Design of nondestructive test system for plasma clots

One of the most important measures that are used to guarantee blood transfusion safety is to detect clots in the plasma before transfusion. To overcome the disadvantages of manual detection method, this research designs a nondestructive testing (NDT) system for plasma clots inspection based on machine vision technique and artificial neural networks. The key technology for system design are studied and presented. Image acquisition is performed by custom-designed software based on MATLAB platform, and the methods of image cut, reverse color, median filter as well as gray cutting are adopted to preprocess image. The use of fisher discrimination method, combined with iterative threshold segmentation method and the selection of connected domain, can successfully eliminate the interference of air bubble and correctly extract the image of plasma clots. Plasma clots are discriminated by a recognition model based on artificial neural network BP algorithms. The results of clinical contrast experiment shows that the system can effectively detect whether plasma contains plasma clots and the new system shows a much higher degree of repeatability and stability. From the image acquisition and processing to the recognition of plasma clots, the detecting time of a sample is no more than 1 min.     

Using pre-classification to improve the accuracy of species-specific forest attribute estimates from airborne laser scanner data and aerial images

The aim of this study was to examine whether pre-classification (stratification) of training data according to main tree species and stand development stage could improve the accuracy of species-specific forest attribute estimates compared to estimates without stratification using k-nearest neighbors (k-NN) imputations. The study included training data of 509 training plots and 80 validation plots from a conifer forest area in southeastern Norway. The results showed that stratification carried out by interpretation of aerial images did not improve the accuracy of the species-specific estimates due to stratification errors. The training data can of course be correctly stratified using field observations, but in the application phase the stratification entirely relies on auxiliary information with complete coverage over the entire area of interest which cannot be corrected. We therefore tried to improve the stratification using canopy height information from airborne laser scanning to discriminate between young and mature stands. The results showed that this approach slightly improved the accuracy of the k-NN predictions, especially for the main tree species (2.6% for spruce volume). Furthermore, if metrics from aerial images were used to discriminate between pine and spruce dominance in the mature plots, the accuracy of volume of pine was improved by 73.2% in pine-dominated stands while for spruce an adverse effect of 12.6% was observed.     

利用脉搏波参数间接测定大鼠动脉血压的一种方法

通过提取动脉脉搏波特征参数,建立了间接测定大鼠动脉血压的多元回归方程。结果表明:脉搏波周期、K值、脉搏波波图面积等参数与动脉收缩压有较好的相关性,与颈动脉有创血压测定法数值比较,有较小差异(P>0. 05),表明所筛选的脉搏波特征参数能准确地反映动脉的每搏收缩压值,但与舒张压相关性较差。该方法简便、准确、稳定性好,便于长期动态观察。     

植物水分利用效率的影响因子研究综述

在概述植物水分利用效率(WUE)及其层次和测定、计算方法的基础上,介绍了影响植物WUE的内部因素(包括植物种类和品种、叶片解剖结构及生理生化特征等)和外部因素(包括气象、土壤、生物因素等),以及各自的作用机理,尤其是对气孔不均匀关闭、影响Δ13C在田间条件下表现较差的原因、冠层和叶边界层对植物WUE产生的效应及其作用原理进行了探讨,并提出了今后植物WUE研究的重点和方向。     

The Effectiveness of HA-GGE Biplot Application in Analyzing the Data from the National Cotton Cultivar Regional Trial in the Yangtze River Valley

A large number of regional crop trials have demonstrated the ubiquitous existence of genotype × environment interactions (G×E), which make it complicated to select superior cultivars and identify the ideal testing sites. The GGE (genotype main effect plus genotype × environment interaction) biplot is the most powerful statistical and graphical displaying tool available for regional crop trial dataset analysis. The objective of the present study was to demonstrate the effectiveness of the biplot in evaluating the high and stable yields of candidate cultivars simultaneously, and in delineating the most adaptive planting region, analyzing trial location discrimination ability and representativeness, and identifying the ideal cultivar and trial locations. The lint cotton yield dataset with nine experimental genotypes and 17 test locations (three replicates in each) was collected from the national cotton regional trial in the Yangtze River Valley (YaRV) in 2012. The results showed that: (1) the effects of genotype (G), environment (E), and genotype × environment interaction (G×E) were significant (P < 0.01) for lint cotton yield. Differences among environments accounted for 78.7% of the treatment total variation in the sum of squares, whereas the genotype main effect accounted for 8.7%, and the genotype × environment interaction accounted for 12.6%. (2) The “ideal cultivar” and “ideal location” view of the HA-GGE biplot identified Zhongcj408 (G2) and Nannon12 (G9) as the best ideal genotypes; Cixi in Zhejiang Province and Jiangling in Hubei Province were the most ideal locations.(3) The “which-won-where” view of the biplot outlined the adaptive planting region for each experimental cultivar. (4) The “similarity among locations” view clustered the trial locations into four groups, among of which the two outlier locations, Shehong (SH) and Chengdu (QBJ), located in Shichuan Basin in the upper reaches of YaRV, were clustered in one group, whereas the Nanyang (NY) of Henan Province at the northern edge of YaRV was singled out as a sole group. Such location clustering results implied an apparent association with the geographical environment.     

Analysis of Genotype-by-Environment Interaction for Agronomic Traits of Durum Wheat in Iran

Abstract

Grain yield of durum wheat (Triticum turgidum L. var. durum) under Mediterranean conditions is frequently limited by both high temperature and drought during grain filling. Genotype-by-environment (GE) interaction and genotype-by-trait (GT) data were analyzed for agronomic performance of durum wheat breeding lines. Data were obtained from 18 durum wheat breeding lines and two cultivar checks (Zardak and Sardari) for their agronomic performance under three different climate locations (moderate, warm and cold winters) and two moisture regimes (rainfed and two supplemental irrigations conditions) in two cropping seasons (2006 and 2007) in Iran. Analysis of GE interaction data based on multiple traits showed that the environment (combination of year-location- moisture regimes) effect was always the most important source of trait variation, accounting for 58.6 to 98.4% of the total variation. Biplot analysis of the studied traits revealed that (i) the locations tended to discriminate genotypes in dissimilar fashions, and (ii) the relationships among traits were not consistent over the locations, where they facilitated visual genotype comparisons and selection at each location.     

Effects of nitrogen supply on water‐use efficiency of higher plants

The worldwide increase of food demand and reduced sweet‐water availability in some important food‐producing regions raised interest in more efficient water use, which has become one of the central research topics in agriculture. Improved irrigation management and reduced bare‐soil evaporation have highest priority to increase agronomic water‐use efficiency (WUE). Compared to these technical (irrigation) and basic (crop production) management options, effects of nutrient management on WUE were less frequently considered. Twenty‐nine publications on nitrogen (N) effects on biomass WUE of container‐grown plants are considered in this review. Most of them indicate positive N effects on WUE, and relevance of N effects on intrinsic WUE and unproductive water and carbon loss is discussed. A plot of 90 published data of percent decreases of WUE and dry mass under variable N supply is presented. Extrapolation of biomass WUE from leaf measurements of intrinsic WUE is critically reviewed. The positive correlation between WUE and dry‐mass formation suggests that physiological rather than stomatal effects are more important in order to explain positive N effects on WUE.     

A comparison of changes in stable isotope ratios in the epidermal mucus and muscle tissue of slow‐growing adult catfish

Although stable isotope analysis is a powerful tool for determining diet, migration patterns and the structure of food webs in aquatic systems, the slow response of isotopic ratios in the widely used muscle tissue often hampers this approach, particularly in slow‐growing or adult fishes. We conducted a diet‐switch experiment to compare the changes in the stable carbon isotope ratio (δ¹³C values) in the epidermal mucus and muscle tissue of five‐year‐old catfish (Silurus asotus). The isotope ratios in noninvasively sampled mucus changed more rapidly than those in the muscle tissue. As isotopic change in mucus was relatively rapid, this technique can be used over a finer timescale than traditional isotopic analyses using the muscle tissue. The isotopic change half‐life in our experimental condition was 200 days, which would not be short enough for some research purposes. Examining mucus along with the muscle would enable food habits of slow‐growing fishes to be determined over different timescales. However, the rate of isotopic change in the mucus was negatively affected by the size of fish and was slower than the previously reported rates in juvenile steelhead. These findings suggest that mucus turnover rates need to be determined prior to the field data interpretation.     

Clinical feasibility of cognitive testing in dogs (Canis lupus familiaris)

Several cognitive tests have been developed to evaluate specific aspects of human and animal learning and memory. These tests have been used for early detection of cognitive deficits and to monitor the treatment of dogs with cognitive impairment. Thus, this article evaluated the feasibility of cognitive tests for use in canine neurology clinical routines and the suitability of the different tests to accomplish this aim. Fifteen healthy adult dogs were used for the cognitive tests of reward approach learning, object approach learning, object discrimination learning, reversal learning, delayed non-matched to position, and delayed non-matched to sample to assess different aspects of memory. No difference was observed between tests of delayed non-matched to position (3.13 ± 2.23 days) and delayed non-matched to sample (3.20 ± 2.40 days) (P = 0.944). However, dogs had greater difficulty in reversal learning (8.47 ± 2.61 days) than in object discrimination learning (4.60 ± 1.64 days) (P ≤ 0.001). Based on the tests performed, the delayed non-matched to position test may be performed in clinical routine if the owner and the veterinarian have time available, because this test is sensitive to evaluate dogs with cognitive impairments, but requires approximately 10 days of training. Thus, elderly dogs are excellent experimental models to study pathological aging based on their similarities with some human brain diseases, such as Alzheimer disease.     

基于无人机多光谱遥感的冬小麦冠层叶绿素含量估测研究

为探讨利用无人机多光谱影像监测冬小麦叶绿素含量的可行性,基于北京市大兴区中国水科院试验基地的2019年冬小麦无人机多光谱影像和田间实测冠层叶绿素含量数据,选取16种光谱植被指数,确定对冬小麦冠层叶绿素含量显著相关的植被指数,采用一元二次线性回归和逐步回归分析方法建立各生育时期及全生育期的SPAD值估测模型,通过精度检验确定对冬小麦冠层叶绿素含量监测的最优模型。结果表明,两种分析方法中逐步回归建模效果最佳。拔节期选取4个植被指数(MSR、CARI、NGBDI、TVI)建模效果最好,模型率定的决定系数(r~2)为0.73,模型验证的r~2、相对误差(RE)和均方根误差(RMSE)分别为0.63、2.83%、1.68;抽穗期选取3个植被指数(GNDVI、GOSAVI、CARI)建模效果最好,模型率定的r~2为0.81,模型验证的r~2、RE、RMSE分别为0.63、2.83%、1.68;灌浆期选取2个植被指数(MSR、NGBDI)建模效果最好,模型率定的r~2为0.67,模型验证的r~2、RE、RMSE分别为0.65、2.83%、1.88。因此,无人机多光谱影像结合逐步回归模型可以很好地监测冬小麦SPAD值动态变化。