Mechanisation of organic fertiliser spreading,choice of fertiliser and crop residue management as solutions for maize environmental impact mitigation

The environmental impact of crop production is mainly related to fossil fuels consumption and to fertilisers application. Emissions arising from the spreading of organic and mineral fertilisers are important contributors for impact categories such as eutrophication and acidification. The choice of the fertilisers and of the spreading techniques as well as the crop residues management can deeply affect the environmental impact related to crop cultivation.In this study, seven scenarios describing fertilising schemes characterised by different organic and mineral fertilisers and by different mechanisation were compared. The aim is to evaluate, using the Life Cycle Assessment (LCA) method, how the environmental performances of grain maize production were affected by these different fertilisers schemes. The study was carried out considering a cradle to farm gate perspective and 1 t grain maize was selected as functional unit. Inventory data were collected on a farm located in Po Valley (Northern Italy) during year 2013 and were processed using the composite method recommended by the International Reference Life Cycle Data System (ILCD). The compared scenarios involved organic and mineral fertiliser distribution and were: pig slurry incorporation after >3 days after spreading (BS), fast pig slurry incorporation within 2 h from spreading (AS1), direct soil injection of pig slurry (AS2), pig slurry incorporation (after >3 days) with straw collection (AS3), digestate spreading instead of pig slurry (after >3 days) (AS4), only mineral fertilisers (i.e. urea and superphosphate) distribution (AS5) and only mineral fertilisers (i.e. calcium ammonium nitrate and superphosphate) distribution (AS6).The results were not univocal, since climate and soil conditions as well as physical and chemical fertiliser characteristics differently affected the environmental load, especially for particulate matter formation, terrestrial acidification and terrestrial eutrophication impact categories. AS1 and AS2 showed the most beneficial results for these impact categories (between ↙67% and ↙73% respect to worst scenario). AS6, on the opposite, showed the highest environmental impact for those impact categories mainly affected by energy and fossil fuel consumption (climate change, ozone depletion, human toxicity with carcinogenic effect, particulate matter, freshwater eutrophication, freshwater ecotoxicity and mineral, fossil and renewable resources depletion), categories on which AS3 and AS4 were the best solutions. AS3 was the most impacting for terrestrial acidification and eutrophicationA sensitivity analysis was carried out varying grain maize yield (mostly affected: marine eutrophication) and ammonia volatilisation losses due to organic fertilisers (mainly affected: terrestrial acidification and eutrophication).The achieved results can be useful for the development of ⬓spreading rules⬽ that drive the application of organic fertilisers in agricultural areas where there is an intense livestock activity.     

Environmental performances of giant reed (Arundo donax L.) cultivated in fertile and marginal lands: A case study in the Mediterranean

Perennial rhizomatous grasses (PRGs) tend to have a high yield combined with a low environmental impact. Cultivation in marginal or poorly cultivated land is recommended in order not to compromise food security and to overcome land use controversies. However, the environmental impacts of using different types of soil are still unclear. We thus assessed the environmental impact of two giant reed (GR) systems cultivated in a fertile soil (FS) and in a marginal soil (MS) through a cradle-to-plant gate LCA. We analyzed energy balance, GHG emissions (including LUC, not including iLUC), and the main impacts on air, water and soil quality. In both systems the annualized soil carbon sequestration was more than twofold the total GHG emitted, equal to −6464 kg CO₂eq ha⁻¹ in FS and −5757 kg CO₂eq ha⁻¹ in MS. Overall, soil characteristics affected not only GR yield level, but also its environmental impact, which seems to be higher in the MS system both on a hectare and tonne basis. The production of GR biomass in marginal soil could thus lead to higher environmental impacts and a more extensive land requirement.     

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。     

苹小卷叶蛾在6个苹果品种上的发育与繁殖

为探索不同品种苹果对苹小卷叶蛾生长发育和繁殖的影响,在温度(26±1)℃、相对湿度(80±5)%、光周期L∶D=16 h∶8 h的室内条件下,测定了苹小卷叶蛾在小国光、大国光、红玉、祝光、红星和金帅上的发育历期、存活率和产卵量,并组建了其各自的生命周期表。结果显示,苹小卷叶蛾在6个品种上的发育历期差异显著,全世代发育历期以小国光最短(33.95 d),以红玉最长(39.76 d);平均单雌产卵量以红玉最高(107.24粒),小国光次之(85.00粒);而存活率则无显著差异。生命表参数中净生殖率(R0)、内禀增长率(rm)和周限增长率(λ)均以小国光最高,世代平均周期(T)和种群加倍时间(Dt)以小国光最短,表明6种试验品种中小国光是苹小卷叶蛾最适宜的寄主品种。     

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.     

Energy use and greenhouse gas emissions from turf management of two Swedish golf courses

Turf management on golf courses entails frequent maintenance activities, such as mowing, irrigation and fertilisation, and relies on purchased inputs for optimal performance and aesthetic quality. Using life cycle assessment (LCA) methodology, this study evaluated energy use and greenhouse gas (GHG) emissions from management of two Swedish golf courses, divided into green, tee, fairway and rough, and identified options for improved management. Energy use and GHG emissions per unit area were highest for greens, followed by tees, fairways and roughs. However, when considering the entire golf course, both energy use and GHG emissions were mainly related to fairway and rough maintenance due to their larger area. Emissions of GHG for the two golf courses were 1.0 and 1.6 Mg CO₂e ha⁻¹ year⁻¹ as an area-weighted average, while the energy use was 14 and 19 GJ ha⁻¹ year⁻¹. Mowing was the most energy-consuming activity, contributing 21 and 27% of the primary energy use for the two golf courses. In addition, irrigation and manufacturing of mineral fertiliser and machinery resulted in considerable energy use. Mowing and emissions associated with fertilisation (manufacturing of N fertiliser and soil emissions of N₂O occurring after application) contributed most to GHG emissions. Including the estimated mean annual soil C sequestration rate for fairway and rough in the assessment considerably reduced the carbon footprint for fairway and turned the rough into a sink for GHG. Emissions of N₂O from decomposition of grass clippings may be a potential hotspot for GHG emissions, but the high spatial and temporal variability of values reported in the literature makes it difficult to estimate these emissions for specific management regimes. Lowering the application rate of N mineral fertiliser, particularly on fairways, should be a high priority for golf courses trying to reduce their carbon footprint. However, measures must be adapted to the prevailing conditions at the specific golf course and the requirements set by golfers.     

终身效益指数(LPI)及近五年加拿大荷斯坦牛群性状遗传增量

终身效益指数是加拿大选择公母牛的主要依据,对提高产奶量和奶品质及牛的强壮度具有重要意义。通过指数选择2010年加拿大的荷斯坦泌乳牛单产已超过9 700kg,乳脂率3.8%,乳蛋白率3.2%,体细胞数低于20万个/mL、细菌数3万以下,真正做到了优质高产。     

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。