Pod shatter resistance evaluation in cultivars and breeding lines of Brassica napus, B. juncea and Sinapis alba

Pod shatter susceptibility was investigated in Brassica napus germplasm and shatter resistant species of B. juncea and Sinapis alba. The comparisons were made by measuring seed yield in field plots, detached pod rupture energy (RE) and the half‐life of pod‐opening. Pod shatter resistance was significantly greater in B. napus lines derived from interspecific hybridizations of B. napus with B. rapa, B. carinata and B. juncea, than common B. napus cultivars. While these lines exhibited no significant difference in resistance to pod shatter than B. juncea, an entry of S. alba had no yield loss caused by pod shatter. Resistance to pod shatter was characterized in the field as little or no yield loss after full maturity, delayed shattering in time, and stable yield performance under variable climatic conditions during pod maturity. Yield loss caused by pod shatter ranged from a low of 4% for the B. juncea cv. ‘AC Vulcan’ to a high of 61% for the black seeded B. napus line DH12075 in 2‐year field trials after 1 month maturity. Pod shatter resistance was not significantly associated with specific plant and pod morphological traits, except pod length (P = 0.005) in tested materials. Field visual scores of pod shatter through inspections of average pod shatter per plant within plots were highly correlated with plot yield loss. Indoor quantitative evaluations of pod strength using a pendulum machine to measure pod RE and random impact test to measure half‐life of pod‐opening resistance were highly correlated with field yield loss. Multiple evaluations of pod shatter in method and in time after pod maturity are recommended for reliable evaluation of pod shatter resistance.     

Screening RAPD primers for molecular taxonomy and cultivar fingerprinting in the genus Actinidia

Summary Eighty ten-base long arbitrary primers were tested for PCR-based DNA amplification of three species of the genus Actinidia (A. deliciosa the kiwifruit, A. chinensis, and A. kolomikta), with the aim of screening species-specific and genotype-specific markers.Of the 80 primers tested, 30 gave an average of 3.5 bands which were monomorphic within one or two species and absent in the remaining one(s), thus resulting in useful markers for taxonomic and phylogenetic purposes. None of the primers tested produced bands linked to sex. Twenty primers out of the twenty-five selected from a preliminary screening showed high levels of polymorphism, producing two to eleven patterns each from the 13 kiwifruit cultivars examined.We found the Stoffel fragment and the Taq polymerase were both suitable for RAPD analysis, the most noticeable difference being the smaller size of fragments (0.4–1.2 kb) produced by the former in comparison to the latter (1.0–3.4 kb). We tested also three different annealing temperatures (35, 37, and 39° C) and found the intermediate one best for number of amplified bands and reproducibility of results.Abbreviations 2-BE 2-butoxyethanol - CTAB hexadecyltrimethylammonium bromide - MAS Marker-Assisted-Selection - PCR Polymerase Chain Reaction - RAPD Random Amplified Polymorphic DNA - RFLPs Restriction Fragment Length Polymorphisms     

Molecular mapping and characterization of traits controlling fiber quality in cotton

Cotton (Gossypium spp) is the world's leading natural fiber crop. Genetic manipulation continues to play a key role in the improvement of fiber quality properties. By use of DNA-based molecular markers and a polymorphic mapping population derived from an inter specific cross between TM-1 (G. hirsutum) and 3-79 (G. barbadense), thirteen quantitative trait loci (QTLs) controlling fiber quality properties were identified in 3-79, an extra long staple (ELS) cotton. Four QTLs influenced bundle fiber strength, three influenced fiber length, and six influenced fiber fineness. These QTLs were located on different chromosomes or linkage groups and collectively explained 30% to 60%of the total phenotypic variance for each fiber quality property in the F₂ population. The effects and modes of action for the individual QTLs were characterized with 3-79 alleles in TM-1 genetic background. The results indicated more recessive than dominant, with much less additive effect in the gene mode. Transgressive segregation was observed for fiber fineness that could be beneficial to improvement of this trait. Molecular markers linked to fiber quality QTLs would be most effective in marker-assisted selection (MAS) of these recessive alleles in cotton breeding programs. This revised version was published online in August 2006 with corrections to the Cover Date.     

The frequency of natural cross-fertilisation in sequential sowings of winter barley

Summary Estimations of random mating frequency were computed for a series of sequential autumn sowings of populations of winter barley. The estimations were by means of the maximum likelihood scoring method and three varieties, each carrying a recessive genetic marker, provided three independent estimations for each population. High levels of out-crossing were found in sowings made early in September, and a trend towards absence of out-crossing in populations sown in late November was evident. Although fluctuations in this trend could be accounted for by fluctuations in meteorological factors, a more profound underlying effect was evident in that the three marker varieties behaved similarly, though to different degrees. It is postulated that the principle effect of sowing date, as it affects out-crossing, is upon the development of the flowering apex, and that environmental conditions at flowering time merely modify flowering behaviour.     

Sex-linked SSR markers in hemp

Hemp is a dioecious plant with sex chromosomes X and Y, the male sex being heterogametic. The quality of the fibre depends on the sex type. The sex chromosomes can be characterized by molecular markers. In this report, sex‐linked simple sequence repeat (SSR) markers are described. One SSR marker was polymorphic in both the populations derived from single crosses, two other markers in but one of the two populations. Three alleles were detected for two SSR markers indicating polymorphism not only between X and Y, but also between different X chromosomes. In addition, several sex‐linked RAPD markers were detected in one population. Recombination within the sex chromosomes was observed for nearly all markers.     

土壤养分空间变异及合理取样数研究

土壤养分存在明显的空间差异，田间土壤养分合理取样数取决于养分要素自身空间变异程度和人们对数据精度的要求。若空间变异大、精度要求高则需要较多采样数，反之需较少样点数。计算结果表明，极大多数养分要素的合理取样数较实际取样数有较大幅度减少，意味着可大幅降低采样及分析成本。据统计学空间自相关和半方差函数方法研究结果，养分要素存在一定的空间自相关性，但不同方向上的自相关性有明显差异，独立间距也因养分要素而异。研究结果可为精准农业土壤养分样点密度设定、养分要素等值线绘制及精准施肥提供支持。     

基于HJ-CCD数据和随机森林算法的小麦叶面积指数反演

为给小麦长势的遥感监测提供技术支持,该文运用随机森林回归(RF,random forest)算法建立小麦叶面积指数(LAI)遥感反演模型。首先基于2010-2013年江苏地区小麦环境减灾卫星HJ-CCD的影像数据,提取拔节、孕穗和开花3个生育期的卫星植被指数,进而根据各生育期植被指数和相应实测LAI数据,利用RF算法构建各期小麦LAI反演模型,并以人工神经网络(ANN,artificial neural network)模型为参比模型进行预测精度的比较。结果表明:RF算法模型在3个生育期的预测结果均好于同期的ANN模型。拔节、孕穗和开花3个生育期RF模型预测值与地面实测值的R2分别为0.79,0.67和0.59,对应的RMSE分别为0.57,0.90和0.78;ANN模型的R2分别为0.67,0.31和0.30,对应的RMSE分别为0.82,1.94和1.43。该研究结果为提高大田尺度下的小麦LAI遥感预测精度提供了技术和方法。     

精准农业土壤采样密度研究——以上海精准农业试验示范基地为例

通过土壤密集采样识别农田土壤物理生化性状的空间差异,构建土壤与农作物产量关系模型,用间接方法提高土壤性状信息的分辨率并定量评价这些信息的可靠性非常必要。在评价多种插值方法的基础上,对中国科学院上海精准农业示范基地每公顷3个样本、等距离系统抽样的280个土壤有机质样本采用克立格方法进行插值,估算样本之间土壤有机质含量和分析估算的可靠性,并与距离倒数函数插值法进行对比。对几个减少样本数量的方案进行分析,提出在满足精准水稻种植管理分区要求前提下可减少1/2原有土壤采样样本,并给出适于水稻精准种植土壤采样设计的逐步优化方法。     

利用无人机多光谱影像的多品种玉米成熟度监测

基于遥感监测多品种玉米成熟度进而掌握最佳收获时机，对提高其产量和品质至关重要。该研究在玉米成熟阶段获取无人机多光谱影像，同步采集叶片叶绿素含量（chlorophyll content，C）、籽粒含水率（moisture content，M）、乳线占比（proportion of milk line，P）等地面实测数据，以此构建玉米成熟度指数（maize maturity index，MMI），从而定量表征玉米成熟度。通过MMI与植被指数构建回归模型和随机森林模型，验证MMI适用性，并分析无人机遥感对不同品种玉米成熟度的监测精度。结果表明：1）不同品种玉米的叶片叶绿素含量、籽粒含水率、乳线占比的变化速率均存在差异。2）MMI与所选植被指数的相关性均可达到0.01显著水平，其中与归一化植被指数（normalized difference vegetation index，NDVI）、转换叶绿素吸收率（transformed chlorophyll absorbtion ratio index，TCARI）相关性最高，相关系数均为0.87。3）该研究基于不同组合的数据集进行了模型验证，其中随机森林模型对MMI的估测精度最高，测试集决定系数（coefficient of determination，R²）为0.84，均方根误差（root mean squared error，RMSE）为8.77%，标准均方根误差（normalized root mean squared error，nRMSE）为12.05%。此外，随机森林模型对不同品种MMI的估测精度较好，京九青贮16精度最优，其中R²、RMSE、nRMSE为0.76、10.67%、15.88%，模型精度证明了可以利用无人机平台对不同品种玉米成熟度进行监测。研究结果可为多光谱无人机实时监测农田多品种玉米成熟度的动态变化提供参考。     

基于野外VIS-NIR光谱的土壤盐分主要离子预测

为明确干旱区土壤盐分主要离子的特征光谱,建立精度高和稳定性好的盐渍土预测模型,以新疆阜康市为研究区域,采用网格法采集55个土壤样本,利用实测VIS-NIR光谱,选择多元线性回归(MLR)、支持向量机(SVM)、随机森林(RF)法构建土壤盐分主要离子含量反演模型,而后对反演精度进行检验。结果显示:(1)在0.01显著水平下,土壤盐分与Na~+、Cl~–、Ca~(2+)含量均呈显著相关,相关系数分别为0.978、0.814、0.645;(2)综合光谱响应和相关性分析确定土壤盐分主要离子的特征波段为459、537、1 381、1 386 nm,显著特征波段为459、537 nm;(3)3种模型拟合效果从高到低依次为RFMLRSVM,采用RF所建模型盐分主要离子(Na~+、Cl~–、Ca~(2+))R~2最高,RMSE最小,RPD最大,分别为2.11、2.03、1.80,为最优预测模型。通过选取土壤主要离子显著特征波段,进而采用RF法构建其估测模型,可以有效提取干旱区土壤盐分的主要离子信息。