 gas emission, and 6.6% of the P unaccounted-for, most likely due to having underestimated the quantity of sediment. At the beginning of the experiment, N represented 55.9%, 37.1% and 0.1% of the total N input in the formulated feed, stocked fish and lettuce seedlings, respectively. At the end of the experiment, N represented 47.6% and 0.4% of the total N input in the harvested fish and lettuce, respectively. At the beginning of the experiment, P represented 56.94%, 40.20% and 0.03% of the total P input in the formulated feed, stocked fish and lettuce seedlings, respectively. At the end of the experiment, P represented 51.52% and 0.42% of the total P input in the harvested fish and lettuce, respectively. LCA clearly indicated two environmental impact hotspots: the origin of nutrients and energy use. One kg of lettuce growth in the AS clearly had lower environmental impacts than that in the IHS for climate change, acidification, eutrophication, land competition and cumulative energy demand; however, a decrease in water dependence was not observed. The indicator for net primary production use highlighted the dependence of the AS on natural resources, especially fish meal and fish oil. Compared to the use of chemical nutrients in the IHS, the use of nutrients from formulated feed in the AS decreased climate change impact but increased the use of natural resources.     

湖南洋泉水库调度的最优气候决策方法探讨

充分利用气候资源作好水库水位（量）调度、提高水库在抗旱和发电中的经济效益,是当今水库调度决策亟待解决的一个重要课题.本文根据气象经济学原理,运用连续函数求极值方法,利用洋泉水库有关经济参数,建立水库气候最优调度决策,在水库的实际调度中应用,可取得明显的社会经济效益.     

基于HHT变换的PSO-LSSVM耦合模型估算气象资料短缺地区ET_0

为准确估算气象资料短缺地区参考作物腾发量,构建了一种基于HHT变换的PSO-LSSVM耦合模型,并利用新疆和田气象站2000—2009年单日数据做训练、双日数据做验证。结果表明,该模型估算ET0方法明显优于常规的PSO-LSSVM和GRNN,预测精度较二者分别提高了15.7%~85.6%和15.8%~93.7%;该方法预测ET0的气象要素重要性为RsTmaxTminRHWn,利用该方法对气象要素组合为Tmax/Tmin/RH/Wn、Tmax/RH/Wn、Tmin/Wn、Wn条件下的ET0预测,MSE分别为0.407、0.185、0.149、0.135,说明该方法可以很好地估算资料缺失地区ET0。