基于GGE双标图对南方冬大麦区域试验的分析

用GGE双标图对2009—2010年度南方冬大麦品种区域试验进行分析,以图谱的形式阐述了参试品种在各试验点的表现、各品种的平均表现和稳定性、各品种的适应地区、各参试品种的相似性和环境的相似性及两品种之间的比较等问题,很好的解答了品种与环境互作的问题。双标图显示‘苏啤3号’是一个适应性很广的品种。产量相关性状的图谱分析表明：本年度试验中有效穗与产量相关性最高,是影响产量的制约因素。     

基于GGE双标图分析评价辽宁省水稻区域试验参试品种及参试地点

为分析辽宁省水稻区试参试品种的丰产性和稳产性及各试点的代表性和鉴别能力,利用Genstat的GGE双标图分析2017～2018连续两年进入省区域试验晚熟组的14品种(品系)在8个试点中的产量数据.结果表明:花粳12H47、锦稻糯325的丰产性和稳产性较好,辽粳1540产量较高但稳产性差,但在特定区域仍能发挥其高产优势....     

坝上地区马铃薯种植地球化学区划——以尚义县为例

尚义县为国家级贫困县,为了从根本上脱贫致富,因地制宜地进行马铃薯生产及生态环境规划,河北省地矿局出资对尚义县坝上地区开展了农业生态地质环境调查。结果表明：马铃薯优势区土壤Si、K和Na含量相对偏高,Mg、Cl、B、Ca、Cu、As等元素含量偏低,为沙质风积沉积环境;灌溉水水质较好且富Sr,呈弱碱性。通过建立地质地球化学模型对马铃薯种植进行区划,区划结果能有效地提高耕地的产能,发挥土壤内在质量优势,指导土壤平衡施肥,同时为土地利用规划修编、农作物种植结构调整提供可借鉴依据。     

基于Genstat GGE双标图评价甘肃省马铃薯区域试验的参试品种和试点

以2007-2008年甘肃省马铃薯区域试验的9个品种在7个试点的块茎产量为材料,利用基于Genstat的GGE双标图分析评价参试品种(系)的丰产性、稳定性、适应性以及各试点的代表性和区分力。结果表明,参试品种(系)‘陇薯9号’‘L0227-18’‘天薯10号’‘陇薯8号’的丰产性和稳产性较好;7个试点被划分为2个类型区域,在2个类型区域中表现最好的品种分别为‘陇薯9号’和‘陇薯6号’,安定、会川和临夏是比较理想的试点,具有较强的区分力和代表性。     

基于AMMI模型和GGE双标图对玉米品种产量稳定性和适应性选择评价

为有效鉴定和评价黄淮海玉米品种产量丰产性、稳定性和适应性,筛选出适宜黄淮海地区推广种植的优良玉米品种,采用AMMI模型稳定性参数和非参数方法对黄淮海玉米区域试验15个参试品种在6个省12个试点进行产量稳定性评价,同时利用GGE双标图对参试品种进行适应性分析。结果表明：方差分析变异来源中基因型（G）、环境（E）以及基因型与环境互作（GEI）均达到了极显著差异（P＜0.01）和显著差异（P＜0.05）,其中环境效应在总平方和中占比最大,为85.02%,其次是基因型与环境互作效应,占比为10.74%,基因型所占比例最小,为4.25%。对基因型与环境互作效应进行分解,前5个交互主成分（IPCA 1~IPCA 5）差异达到了显著和极显著水平,共计解释了85.41%的互作效应。基于Spearman相关分析,非参数统计因子和参数统计因子内部各指标之间存在着显著的相互关系。生物干重与非参数统计因子S^（6）、Z₁、Z₂、NP^（2）、NP^（3）、NP^（4）、KR间均呈显著负相关（P＜0.05）,与S^（1）和S^（2）则呈显著正相关（P＜0.05）。AMMI双标图显示,参试品种整株生物干重范围在18 000~22 000 kg/hm² ,‘渝单805’‘正大511’‘青秀001’和‘皖农科青贮8号’丰产性较好,‘金诚6’丰产性最差。‘正大511’‘雅玉7758’‘KNX22002’和‘青秀001’等参试品种稳定性较强,山东德州较其他试点有较好的辨别力,而山东泰安和河南濮阳等试点辨别力较差。GGE双标图分析表明‘正大511’属于丰产性和稳定性均较好的品种,为黄淮海地区的理想品种,其次为‘青秀001’和‘渝单805’,而‘安科青2号’离圆心位置最远,为参试品种中最不理想的品种。综上,采用AMMI模型和GGE双标图评价可为黄淮海地区玉米品种示范和推广提供依据。     

安徽省油菜品种区域试验结果分析

通过对安徽省产业协会提供的甘蓝型双低油菜新品种P71-13-2、09-崇9、09-崇10、09-崇26、09-崇30、崇29-4、皖油14（ck）,进行产量、抗逆性及区域适应性田间综合鉴定,为新品种审定、推广利用提供科学依据。试验结果表明,6个品种产量均低于ck,其中09-崇9产量为2045.2kg/hm2,在6个参试品种中最高,比对照皖油14减产1.2%,不显著;产量最低是P71-13-2,为1601.5kg/hm2,比对照减产22.7%,达极显著水平。     

基于AMMI模型和GGE双标图的西北春玉米品种区域试验综合评价

为筛选出西北地区高产稳产的品种和理想的测试点,利用AMMI模型和GGE双标图对2022年西北春玉米品种区域试验中的12个品种在19个试点的丰产性、稳产性和适应性进行分析,评价试点的区分力和代表性。结果表明,产量变异主要包括基因型、环境以及基因型与环境互作,分别占产量变异总平方和的4.39%、74.50%和10.08%。AMMI模型解释了82.76%的品种与试点互作效应。GGE双标图将19个试点分成3个生态区域;其中,甘肃省平凉市、天水市、内蒙古自治区巴彦淖尔、宁夏回族自治区平罗县、陕西省延安市、新疆维吾尔自治区昌吉州和可克达拉市7个试点的区分力和代表性较强。通过AMMI模型和GGE双标图,鉴定出适合西北地区高产稳产的品种为‘DK 2207’和‘玺旺188’。AMMI模型能够充分分解互作效应,并着重评价品种的稳定性,而GGE双标图则在评价试点的区分力和代表性方面有优势。综上,AMMI模型和GGE双标图的综合应用有助于提高西北春玉米品种和测试点评价的可靠性。     

区域试验玉米品种(系)产量稳定性和适应性的GGE双标图分析

为准确评价区域试验玉米品种(系)产量稳定性和适应性,研究采用GGE-biplot软件对2012年恩施州玉米品种区域试验11个参试玉米品种(系)和8个试点的试验数据进行分析。结果表明,在主要农艺性状中,产量与穗长、穗粗、百粒重、秃尖长和穗行数呈正相关。在参试玉米品种(系)中,恩玉单8号、G1004和HS10375具有较高产量和较好稳定性。在各区域试验点中,来凤、鹤峰区试点具有较强的品种鉴别能力和生态代表性。GGE双标图能够直观、简洁地显示玉米品种高产性、稳产性和区试点鉴别力、代表性,可为玉米品种鉴定和推广提供参考依据。     

The Application of GGE Biplot Analysis for Evaluat ng Test Locations and Mega-Environment Investigation of Cotton Regional Trials

In the process to the marketing of cultivars, identification of superior test locations within multi-environment variety trial schemes is of critical relevance. It is relevant to breeding organizations as well as to governmental organizations in charge of cultivar registration. Where competition among breeding companies exists, effective and fair multi-environment variety trials are of utmost importance to motivate investment in breeding. The objective of this study was to use genotype main effect plus genotype by environment interaction (GGE) biplot analysis to evaluate test locations in terms of discrimination ability, representativeness and desirability, and to investigate the presence of multiple mega-environments in cotton production in the Yangtze River Valley (YaRV), China. Four traits (cotton lint yield, fiber length, lint breaking tenacity, micronaire) and two composite selection indices were considered. It was found that the assumption of a single mega-environment in the YaRV for cotton production does not hold. The YaRV consists of three cotton mega-environments: a main one represented by 11 locations and two minor ones represented by two test locations each. This demands that the strategy of cotton variety registration or recommendation must be adjusted. GGE biplot analysis has also led to the identification of test location superior for cotton variety evaluation. Although test location desirable for selecting different traits varied greatly, Jinzhou, Hubei Province, China, was found to be desirable for selecting for all traits considered while Jianyang, Sichuan Province, China, was found to be desirable for none.     

The Application of GGE Biplot Analysis for Evaluating Test Locations and Mega-Environment Investigation of Cotton Regional Trials

In the process to the marketing of cultivars, identification of superior test locations within multi-environment variety trial schemes is of critical relevance. It is relevant to breeding organizations as well as to governmental organizations in charge of cultivar registration. Where competition among breeding companies exists, effective and fair multi-environment variety trials are of utmost importance to motivate investment in breeding. The objective of this study was to use genotype main effect plus genotype by environment interaction（GGE） biplot analysis to evaluate test locations in terms of discrimination ability, representativeness and desirability, and to investigate the presence of multiple mega-environments in cotton production in the Yangtze River Valley（YaRV）, China. Four traits（cotton lint yield, fiber length, lint breaking tenacity, micronaire） and two composite selection indices were considered. It was found that the assumption of a single mega-environment in the YaRV for cotton production does not hold. The YaRV consists of three cotton mega-environments： a main one represented by 11 locations and two minor ones represented by two test locations each. This demands that the strategy of cotton variety registration or recommendation must be adjusted. GGE biplot analysis has also led to the identification of test location superior for cotton variety evaluation. Although test location desirable for selecting different traits varied greatly, Jinzhou, Hubei Province, China, was found to be desirable for selecting for all traits considered while Jianyang, Sichuan Province, China, was found to be desirable for none.     

基于BLUP和GGE双标图的林木多地点试验分析

【目的】建立基于无偏预测值(BLUP)与基因型主效加基因型-环境互作效应(GGE)双标图的分析模型,以提高林木多点试验数据分析的准确性。【方法】以火炬松36个基因型在6个试验地(S1~S6)的种子产量为基础数据,利用ASReml软件对实测数据进行空间变异结合因子分析法的模型拟合,以获取各地点下每个基因型的BLUP值;从试验地划分、试验地评估和林木基因型评估3个方面,对原始数据、BLUP数据进行GGE双标图分析与比较。【结果】BLUP数据具有明显的空间变异,比原始数据具有更高的产量变异解释能力;原始数据和BLUP数据的试验地分组结果一致,均分为2组,但BLUP数据的试验地点间的相关关系变弱;原始数据的理想试验地为地点S5,而BLUP数据为地点S1;原始数据和BLUP数据的最理想基因型均为21,但2种数据高产和稳产基因型的一致性比较低。【结论】基于BLUP与GGE双标图相结合的模型,可用于林木多点试验分析,其比原始数据的GGE双标图分析结果更为可靠。     

Evaluation on the High Yielding,Stability and Comprehensive Performances of Check Cultivars in National Cotton Regional Trials in the Yangtze River Valley

[Objective] This study was to analyze the high yielding, stability, adaptabil-ity and main characteristics of check cultivars in national cotton regional trials in the Yangtze River Val ey in 2000-2013, with the aim to provide theoretical basis for the reasonable selection of check cultivars for cotton regional trials. [Method] GGE biplot analysis method was used to carry out the intensive analysis and comprehensive comparisons on the performances and differences of the 9 major characters of check cultivars, namely, lint cotton yield , stability, and other main traits including bol weight, bol number, lint percentage, fiber length, fiber strength, micronaire val-ue, plant height and seed index. [Result] Ezamian 10 was suitable in the majority of cotton planting regions in the Yangtze River Val ey, with the best high yielding abili-ty and perfect yield stability. The yielding ability of Xiangzamian 8 ranked the sec-ond, but its stability was the poorest. Xiangzamian 8 was of the specific adaptive cultivar with relatively good performance in high yielding but the poorest stability. The suitable planting areas of Xiangzamian 8 were limited to the cotton planting re-gion around Dongting Lake in Hunan province, Poyang Lake in Jiangxi Province, the Coastal region in Jiangsu Province and Wuhan district in Hubei Province. Xi-angzamian 2 performanced poorer in both yielding and stability, while Simian 3 ranked first in stability but the last in yielding ability. The dominant character of Xi-angzamian 8 and Xiangzamian 2 were high cotton plants and big bol s. Simian 3 performanced super in lint percentage and fiber length. Ezamian 10 was strong in cotton bol formation ability, lint cotton yielding, fiber strength and seed size, as wel as high micronaire value. [Conclusion] The outstanding performance of Ezamian 10 in high and stable yield in the Yangtze River Val ey in recent years has effectively promoted the high yielding ability of candidate varieties in cotton regional trials in the area.     

基于GGE双标图的长江中下游中籼迟熟区试品种丰产适应性及抗稻瘟病性评价

为评价长江中下游地区籼稻稻瘟病抗性以及丰产适应性和稳定性,采用GGE双标图对13个中籼迟熟水稻品种在长江中下游16个试验点的产量数据及稻瘟病抗性数据进行综合分析。结果表明：‘爽两优粤农丝苗’平均产量为0.95 kg/hm²,产量稳定性好,稻瘟病抗性鉴定指数3.2,是长江中下游地区高产、稳产、且对稻瘟病高抗的中籼迟熟品种;‘春9两优70’平均产量高,可达0.97 kg/hm²,稳定性中等,稻瘟病抗性高,其鉴定综合指数为3.3,该品种在湖南岳阳、湖北黄冈和安徽芜湖的产量表现均较好,产量分别达1.09、1.16和1.06 kg/hm²,具有广泛的适应性。‘深和两优1133’产量也较高,可达0.93 kg/hm²,但稳定性差,稻瘟病抗性鉴定综合指数平均为4.0,对环境敏感性强,适合在特定的地点如江西高安、福建建阳、浙江温州等地种植。通过GGE双标图对试验地点进行综合评价,湖北武汉、湖北黄冈、安徽休宁、江西吉安和浙江温州对参试品种的区分力较强、生态区的代表性好,是较理想的试验地点。     

黄淮地区主推小麦品种对根腐病抗性的初步鉴定与评价

为了给根腐病的防治和抗病育种工作提供依据,以小麦根腐病病原菌麦根腐离蠕孢(Bipolaris sorokiniana)LK030093分离物为接种菌株,对黄淮麦区主推的89个小麦品种进行了室内盆栽苗期抗性和田间病圃成株期抗性鉴定,并采用病情指数法进行了抗性评价。结果表明,供试小麦品种中没有免疫和高抗品种;在室内盆栽接种鉴定中,仅郑麦9962表现为抗病,平安8号和周麦24表现为中抗,淮川916、西农919等33个品种表现感病,平安3号、济麦23等53个品种表现高感,抗病、中抗、感病和高感品种所占比例分别为1.12%、2.25%、37.08%和59.55%;在田间病圃成株期鉴定中,洛麦22、泛麦5号表现为抗病,郑麦9962、阜麦936等19个品种表现为中抗,周麦27、济麦20等35个品种表现为感病,兰考906、石麦12等33个品种表现为高感,抗病、中抗、感病和高感品种所占比例分别为2.25%、21.35%、39.33%和37.08%。可见,黄淮麦区主推品种对小麦根腐病的整体抗性较差,需要尽快加强抗病资源筛选和抗病育种工作。     

Cultivar Selection and Test Site Evaluation of Cotton Regional Trials in Jiangsu Province Based on GGE Biplot

[Objective] This study was to evaluate the high yielding and stability of candidate cultivars, depict the adaptive planting region, analyze trial location discrimination ability and representativeness, as well as identify the ideal cultivar and trial location, with the aim to provide theory background for cultivar selection and reasonable scheme of test location in Jiangsu Province. [Method] The GGE biplot method was used to analyze the lint cotton yield of 12 experimental genotypes in the 6 test locations(three replicates in each) of the cotton regional trial in Jiangsu Province in 2013. [Result] The effects of genotype(G), environment(E), and genotype by environment interaction(G×E) on lint cotton yield were all highly significant(P0.01), which made it necessary to further explore the specific pattern of genotype by environment interaction. Jinmian118(G4) and SF3303(G5) were the best ideal genotypes screened by the "ideal cultivar" and "ideal location" view of GGE biplot, and the ordination of test sites based on the ideal index were in the order of Dafeng(DF), Yanliang(YL), Liuhe(LH), Dongtai(DT), Yancheng(YC), and Nantong(NT), among which NT was relatively weak in representing of the whole target cotton planting region in Jiangsu Province. The "similarity among locations" view of GGE biplot clustered all trial locations into one group, showing that the test sites in the cotton planting region in Jiangsu Province were in the same mega-environment.The "which-won-where" view of GGE biplot indicated that cotton cultivar Jinmian118(G4) was the most appropriate cultivar in the homogeneous cotton planting region in Jiangsu Province. [Conclusion] Among the candidate cultivars, Jinmian118 and SF3303 were identified as the most ideal cultivars in this set of conventional cotton regional trial in Jiangsu Province; the test site of Dafeng ranked the first out of all locations in terms of discrimination and representativeness, and all test locations were clustered into the same mega-environmet, which indicated the high efficiency of cultivar selection in the cotton regional trial in Jiangsu Province.     

黄淮南片小麦区试品种沉降值的测定及优质区划研究

通过对黄淮南片小麦区试38个参试品种在10个不同试点的沉降值测定分析表明:达强筋标准的品 种有陕农981、藁麦8901、郑麦3666、西农979、新9408、豫麦34、PH6911、郑麦005;接近弱筋的品种有郑麦004、 轮选987、旱抗1号;其余品种为中筋类型。在优质小麦生产中,起决定作用的是品种,但不同生态条件对品种 品质的表现影响也很大,品质表现最好的试点是陕西富平,其次是河南新乡、安徽涡阳、江苏徐州、陕西杨凌。 品质表现最差的是河南周口。