番石榴果实发育的初步研究

以东山月拔和二十一世纪这2个品种为试材，研究了番石榴（Psidium guajava L)果实的发育动态规律。结果表明：番石榴的果实发育呈现双“S”型；果实重量和果核重量的发育呈显著的正相关；推测果实发育后期为进行果实产期调控的关键时期；建议以果实发育的直径大小以及果实转蒂下垂作为确定进行产期调控的田间依据。     

实时荧光定量PCR构建绵羊PrP基因标准品质粒和标准曲线

羊痒病是一种传染性的致死性神经退行性疾病,常引起绵羊和山羊发病,该病在欧洲流行了大约250年,但是它的流行病学和传播机制还不是很清楚.正常的朊蛋白（PrPc）不能引起神经退行性病变,虽然目前已经对许多组织的PrP mRNA进行了检测,但是对它的生物学功能还知之甚少,对PrP基因表达的机制尚不清楚.研究显示,不同组织来源的细胞中朊蛋白的表达程度差异很大,主要出现于神经细胞中.PrPc在细胞中的高水平表达可促使PrPc向PrPsc转变,目前的研究中,对绵羊PrP mRNA的转录机制尚未阐释清楚.因此,对绵羊外周和中枢系统PrP mRNA的表达进行定量,有助于探讨各组织器官中的PrP在羊痒病的发生过程中的作用.     

Finding best exotic breed proportion in crossbred lactating sheep kept under farmers’ conditions in Ethiopia determined by use of nested Legendre polynomials with limited data

ABSTRACT

The present study was conducted to estimate milk production performance and fit lactation curves for groups of ewes of Local and of Awassi crosses, with a variable blood level, reared under farmer’s environment. The Weigh-Suckle-Weigh method plus hand milking was used to estimate milk yield for ewes. A total of 466 observations from 115 ewes were used. Estimated least-squares adjusted means for the milk production over 120 days were 0.56?kg day^?1 (Local), 0.67 (<30% Awassi), 0.86 (30–50% Awassi), and 0.96 (>50% Awassi). Groups with 30–50% Awassi and >50% Awassi ewes produced significantly (p?<?0.05) more milk than Local ewes. Significant differences were observed between <30% Awassi and >50% Awassi crossbred groups. The best crosses (>50% Awassi) produced over 70% more milk than the local ewes which demonstrates the potential that exists in increasing milk production through the initiated crossbreeding programme with sheep in Ethiopia.     

小兴安岭天然林不同树种的树高曲线模型

选用10种树高曲线模型作为候选模型,以决定系数(R~2)、残差平方和(S_(se))和均方差(M_(se))作为模型优劣的评价指标,对小兴安岭天然林中的云杉(Picea asperata)、红松(Pinus koraiensis)、水曲柳(Fraxinus mandschurica)、椴树(Tilia tuan)4种树种的树高曲线模型进行优选。结果表明:云杉、红松和椴树的最优模型均为Logistic模型,水曲柳的最优模型为抛物线模型;云杉和红松两种针叶树种,最优模型的优势不明显,水曲柳和椴树两种阔叶树种最优模型的优势较明显;比较R~2的大小,得出较适合小兴安岭云杉和红松两种针叶树种的树高曲线模型(R~20.8),对小兴安岭阔叶树种的适用程度不具有普遍性,对椴树的适用性好(R~2最大达0.94),对水曲柳的适用性较差(R~20.8)。对水曲柳的树高进行分段研究得出:水曲柳在树高低于9 m时,树高曲线模型较适宜(R~20.8),其中抛物线模型为最优模型;树高较高时,没有适用的树高曲线模型。     

东北地区春玉米临界氮浓度稀释曲线的建立和验证

过量施氮是目前玉米栽培中存在的普遍现象,基于临界氮浓度稀释曲线计算得出的氮营养指数是诊断氮营养丰缺的重要手段。基于东北地区4个生态点的试验数据,构建了东北地区春玉米临界氮稀释曲线,并在此基础上建立了氮营养指数模型和需氮量模型,结果表明,东北地区春玉米地上部临界氮浓度与生物量符合幂函数关系。利用独立试验资料对建立的临界氮浓度稀释曲线进行检验,发现基于临界氮浓度稀释模型计算的氮营养指数可以准确诊断玉米植株的氮营养状况,并计算出实时的氮素需求量。该研究建立的东北地区春玉米临界氮稀释模型可以为该地区春玉米的氮营养诊断和动态调控提供较好的理论和技术指导。     

一种改进的开关磁阻电机磁链模型

开关磁阻电机(SRM)特殊的结构使建立其磁链模型比较困难。根据SRM运行的周期特点,从数学角度用傅里叶级数模型对其进行解析,通过权系数将傅里叶级数模型与传统指数模型结合,得到一个新的改进模型。用提出的改进模型与指数函数模型、傅里叶级数模型分别对Ansoft Maxwell仿真得到的磁链数据进行拟合。对比解析结果,证明提出的改进模型具有更高的解析精度,适合解析磁链。     

超甜玉米子粒果皮柔嫩度的变化规律

为了探讨超甜玉米果皮柔嫩度在子粒发育进程中的变化规律,以10份超甜玉米自交系为材料,采用硬度计法测定子粒发育过程中果皮柔嫩度值,分析果皮柔嫩度在不同环境条件下的变化。结果表明,10份参试材料在果皮柔嫩度上存在梯度差异,其中PE10果皮柔嫩性最好,T105中等,S33205最差;在湖北武汉(2014年春)、海南陵水(2014年冬)两种环境下,在授粉后第12~24天,PE10、T105、S33205的果皮柔嫩度值均呈上升趋势,且各测定时间点的柔嫩度均值由大到小的顺序均为S33205、T105、PE10;随着子粒的发育,相同材料在不同环境条件下果皮柔嫩度差异呈现先增大后缩小最后又趋于一致的规律;2014年湖北武汉春季与海南陵水冬季相比,同一材料最适采收期相差4 d,但最适采收期的果皮柔嫩度值差异不显著,说明环境改变会影响果皮嫩度变化速率,但果皮柔嫩度的好坏本质上仍决定于材料本身。     

黄河未来输沙量态势及其适用性对策

[目的] 探索黄河输沙预测的新思路，预估黄河未来输沙态势与输沙量水平，为黄河流域生态治理规划提供参考。[方法] 结合黄河流域水土保持生态修复现状，采用单累积曲线法、滑动平均及频率分析方法，分析1950—2019年黄河主要来沙区间的实测输沙量变化特征及其未来态势。[结果] 1950—2019年黄河输沙量呈现阶梯式减少。1950—2019年黄河中游各站累积实测输沙量随时间的变化可用“左半抛物线”表征。黄河输沙量自1997年以来已进入相对稳定态势，目前已达企稳状态；黄河潼关站未来年输沙量在90%频率下为1.00×10⁸ t左右，在10%频率下为5.00×10⁸ t左右，未来多年平均输沙量为1.40×10⁸ t。[结论] 为了维持黄河输沙量低稳状态，提升水土保持措施质量与标准，补齐“后水土保持”短板，构建完善的水沙关系调控体系，维持黄河下游河道冲淤平衡，是黄河流域生态保护与高质量发展的保障。     

Atmospheric humidity and genotype are key determinants of the diurnal stomatal conductance pattern

Great understanding of the genotypic difference in diurnal stomatal conductance (g_s) pattern and the key determinants of the pattern is important for saving water by adopting cultivars appropriately. Fifteen wheat genotypes were studied under different soil conditions and various meteorological conditions with pot cultivation in rain shelter for two years. Genotype and air humidity were found to be key determinants of diurnal g_s pattern. All genotypes under low relative humidity (LRH) and most genotypes under high relative humidity (HRH) displayed a gradual decline pattern from morning through the afternoon. Under moderate relative humidity (MRH), all genotypes present a single-peak curve pattern, but they differed in peak time, which may lead to unreliable g_s comparison between genotypes and get ostensible contrasting materials. The stomatal conductance was significantly different among genotypes under LRH and the increased g_s magnitude is also significantly different when it was compared between LRH and HRH. The present results provide new thinking for selecting and adopting appropriate cultivars with specific stomata traits for the area with various meteorological conditions.     

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.