3D-laser scanning: A non-destructive method for studying above- ground biomass and growth of juvenile trees

Many experiments with juvenile trees require the non-destructive monitoring of plant biomass and growth which is most often conducted with allometric relationships between easy to measure morphological traits and plant biomass. In a growth experiment with potted juvenile Fagus sylvatica L. trees, we tested the practicability and accuracy of the portable 3D-laser scanner ZF Imager 5006 using the phase difference method for measuring total above-ground biomass (stems, twigs, leaves), the biomass of axes (stems and twigs), of leaves biomass and the leaf area of 63 experimental trees. The trees were scanned from 20 (or 21) different positions with an angular step width of 0.036° in horizontal and vertical direction and the 3D-point cloud of every tree was translated into a point cloud grid with defined distances between the data points to standardise the spatial resolution of the data. The validation of the laser scan data against traditional biomass harvest data gave good correlations for total above-ground biomass (green and woody plant material combined), leaf biomass and leaf area (obtained by measurements before and after leaf harvest), and the mass of stems and twigs (only woody compartments of the plants) with R²-values between 0.61 and 0.88, all significant with p < 0.001. Biomass estimates using allometric regressions between total plant height or total leaf number and above-ground biomass as alternative non-destructive methods were found to be weaker than laser scanning (R² 0.54-0.67) and required a similar calibration effort. Repeated scanning of the same plant can be used to monitor biomass increase over time. We conclude that 3D-laser scanning is a promising technique for the non-destructive monitoring of biomass and growth in experiments with juvenile trees.     

冰温贮藏对柿果褐变以及相关指标的影响

以磨盘柿和次郎甜柿为试材,分析其贮后褐变指数、品质指标、生理生化指标和褐变底物及相关酶系的变化,探讨不同贮藏环境对2种柿果贮藏过程中褐变的影响.结果表明,在冰温(-0.5~-0.2)℃条件下,磨盘柿和次郎甜柿的褐变指数均低于冷藏(0±1)℃果实,且磨盘柿褐变指数低于次郎甜柿.冰温处理减缓了2种柿果的总酚含量和水分含量的...     

白僵菌酯酶同工酶薄层等电聚焦电泳分析

应用薄层等电聚焦电泳,分析了国内外不同地区、不同寄主47株白僵菌菌株的酯酶同工酶谱;依据各谱带等电点和扫描距离,确立了酶谱的三个区带。通过聚类分析和酯酶型分类,证实不同寄主的白僵菌酯酶同工酶谱差异显著,同一寄主而不同地区的白僵菌酯酶同工酶谱有一定的群体差异。与垂直平板凝胶电泳比较,薄层等电聚焦电泳用于白僵菌酯酶同工酶分析,分辨率较高。     

Acid‐base titration of barley roots

H saturated barley roots were titrated in the presence of 3 different concentrations of KC1. From the observation of the curves obtained, four regions corresponding to ionogenic groups of different pK values are apparent. A CEC of 20 to 30 miliequivalents/100 g dry weight was calculated for barley roots. A pzc value of about 4.5 was found graphically for the root surface.     

蔬菜QACCP生产管理系统的构建和应用

蔬菜生产的信息化管理,正在从安全监管、田间档案管理、信息溯源向生产全过程的质量管理推进。蔬菜质量分析与关键点控制（QACCP）管理系统,是在蔬菜生产管理关键点分析的基础上,综合应用HACCP和GAP管理策略,融合物联网、专家系统、GIS等技术,以生育期为节点,实现蔬菜生产、贮运、销售全过程的信息化管理,能够有效提升蔬菜生产管理水平,保障蔬菜生产供应安全。     

TILLING技术的原理与方法述评

TILLING,即Targeting Induced Local Lesions IN Genomes(定向诱导基因组局部突变技术),是由美国FredHutchinson癌症研究中心Steven Henikoff领导的研究小组发展起来的,是一种全新的反向遗传学研究方法。TILLING技术借助高通量的检测手段,快速有效地从由化学诱变剂(EMS)诱变过的突变群体中鉴定出点突变。目前,TILLING已被应用于多种生物的研究中。本文系统介绍了TILLING技术的基本原理、技术路线及其技术优势,同时列举了TILLING的应用实例,并展望了TILLING技术的应用前景。     

基于ISS-LCG组合特征点的油菜分枝点云配准方法

【目的】针对传统点云配准方法准确率低、速度慢等问题,以油菜Brassica napus L.分枝点云为研究对象,提出基于ISS-LCG组合特征点的配准方法。【方法】以成熟期油菜角果分枝点云为对象,去除背景噪声后,得到清晰完整的油菜分枝点云;然后通过内部形状描述子(Intrinsic shape signature,ISS)提取油菜分枝点云的特征点,再使用线性同余法(Linear congruential generator,LCG)伪随机选取油菜点云的部分点构成关键点,将特征点和关键点进行融合,构成ISS-LCG组合特征点;通过三维形状上下文特征(3D shape context,3DSC)对组合特征点进行特征描述,最后采用RANSAC+ICP两步点云配准法进行点云配准。【结果】基于ISS-LCG组合特征点的点云配准算法以30°为间隔对点云进行两两配准时,配准效果最佳,配准误差约0.066 mm,配准精度比未采用组合特征点的配准方法提升了50%～70%;配准时间均小于48 s,平均配准时间为8.706 s。【结论】该方法在可控环境内可以实现成熟期油菜植株高精度、高效率的自动配准。     

双浊点萃取-毛细管电泳法分离测定井水中痕量硝基苯酚位置异构体

[目的]为测定井水中痕量硝基苯酚位置异构体提供参考。[方法]采用双浊点萃取进行预处理,结合毛细管电泳技术对萃取物进行检测。[结果]选择浓度为0.5%Triton X-114为表面活性,pH 1.5,添加浓度0.020 g/ml NaCl,同时添加浓度0.2 mol/L NaOH溶液100μl,40℃时加热20min条件下双浊点萃取-毛细管电泳法分离测定井水中痕量硝基苯酚位置异构体,邻硝基苯酚、间硝基苯酚在0.000 2～0.005 0 mg/ml浓度范围内均呈现良好的线性关系,方法的加标回收率可达97%,相对标准偏差均小于5%。[结论]该方法消除了富集相中表面活性剂对毛细管电泳分离的影响,分析结果准确,且对环境友好。     

The impact of fire and density-dependent mortality on the spatial patterns of a pine forest in the Hulun Buir sandland,Inner Mongolia,China

Wildland fire, especially surface fire, is one of the major disturbances in forest ecosystems such as the Mongolian pine forest of the Hulun Buir sandland. However, little is known about the impact of fire on the spatial patterns at the stand level and its consequences for successional dynamics. To fill this gap we mapped three plots of Mongolian pine forest comprising sites of the same age that were affected by fire in 2006 and 1994, and a site without fire. We explored the stand structure using diameter at breast height (DBH) distributions and basal area, and used point pattern analysis to quantify the observed spatial patterns. Null models included homogeneous Poisson and Thomas cluster processes for univariate analyses, toroidal shift to test for independence, and random labelling for analyzing mortality. Large stems showed at all three stands a tendency to regularity, whereas small stems were mostly clustered. However, small stems did not become more regular at plots with earlier fire, and only the “overstocked” 2006 pre-fire stand showed negative association between large and small trees. Mortality was non-random, showing clustering of dead (or surviving) trees and clear density dependence where stems with more neighbors had a higher risk to die. Fire killed mostly smaller trees and after prolonged fire-free periods the stand approached the pre-fire patterns structurally and spatially. Our study showed that surface fire causes strong thinning in later succession stages and pushes the forest into maturity. It may also enhance resistance of our forest to more severe fire under the relatively harsh environmental conditions. A novel test statistic for random labeling allowed directly testing for density-dependent mortality and could be widely applied in point pattern analysis.     

Prognostic Value of Cardiac Troponin I and L‐Lactate in Blood of Dairy Cows Affected by Downer Cow Syndrome

Background

The downer cow syndrome (DCS) is a challenging health issue in the dairy industry. No cow‐side test is available to provide an accurate prognosis for DCS cases in farm settings.

Hypothesis/Objectives

Local or systemic hypoperfusion and myocardial lesions lead to an increase in blood concentration of biomarkers cardiac troponin I (cTnI) and L‐lactate. The objective was to determine the prognostic values of these biomarkers assessed cow‐sides in addition to clinical examinations in prognostication of a negative outcome (NO: death or euthanasia within 7 days).

Animals

218 client‐owned dairy cows affected by DCS.

Methods

In a prospective study, animals were monitored for 60 days after inclusion of each cow. Blood cTnI and L‐lactate concentrations were measured on the day of inclusion. The prognostic accuracy of both biomarkers and physical examination variables was estimated to predict NO. A mixed multivariable logistic regression model was used for data analysis.

Results

Prevalence of NO in this study was 63% on day 7. Troponin concentrations greater than 0.7 ng/mL had sensitivity and specificity of 54.1% (95% CI: 45.3–62.7%) and 78.4% (95% CI: 67.3–87.1%), respectively, for predicting NO. Blood L‐lactate was not associated with the outcome. The multivariable model revealed that heart rate >100 bpm (OR; 95% CI: 3.7; 1.3–10.2) and cTnI > 0.7 ng/mL (OR; 95% CI: 5.5; 2.1–14.6) were associated with the risk of NO.

Conclusions and Clinical Importance

Hypertroponinemia and tachycardia were associated with reduced survival in DCS cases. The use of cow‐side blood cTnI concentrations and heart rate could help to rapidly identify cows in farm setting that have poor chances of recovery and would benefit from a more aggressive treatment or euthanasia.