种植年限对设施蔬菜土壤养分和环境的影响

为了给设施蔬菜地合理施肥提供依据,研究了不同种植年限设施蔬菜地土壤理化性质、微生物数量及酶活性变化,以露地土壤为对照(CK),采集种植1 a(年)、3 a、5 a、7 a、9 a、11 a、13 a、15 a、17 a、20 a以及20 a以上的0~20 cm设施蔬菜土壤样品,采用常规土壤理化性质检测方法测定了土壤理化性质和酶活性,采用平板计数法,分析土壤微生物数量。结果表明,设施菜地种植年限与土壤容重呈正相关,与土壤孔隙度呈负相关;设施菜地土壤pH值随种植年限的增加逐年降低,两者呈显著的负相关性;土壤EC值、土壤有机质和速效磷含量都随种植年限的增加而逐年增高,并与种植年限呈显著的正相关性;与CK相比,种植13 a的蔬菜样地土壤全氮和速效钾含量均显著地增加;连续种植20 a以上,设施蔬菜土壤含盐量比对照土壤显著地增加了486.49%。土壤细菌和放线菌数量、过氧化氢酶和碱性磷酸酶活性呈现出先增加后减少的趋势,且都在种植年限为11~13 a时达到最大;真菌数量随着种植年限的增加而增加,而土壤脲酶活性则随种植年限的增加呈下降趋势;转化酶活性随着种植年限的增加保持不变。土壤微生物数量与酶活性之间存在一定程度的相关关系,其中土壤真菌数量与土壤酶活性之间的相关性最为显著。综上所述,种植年限不同的设施菜地,土壤养分失衡,呈现酸化趋势,盐分含量逐年增加,土传真菌病害潜在发生,对设施蔬菜生产不利。     

动态高压微射流对乌贼墨黑色素物理性质及微观结构的影响

为改善乌贼墨黑色素在食品中的应用性能,以虎斑乌贼(Sepia pharaonis)墨囊为原材料,采用碱性蛋白酶酶解制备乌贼墨黑色素,研究不同动态高压微射流(DHPM)(0、40、80、120、160、200 MPa)均质对其物理性质的影响,并采用红外光谱、扫描电子显微镜分析其微观结构。结果表明,DHPM处理使乌贼墨黑色素聚集体解聚,浊度增加、平均粒径减小,粒度分布更加集中和细微化,同时改善了其在去离子水和生理盐水中的溶解性;在压力作用下表现为粘度、空间色度值均有所增大;差示扫描量热法(DSC)分析表明,乌贼墨黑色素在120 MPa下热变性温度为90.70℃,焓变值为0.45 J·g^-1,且该压力下其贮藏稳定性最好;红外光谱分析表明,在特定压力处理范围内,DHPM处理使乌贼墨黑色素分子间形成了较强的氢键;扫描电镜观察发现样品颗粒在120 MPa处理后颗粒尺寸最小。因此,DHPM改性技术改善了乌贼墨黑色素的物理性质和微观结构,为其在食品工业中的应用提供了理论依据。     

苜蓿秸秆压缩仿真离散元模型参数标定

为了提高苜蓿秸秆压缩过程中离散元仿真研究所用参数的准确度,该研究采用物理试验和仿真优化设计相结合的方法对离散元仿真参数进行标定。首先,以接触参数物理试验结果为仿真参数选择依据,利用Plackett-Burman试验对初始参数进行显著性筛选,方差分析结果表明,苜蓿秸秆-苜蓿秸秆静摩擦系数、苜蓿秸秆-苜蓿秸秆滚动摩擦系数、苜蓿秸秆-45钢静摩擦系数对仿真休止角影响显著。进一步以休止角的相对误差值为评价指标,对3个显著性参数进行最陡爬坡试验,优化显著性参数取值范围,并基于Box-Behnken试验建立休止角与显著性参数的二阶回归模型,以物理试验得到的38.88°休止角为目标值,对显著性参数进行寻优,得到最优组合:苜蓿秸秆-苜蓿秸秆静摩擦系数为0.45、苜蓿秸秆-苜蓿秸秆滚动摩擦系数为0.08、苜蓿秸秆-45钢的静摩擦系数为0.54。最后利用T检验得到P0.05,表明仿真休止角与物理试验值无显著性差异,验证了最优参数组合的可靠性。研究结果表明,应用上述各优化试验来标定离散元仿真参数是可行的,同时标定的参数可为苜蓿秸秆的其它仿真试验提供参考。     

施肥对灌漠土作物产量、土壤肥力与重金属含量的影响

有机物还田是提升土壤肥力的主要措施,但也存在造成土壤金属污染的潜在风险。为查明不同有机物还田对土壤质量及作物产量的影响,本文通过长期定位试验,研究了无肥对照、常规施化肥(氮磷配施)以及70%常规化肥与牛粪、沼渣、污泥、鸡粪、菌渣和猪粪配施对土壤理化性状、有机碳和氮的固存率、氮磷钾活化系数、作物产量及重金属含量的影响。结果表明:牛粪、沼渣、污泥、菌渣、鸡粪和猪粪与70%化肥配施虽作物产量与常规施化肥相似,但6种有机物处理土壤有机质、全氮和碱解氮含量都较常规施化肥处理显著增加,污泥、鸡粪和猪粪处理土壤全磷与速效磷含量较常规施化肥处理显著增加,而且牛粪、沼渣、鸡粪和猪粪处理的速效钾、土壤磷活化系数和土壤钾活化系数较常规施化肥处理也显著提升。牛粪、沼渣、污泥、菌渣、鸡粪和猪粪处理土壤有机碳固存率为36.42%～71.61%,较常规施化肥处理都显著提高;而其氮固存率为6.47%～49.44%,仅有菌渣处理与常规施化肥处理差异不显著,而其他处理较常规施化肥处理显著增加。长期施鸡粪和菌渣处理的土壤铜含量较常规施化肥处理显著增加,增加量分别为4.17mg·kg~(-1)和14.2mg·kg~(-1);而污泥、鸡粪和菌渣处理的土壤锌含量较常规施化肥处理显著增加,增加量分别为13.53 mg·kg~(-1)、22.60 mg·kg~(-1)和49.73mg·kg~(-1)。综上,等有机质(4 500kg×hm~(-2))的牛粪、沼渣、污泥、菌渣、鸡粪和猪粪可替代30%氮磷肥,作物产量不受影响;不同有机物培肥土壤效果为污泥、鸡粪和猪粪优于牛粪和沼渣,而沼渣的培肥效果略差。为保证土壤环境质量稳定不恶化,种植小麦时有机物铜和锌的年携入量应分别低于53.01g×hm~(-2)和221.30 g×hm~(-2),而种植玉米时应分别低于153.40 g×hm~(-2)和347.04 g×hm~(-2)。     

微喷补灌对麦田土壤物理性状及冬小麦耗水和产量的影响

黄淮海麦区水资源短缺,探明畦灌和微喷补灌对麦田土壤物理性状及冬小麦耗水特性、产量和水分利用效率调节的差异,可为该地区冬小麦节水高产栽培提供理论和技术支持。2016—2018年冬小麦生长季,设置畦灌和微喷补灌两处理,研究其对麦田0～40 cm土层土壤容重、总孔隙度、毛管孔隙度、田间持水率,及冬小麦各生育阶段棵间蒸发量、蒸腾量、籽粒产量和水分利用效率的影响。结果表明微喷补灌处理与畦灌处理相比, 0～20 cm土层土壤容重降低,总孔隙度、毛管孔隙度和田间持水率增加;冬小麦返青后春季分蘖明显减少,返青至拔节期的棵间蒸发量和蒸腾量及全生育期总耗水量均显著减少;籽粒产量无明显变化,但水分利用效率显著提高,说明微喷补灌可以改善麦田土壤物理性状,优化冬小麦群体结构,通过减少棵间蒸发和植株无效蒸腾降低麦田耗水量,从而在维持高产水平的同时提高水分利用效率。     

添加芽孢杆菌对草鱼池塘中真核微生物的影响

为了研究添加芽孢杆菌对池塘中真核微生物群落结构和理化因子的影响,采用高通量测序技术分析了实验组(添加芽孢杆菌池塘)与对照组(普通池塘)水体真核微生物群落结构,同时分析了两组池塘的水体理化指标。结果表明:8、9月实验组池塘水体中TN、NH_4~+-N、NO_3~--N含量显著低于对照组(P0.05)。水体中梅尼小环藻(Cyclotella meneghiniana)、红囊藻(Hedriocystis)、蓝隐藻(Chroomonas)、丝孢酵母属(Trichosporon)和小环藻属(Cyclotella)真核微生物丰度显著高于对照组(P0.05)。实验组池塘水体真核微生物Chao1指数和Shannon指数显著高于对照组(P0.05)。实验结果证实:通过向池塘添加芽孢杆菌,可以改变水体中真核微生物群落的结构,从而实现对池塘理化因子的调节。研究结果对于降低水产养殖尾水对水域环境的污染具有一定的意义。     

Performance and uncertainty analysis of a short-term climate reconstruction based on multi-source data in the Tianshan Mountains region,China

Short-term climate reconstruction, i.e., the reproduction of short-term(several decades) historical climatic time series based on the relationship between observed data and available longer-term reference data in a certain area, can extend the length of climatic time series and offset the shortage of observations. This can be used to assess regional climate change over a much longer time scale. Based on monthly grid climate data from a Coupled Model Inter-comparison Project phase 5(CMIP5) dataset for the period of 1850–2000, the Climatic Research Unit(CRU) dataset for the period of 1901–2000 and the observed data from 53 meteorological stations located in the Tianshan Mountains region(TMR) of China during the period of 1961–2011, we calibrated and validated monthly average temperature(MAT) and monthly accumulated precipitation(MAP) in the TMR using the delta, physical scaling(SP) and artificial neural network(ANN) methods. Performance and uncertainty during the calibration(1971–1999) and verification(1961–1970) periods were assessed and compared using traditional performance indices and a revised set pair analysis(RSPA) method. The calibration and verification processes were subjected to various sources of uncertainty due to the influence of different reconstructed variables, different data sources, and/or different methods used. According to traditional performance indices, both the CRU and CMIP5 datasets resulted in satisfactory calibrated and verified MAT time series at 53 meteorological stations and MAP time series at 20 meteorological stations using the delta and SP methods for the period of 1961–1999. However, the results differed from those obtained by the RSPA method. This showed that the CRU dataset produced a low degree of uncertainty(positive connection degree) during the calibration and verification of MAT using the delta and SP methods compared to the CMIP5 dataset. Overall, the calibrated and verified MAP had a high degree of uncertainty(negative connection degree) regardless of the dataset or reconstruction method used. Therefore, the reconstructed time series of MAT for the period of 1850(or 1901)–1960 based on the CRU and CMIP5 datasets using the delta and SP methods could be used for further study. The results of this study will be useful for short-term(several decades) regional climate reconstruction and longer-term(100 a or more) assessments of regional climate change.     

Use of reflex indicators for measuring vitality and mortality of the snow crab (Chionoecetes opilio) in captivity

The snow crab (Chionoecetes opilio) is one of the most important commercial crabs in the world; it is heavily exploited in Atlantic Canada, Alaska, the Sea of Japan and the Barents Sea. Catches in the Barents Sea north of Norway have increased dramatically in the last decade. Most of the world's catch is processed, frozen and exported overseas. However, recently there has been considerable interest in exporting live snow crab, particularly in Norway. The stress of capture and live transport can result in significant mortalities. In order to establish a live export industry for snow crab, the welfare of the animal must be monitored throughout all the steps of the live transport process. In this study the reactions of snow crabs exposed to increasing periods of air exposure were measured in terms of reflex indicators, incidence of mortality, blood lactate levels and blood protein and haemocyanin. Although this is not a specific live holding or live transport process the aim was to test the suitability of reflex indicators to reflect vitality (stress) and not just to predict mortality. This would be compared with traditional blood biochemistry techniques for measuring crustacean stress. The study demonstrated that the reflex index score (RIS) is suitable to assess the vitality of snow crab. Longer air exposure periods render higher mortality rates and less vital individuals. The authors believe using vitality reflex indicators would be a suitable way of measuring crab welfare during the live holding and transport process.     

Quantifying uncertainty in the wild‐caught fisheries goal of the Ocean Health Index

Sustainability indices are proliferating, both to help synthesize scientific understanding and inform policy. However, it remains poorly understood how such indices are affected by underlying assumptions of the data and modelling approaches used to compute indicator values. Here, we focus on one such indicator, the fisheries goal within the Ocean Health Index (OHI), which evaluates the sustainable provision of food from wild fisheries. We quantify uncertainty in the fisheries goal status arising from the (a) approach for estimating missing data (i.e., fish stocks with no status) and (b) reliance on a data‐limited method (catch‐MSY) to estimate stock status (i.e., B/B_MSY). We also compare several other models to estimate B/B_MSY, including an ensemble approach, to determine whether alternative models might reduce uncertainty and bias. We find that the current OHI fisheries goal model results in overly optimistic fisheries goal statuses. Uncertainty and bias can be reduced by (a) using a mean (vs. median) gap‐filling approach to estimate missing stock scores and (b) estimating fisheries status using the central tendency from a simulated distribution of status scores generated by a bootstrap approach that incorporates error in B/B_MSY. This multitiered approach to measure and describe uncertainty improves the transparency and interpretation of the indicator and allows us to better understand uncertainty around our OHI fisheries model and outputs for country‐level interpretation and use.     

Towards the sustainable intensification of agriculture—a systems approach to policy formulation

The sustainable intensification of agriculture involves providing sufficient food and other ecosystem services without going beyond the limits of the earth’s system. Here a project management approach is suggested to help guide agricultural policy to deliver these objectives. The first step is to agree measurable outcomes, integrating formal policy goals with the often much less formal and much more diverse goals of individual farmers. The second step is to assess current performance. Ideally, this will involve the use of farm-scale metrics that can feed into process models that address social and environmental domains as well as production issues that can be benchmarked and upscaled to landscape and country. Some policy goals can be delivered by supporting ad hoc interventions, while others require the redesign of the farming system. A pipeline of research, knowledge and capacity building is needed to ensure the continuous increase in farm performance. System models can help prioritise policy interventions. Formal optimization of land use is only appropriate if the policy goals are clear, and the constraints understood. In practice, the best approach may depend on the scale of action that is required, and on the amount of resource and infrastructure available to generate, implement and manage policy.