Soil water response to precipitation in different microtopographies on the semi-arid Loess Plateau,China

Soil water is an important factor restricting afforestation on the semi-arid Loess Plateau.The microtopography of the loess slope has changed the distribution pattern of soil water on the slope.To improve water utilization efficiency and optimize afforestation configuration patterns,the relationship between soil water and precipitation at micro-topographic scale must be studied.We used time series analysis to study the temporal variation of soil water and its response to precipitation in four kinds of micro-topographies and undisturbed slope on loess slopes.Micro-topographies significantly influenced soil water distribution and dynamics on the slopes.Soil water stored in the platform,sinkhole,and ephemeral gully influenced subsequent soil water for 4 weeks,whereas soil water stored in the scarp and undisturbed slope could influence soil water for 2 weeks.It took 12 weeks,10 weeks,18 weeks,6 weeks,and 12 weeks for precipitation to reach the deeper soil layer in the platform,sinkhole,scarp,ephemeral gully,and undisturbed slope,respectively.These soil water characteristics in different micro-topographies are vital factors that should be taken into consideration when undertaking afforestation on the Loess Plateau.     

Simulation modelling of potato virus Y spread in relation to initial inoculum and vector activity

Potato virus Y(PVY) is a non-persistent virus that is transmitted by many aphid species and causes significant damage to potato production. We constructed a spatially-explicit model simulating PVY spread in a potato field and used it to investigate possible effects of transmission efficiency, initial inoculum levels, vector behavior, vector abundance, and timing of peak vector activity on PVY incidence at the end of a simulated growing season. Lower PVY incidence in planted seed resulted in lower virus infection at the end of the season. However, when populations of efficient PVY vectors were high, significant PVY spread occurred even when initial virus inoculum was low. Non-colonizing aphids were more important for PVY spread compared to colonizing aphids, particularly at high densities. An early-season peak in the numbers of noncolonizing aphids resulted in the highest number of infected plants in the end of the season, while mid-and late-season peaks caused relatively little virus spread. Our results highlight the importance of integrating different techniques to prevent the number of PVY-infected plants from exceeding economically acceptable levels instead of trying to control aphids within potato fields. Such management plans should be implemented very early in a growing season.     

Is it possible to differentiate between environmental and fishery effects on abundance‐biomass variation? A case study of blackspot seabream (Pagellus bogaraveo) in the Strait of Gibraltar

We assessed the potential for simulation and modelling of the blackspot seabream (Pagellus bogaraveo) population in the Strait of Gibraltar to discriminate the environmental effects of fishery impacts. A discrete biomass–abundance dynamic model was implemented to obtain a simulated monthly time series of blackspot seabream biomass. On this simulated time series, autoregressive integrated moving average (ARIMA) models were fitted. The best ARIMA fit provided a significant correlation of 0.76 and persistence index higher than 0.85. The proportion of variance non‐explained by the ARIMA models was correlated with a time series of sea surface temperature (SST) and North Atlantic Oscillation (NAO). The analysis of global, annual and winter correlation between the proportion of variance not explained by the ARIMA models and environmental variables showed that significant associations were not detected over the full time series. Our analysis therefore suggests that overexploitation is the main factor responsible for the commercial depletion of blackspot seabream in the Strait of Gibraltar.     

运用植被指数时序特征对落叶松人工林分类

为探究植被指数时序特征是否有利于落叶松人工林提取,以孟家岗林场为研究试验区域,根据落叶松人工林季相和物候特征,利用Landsat8OLI影像数据提取研究区内5种植被的归一化植被指数(I NDV)、差值植被指数(I DV)、比值植被指数(I RV)、增强型植被指数(I EV),构建相应的植被指数时序特征。采用最大似然和随机森林两种方法对单一时相影像和加入植被指数时序特征的影像进行对比试验。结果表明:影像中加入植被指数时序特征后,最大似然算法的分类总体精度为89.53%,Kappa系数为0.87,比单一时序特征的影像分类精度提高了13.35%;随机森林算法的森林类型分类总体精度为93.22%,Kappa系数为0.92,比单一时序特征的影像分类精度提高了19.8%。因此,加入植被指数时序特征后能得到更高的落叶松人工林提取精度。     

Panax notoginseng saponins suppress oxygen-glucose deprivation/reoxygenation-induced pyroptosis of SH-SY5Y cells

AIM To investigate the effect of Panax notoginseng saponins (PNS) on pyroptosis of SH-SY5Y cells induced by oxygen-glucose deprivation/reoxygenation (OGD/R). METHODS The OGD/R was conducted to induce ischemia/reperfusion injury in SH-SY5Y cells. The effects of PNS on the viability (detected by CCK-8 assay) and membrane permeability [indicated by lactate dehydrogenase (LDH) leakage and propidium iodide (PI) staining positive cell proportion] of OGD/R-induced SH-SY5Y cells were observed. The protein levels of gasdermin D (GSDMD), GSDMD N-terminal fragment (GSDMD-N), caspase-1 and caspase-4, and the release of interleukin-1β (IL-1β) and IL-18 in the cells were also determined. RESULTS After exposure to OGD/R, the viability of SH-SY5Y cells dramatically decreased (P<0.01), while the LDH leakage, the PI staining positive cell proportion, the protein levels of GSDMD, GSDMD-N, caspase-1 and caspase-4, and the release of IL-1β and IL-18 were significantly increased (P<0.01). However, PNS treatment enhanced the viability of SH-SY5Y cells inhibited by OGD/R (P<0.01), but reduced the leakage of LDH and the percentage of PI staining positive cells (P<0.05 or P<0.01). Moreover, PNS reversed the increases in the protein levels of GSDMD, GSDMD-N, caspase-1 and caspase-4 and the release of IL-1β and IL-18 in OGD/R-induced SH-SY5Y cells (P<0.05 or P<0.01). CONCLUSION Treatment with PNS alleviates OGD/R-induced injury in SH-SY5Y cells. Its mechanism may be related to inhibition of SH-SY5Y cell pyroptosis induced by OGD/R.     

新单系列玉米品种的遗传基础解析以及品质和产量性状变化趋势分析

为探索新单系列玉米品种籽粒品质性状之间的关系以及产量性状的变化趋势,以新乡市农科院2003年以来审定的玉米品种为材料,研究了它们的遗传基础、杂优模式、品质性状以及群体、个体生产力。结果表明：13个玉米品种利用的杂优模式主要有2种,9个品种杂优模式为改良Reid×唐四平头,4个品种为外来种质×唐四平头。品质分析中,‘新单28’、‘新单38’、‘新单66’粗淀粉含量高,‘新单61’、‘新单65’和‘新单68’的粗蛋白和赖氨酸含量高。粗脂肪含量和粗淀粉含量之间呈显著负相关,相关系数为0.610,粗蛋白含量和赖氨酸含量之间呈显著正相关,相关系数为0.491。产量分析表明,‘新单22’单株生产力最大,‘新单33’单株生产力最小,‘新单58’的群体生产力最大,‘新单28’的群体生产力最小。群体生产力随密度增加呈现上升趋势,其中密度为75000株/hm²时的群体生产力较45000株/hm²高62.9%,平均每公顷增加7500株产量增益为12.97%。单株生产力随密度增加开始呈下降趋势,增至60000株/hm²后逐渐平缓,低密度时单株生产力较高密度高5.5%。外来种质×唐四平头杂优模式选育的玉米新品种在品质上优于改良Reid×唐四平头模式选育的品种,且耐密性也显著增加,群体生产力也不断上升。     

Intercropping fenugreek (Trigonella foenum‐graecum L.) and barley (Hordeum vulgare L.) with and without biochar: Tests along a competition gradient

Integrating soil amendment biochar to legume‐based intercropping systems may amplify the intercropping benefits and lead to more sustainable production due to its positive effects on the soil physicochemical and biological environment. Fenugreek (Trigonella foenum‐graecum) is a legume used in an intercropping system in several countries in Southern Europe, the Middle East, and Asia. A barley cultivar and an Iranian fenugreek ecotype were studied in two replacement series experiments to find the best combination of the two species as well as the effect of adding biochar to the soil. Fenugreek and barley were grown in 4‐L pots in five density combinations (20:0, 15:5, 10:10, 5:15, 0:20) with and without application of biochar in sandy loam soil. The biomass, nitrogen (N) and carbon (C) amount of the two crops were measured fifty days after sowing, and the Relative Yield Total (RYT) was estimated. Our results showed that biochar application resulted in a higher total biomass, N and C amount in all combinations of fenugreek and barley. Total biomass was increased by biochar 19.2% when fenugreek was grown alone and 8.1 and 12.9% in series with 25 and 50% barley when biochar was added, respectively. Biochar increased dry matter, N and C accumulation in both crop species in the mixtures. An exception was the C amount of barley which was not influenced by biochar in intercropping. RYT values were largest for biomass, C and N amount in mixtures with 15 fenugreek plants per pot and 5 barley plants per pot corresponding to approximately 400 fenugreek plants per m mixed with 130 barley plants per m². Biochar application increased RYT of the total dry weight by 2.7 and 5.5% in mixtures of 25 and 50% barley plants, RYT of the total nitrogen by 0.8% in mixtures with 25% barley plants, and RYT of the total carbon by 2.7 and 6.6% in mixtures with 25 and 50% barley plants. The RYT values declined with increasing number of barley plants as a result of a less competitive ability of fenugreek when growing in high barley densities. The yield was highest with intercropping but monoculture of barley also resulted in high yields. The total highest yield was found when approximately 130 fenugreek plants per m² were mixed with 400 barley plants per m². Mixtures with 75% fenugreek and 25% barley obtained RYT values larger than 1 for biomass, carbon and nitrogen percentages.     

基于GF-1和Sentinel-2时序数据的茶园识别

由于茶园大多分布在地形复杂的山区,地块破碎,分布零散,形状差异大、植被混杂且茶园所处环境长期受到云雨的影响,增加了茶园遥感识别的难度与不确定性,针对这一问题,该研究提出了利用高分1号(GF-1)和哨兵2号(Sentinel-2)时序数据提取茶园的方法,以浙江省武义县王宅镇为研究区,采用GF-1号为主要数据源,并利用MODIS地表反射率产品和Sentinel-2反射率数据,基于时空融合算法得到时间分辨率5 d的10 m Sentinel-2完整的时序数据。综合利用GF-1在空间细节方面的优势和重建的Sentinel-2高观测频率时序数据在反映茶树生长过程方面的优势,分别基于GF-1的光谱和纹理特征及GF-1的光谱、纹理特征和Sentinel-2时序特征两种特征组合方式,采用随机森林算法提取茶园。结果表明,GF-1光谱、纹理信息结合Sentinel-2时序信息分类结果的准确率、错误率、精确率、召回率和F1分数分别为96.91%、3.09%、89.00%、83.09%和0.86,仅基于GF-1光谱和纹理信息的分类准确率、错误率、精确率、召回率和F1分数分别为94.72%、5.28%、73.09%、84.61%和0.78,添加时序信息分类结果总体优于未添加时序信息的分类结果。表明高空间分辨率结合高频率时序遥感数据是提高茶园分类精度的有效手段。     

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.