An economically based evaluation index for perennial and short‐term ryegrasses in New Zealand dairy farm systems

Grazed pastures based on ryegrass species provide most of the feed for dairy cattle in New Zealand. There are many cultivars of perennial (Lolium perenne), annual and Italian (L. multiflorum), and hybrid (L. boucheanum) ryegrasses available for dairy farmers to use in pasture renewal. This study describes an index which ranks ryegrass cultivars relative to a genetic base according to the estimated economic value (EV) of seasonal dry matter (DM) traits. A farm system model was used to derive EVs (Grazed pastures based on ryegrass species provide most of the feed for dairy cattle in New Zealand. There are many cultivars of perennial (Lolium perenne), annual and Italian (L. multiflorum), and hybrid (L. boucheanum) ryegrasses available for dairy farmers to use in pasture renewal. This study describes an index which ranks ryegrass cultivars relative to a genetic base according to the estimated economic value (EV) of seasonal dry matter (DM) traits. A farm system model was used to derive EVs ($ ha^?1 calculated as change in operating profit divided by unit change of the trait) for additional DM produced in different seasons of the year in four regions. The EV of early spring DM was consistently high across all regions, whereas EV for late spring DM was moderate to low. Genotype × environment analysis revealed significant reranking of DM yield among ryegrass cultivars across regions. Hence, separate performance values (PVs) were calculated for two mega‐environments and then combined with the corresponding season and region EV to calculate the overall EV for twenty‐three perennial ryegrass and fifteen short‐term ryegrass cultivars. The difference in operating profit between the highest ranked and lowest ranked perennial ryegrass cultivar ranged from $556 ha^?1 to $863 ha^?1 year^?1 depending on region. For short‐term ryegrasses used for winter feed, the corresponding range was $394 to $478 ha^?1 year^?1. Using PV for DM yield, it was estimated that plant improvement in perennial ryegrass has added $12–$18 ha^?1 year^?1 (depending on region) operating profit on dairy farms since the mid‐1960s.     

The efficiency of nitrogen in cattle manures when applied to a double‐annual forage cropping system

The use of cattle manure (CM) for fertilization presents challenges for optimizing nitrogen (N) use. Our work aimed to assess N efficiencies, in a 6‐year experiment with three biennial rotations of four crops: oat–sorghum (first year) and ryegrass–maize (second year) in a rainfed humid Mediterranean area of Spain. Fertilization treatments included the following: control (no N), 250 kg mineral N ha^?1 year^?1 (250MN), three CM rates (supplying 170, 250 and 500 kg N ha^?1 year^?1) and four treatments where the two lowest CM rates were complemented with either 80 or 160 kg mineral N ha^?1 year^?1. Treatments were distributed randomly in each of three blocks. Maximum dry‐matter yield (~44–49 t ha^?1 rotation^?1) was achieved in the third rotation, and only the control and the 170CM yielded significantly less. Within the limitations of the EU Nitrate Directive, the N steady state supply of 170CM always requires a complement of mineral N (80 kg N ha^?1) to maximize N agronomic efficiency. The maximum N‐fertilizer replacement value (250CM vs. 250MN) was 0·67, without significant differences between the two treatments in other N‐related efficiency indexes, which indicates that plants took advantage of residual‐N effects. Nitrogen losses by leaching in the 250CM treatment were around 5–7% of the N applied. This reinforces the sustainability of manure recycling in long cropping seasons.     

Artificial neural network modeling of microbial community structures in the Atlantic Forest of Brazil

Microbial communities vary across the landscape in forest soils, but prediction of their biomass and composition is a difficult challenge due to the large numbers of variables that influence their community structures. Here we examine the use of artificial neural network (ANN) models for extraction of patterns among soil chemical variables and microbial community structures in forest soils from three regions of the Atlantic Forest of Brazil. At each location, variations in soil chemical properties and FAME profiles of microbial community structures were mapped at 20 × 20 m intervals within 10 ha parcels. Geostatistical analyses showed that spatial variability in soil physical and chemical variables could be mapped at scale distances of 20 m, but that FAME profiles representing the microbial communities were highly variable and had no spatial dependence at the same scale in most cases. RDA analysis showed that FAME signatures representing different microbial groups were positively associated with soil pH, OM, P and base cations concentrations, whereas microbial biomass was negatively associated with the same environmental factors. In contrast, ANN models revealed clear relationships between microbial community structures at each parcel location, and generated verifiable predictions of variations in FAME profiles in relation to soil pH, texture, and the relative abundances of base cations. The results suggest that ANN modeling provides a useful approach for describing the relationships between microbial community structures and soil properties in tropical forest soils that were not able to be captured using geostatistical and RDA analyses.     

Climate change impacts and potential benefits of drought and heat tolerance in chickpea in South Asia and East Africa

Using CROPGRO-Chickpea model (revised version), we investigated the impacts of climate change on the productivity of chickpea (Cicer arietinum L.) at selected sites in South Asia (Hisar, Indore and Nandhyal in India and Zaloke in Myanmar) and East Africa (Debre Zeit in Ethiopia, Kabete in Kenya and Ukiriguru in Tanzania). We also investigated the potential benefits of incorporating drought and heat tolerance traits in chickpea using the chickpea model and the virtual cultivars approach. As compared to the baseline climate, the climate change by 2050 (including CO₂) increased the yield of chickpea by 17% both at Hisar and Indore, 18% at Zaloke, 25% at Debre Zeit and 18% at Kabete; whereas the yields decreased by 16% at Nandhyal and 7% at Ukiriguru. The yield benefit due to increased CO₂ by 2050 ranged from 7 to 20% across sites as compared to the yields under current atmospheric CO₂ concentration; while the changes in temperature and rainfall had either positive or negative impact on yield at the sites. Yield potential traits (maximum leaf photosynthesis rate, partitioning of daily growth to pods and seed-filling duration each increased by 10%) increased the yield of virtual cultivars up to 12%. Yield benefit due to drought tolerance across sites was up to 22% under both baseline and climate change scenarios. Heat tolerance increased the yield of chickpea up to 9% at Hisar and Indore under baseline climate, and up to 13% at Hisar, Indore, Nandhyal and Ukiriguru under climate change. At other sites (Zaloke, Debre Zeit and Kabete) the incorporation of heat tolerance under climate change had no beneficial effect on yield. Considering varied crop responses to each plant trait across sites, this study was useful in prioritizing the plant traits for location-specific breeding of chickpea cultivars for higher yields under climate change at the selected sites in South Asia and East Africa.     

便携式木材绞盘机新型卷筒离合器设计

在利用便携式木材绞盘机进行木材生产试验过程中,发现卷筒离合器在分离与接合过程中易出现卡阻现象,从而影响集材生产效率。在对牙嵌式离合器结构进行受力分析和卡阻原因分析的基础上,基于Solid Works的建模分析设计方法,设计了一种新型多孔旋转圆柱式卷筒离合器,该方法有效缩短了新型卷筒离合器的设计周期。新型卷筒离合器采用圆柱销与圆孔的嵌合,代替牙嵌式离合器牙嵌轴与牙嵌套的嵌合,同等试验条件下,旋转柱销式卷筒离合器平均分离时间分别比柱销式卷筒离合器节省3.71 s、比牙嵌式卷筒离合器节省8 s,改善了便携式木材绞盘机卡阻后离合器分离困难的现象,节约了离合器分离时间,从而有效提高了便携式木材绞盘机在集材作业中的生产效率。     

大连市中心区声环境功能区划调整研究

在分析了大连市中心区声环境功能区划调整必要性的基础上,全面评估了现有区划实施效果,以问题为导向提出了区划调整的方法体系,并阐述了区划调整结果的可行性,为城市环境噪声管理和防治提供科学依据。     

三角梅在美化城市中应用效果研究

三角梅广泛种植于热带、亚热带地区,品种多,花量大,花期长,色彩艳丽,易于养护,在城市绿化中对美化城市环境具有重要作用。本文分析了三角梅在现代高速工作、生活节奏的大环境中的应用,阐述了三角梅在现代桥梁、道路、社区、校园、公园以及家庭园艺等方面的应用效果,三角梅植物的应用软化了现代钢筋水泥铸成的立交交错的城市,增加了城市色彩点缀,为三角梅产业在城市中的应用提供理论支持。     

Wide hybridization and introgression breeding in safflower: Effectiveness of different selection methods

Possibility of using interspecific hybridization to increase genetic diversity of drought tolerance in safflower (Carthamus tinctorius L.) and effectiveness of different selection methods is poorly understood. The main objectives of this study were to evaluate the effectiveness of (a) interspecific hybridization to expand genetic diversity in safflower for agronomic traits and drought tolerance in advance generations and (b) different selection methods (direct vs. indirect) for improving seed yield. Interspecific hybridizations were performed between species of C. tinctorius × C. palaestinus (TP), C. palaestinus × C. oxyacantha (PO) and C. tinctorius × C. oxyacantha (TO). Based on the field screening of genotypes in F3 generation, four groups of selected genotypes (derived from combination of direct and indirect selection under both drought and normal environments along with selection based on drought tolerance index (STI)) were evaluated in F4 and F5 generations. Indirect selection for seed yield was significantly more efficient than direct selection. Selection in stress environment resulted to more efficiency than selection in normal environment. No significant difference was observed between direct selection and selection based on STI. The result showed that TP was the best population to combine high seed yield and drought tolerance in safflower.     

基于DPSIR和云模型的宿鸭湖水库水环境安全评估

为了推动水库水环境安全工作的开展,强化水源区水质保护,以宿鸭湖水库为例,应用DPSIR模型建立了水库水环境安全评估的指标体系,通过熵值法确定了各指标的权重,采用云模型对其2015年的水环境安全进行了评估,结果表明：该水库水环境处于较安全等级,但存在安全隐患；由于上游工业废水、居民生活污水、餐饮业的废弃物随着降雨径流汇入水库,再加上水产养殖、观光旅游等人类活动的影响,使其TN、TP的浓度和入库量增加,水库水质难以达标,需引起水库管理部门的重视。结论：云模型可减少评估过程中的不确定性,实现水库水环境安全概念与其定量数值间的合理转换,使其评估结果与实际相符。     

基于季节特征的土壤退墒模型建立与率定

利用河南省南阳市2011—2015年12个墒情站的土壤水分监测资料,分析研究了无增墒情况下土壤含水量消退规律,构建出基于不同季节(夏季、春秋季与冬季)的土壤含水量与衰减系数的数学模型,运用规划求解法率定模型参数,并利用2016—2017年资料对模型进行检验。结果表明,不同季节土壤水分衰竭系数模型分别为α=1.023(1-ω~2/4353)~(1/2)(夏季)、α=1.013(1-ω~2/7005)~(1/2)(春秋季)与α=1.008(1-ω~2/9303)~(1/2)(冬季),所建立的数学模型适用于南阳市相应季节壤土与粘壤土小麦、水稻与休闲地土壤旱情预测,但不适用于夏季与春秋季砂土特别是休闲地砂土土壤墒情预测。