<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE article PUBLIC "-//NLM//DTD JATS (Z39.96) Journal Publishing DTD v1.3 20210610//EN" "JATS-journalpublishing1-3.dtd">
<article article-type="research-article" dtd-version="1.3" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xml:lang="ru"><front><journal-meta><journal-id journal-id-type="publisher-id">vavilov</journal-id><journal-title-group><journal-title xml:lang="ru">Вавиловский журнал генетики и селекции</journal-title><trans-title-group xml:lang="en"><trans-title>Vavilov Journal of Genetics and Breeding</trans-title></trans-title-group></journal-title-group><issn pub-type="epub">2500-3259</issn><publisher><publisher-name>Institute of Cytology and Genetics of Siberian Branch of the RAS</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.18699/VJ19.469</article-id><article-id custom-type="elpub" pub-id-type="custom">vavilov-1876</article-id><article-categories><subj-group subj-group-type="heading"><subject>Research Article</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="ru"><subject>МОЛЕКУЛЯРНЫЕ МАРКЕРЫ В ГЕНЕТИКЕ И СЕЛЕКЦИИ</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="en"><subject>BIOINFORMATICS AND SYSTEM BIOLOGY</subject></subj-group></article-categories><title-group><article-title>Статистическая и графическая (GGE biplot) оценка адаптивной способности и стабильности селекционных линий ячменя озимого</article-title><trans-title-group xml:lang="en"><trans-title>Statistical and graphical (GGE biplot) evaluation of the adaptive ability and stability of winter barley breeding lines</trans-title></trans-title-group></title-group><contrib-group><contrib contrib-type="author" corresp="yes"><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Гудзенко</surname><given-names>В. Н.</given-names></name><name name-style="western" xml:lang="en"><surname>Gudzenko</surname><given-names>V. N.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Киевская область, с. Центральное</p></bio><bio xml:lang="en"><p>Kiev region, Tcentralnоe village</p></bio><xref ref-type="aff" rid="aff-1"/></contrib></contrib-group><aff-alternatives id="aff-1"><aff xml:lang="ru">Мироновский институт пшеницы имени В.Н. Ремесло Национальной академии аграрных наук Украины<country>Украина</country></aff><aff xml:lang="en">The V.N. Remeslo Mironovka Institute of Wheat of NAAS of Ukraine<country>Ukraine</country></aff></aff-alternatives><pub-date pub-type="collection"><year>2019</year></pub-date><pub-date pub-type="epub"><day>26</day><month>02</month><year>2019</year></pub-date><volume>23</volume><issue>1</issue><fpage>110</fpage><lpage>118</lpage><permissions><copyright-statement>Copyright &amp;#x00A9; Гудзенко В.Н., 2019</copyright-statement><copyright-year>2019</copyright-year><copyright-holder xml:lang="ru">Гудзенко В.Н.</copyright-holder><copyright-holder xml:lang="en">Gudzenko V.N.</copyright-holder><license license-type="creative-commons-attribution" xlink:href="https://creativecommons.org/licenses/by/4.0/" xlink:type="simple"><license-p>This work is licensed under a Creative Commons Attribution 4.0 License.</license-p></license></permissions><self-uri xlink:href="https://vavilov.elpub.ru/jour/article/view/1876">https://vavilov.elpub.ru/jour/article/view/1876</self-uri><abstract><p>В связи с глобальными климатическими изменениями последних лет остро стоит вопрос повышения адаптивного потенциала сельскохозяйственных культур. Необходимо создание сортов озимых зерновых как с экологической адаптивностью, так и способностью формировать стабильный уровень урожайности в разные по гидротермическим условиям года. С целью выведения сортов ячменя озимого с сочетанием урожайности и стабильности в Мироновском институте пшеницы имени В.Н. Ремесло Национальной академии аграрных наук Украины в 2012/2013–2014/2015 гг. испытывали 14 перспективных селекционных линий ячменя озимого, используя четыре различных срока сева. С помощью дисперсионного анализа выявлены достоверные вклады в вариацию урожайности: условий среды – 64.59 %, взаимодействия генотип–среда – 16.84 % и генотипа – 15.57 %. Сроки сева существенно влияли на увеличение варьирования урожайности линий. Разница между средними значениями урожайности по срокам сева в пределах года составляла: 2012/2013 г. – 1.05 т/га, 2013/2014 г. – 0.90 т/га, 2014/2015 г. – 1.25 т/га. Для характеристики взаимодействия генотип–среда и ранжирования линий по урожайности применяли несколько наиболее распространенных статистических параметров адаптивности, стабильности, пластичности и GGE biplot. Использование различных сроков сева на завершающем этапе селекционного процесса ячменя озимого – простой, но эффективный подход, позволяющий более детально оценить адаптивность селекционных линий в меняющихся условиях вегетации. По сравнению с статистическими показателями GGE biplot имеет ряд преимуществ для характеристики взаимодействия генотип–среда. Эта графическая модель позволяет визуализировать ранжирование сред по дифференцирующей способности и репрезентативности, а также выделять генотипы как специфически адаптированные, так и с оптимальным сочетанием потенциала урожайности и стабильности в совокупности сред (мегасред). Выделены селекционная линия с оптимальным сочетанием урожайности и стабильности Pallidum 4816, а также высокопродуктивные линии Pallidum 4857 и Pallidum 4659, которые переданы на государственное сортоиспытание Украины как новые сорта ячменя озимого: МИП Ясон, МИП Оскар и МИП Гладиатор.</p></abstract><trans-abstract xml:lang="en"><p>Due to current global climate changes, the issue of improving adaptive capacity of crops is of high importance. It is important to create winter crop varieties with both ecological adaptability and yield stability in years with different hydrothermal conditions. In order to develop winter barley varieties with a combination of yield and stability, 14 promising breeding lines have been evaluated in the conditions of the V.M. Remeslo Myronovka Institute of Wheat of NAAS of Ukraine in 2012/2013–2014/2015 using four different sowing dates. The ANOVA revealed a reliable part in yield variation: 64.59 % for environment, 16.84 % for genotype–environment interaction, and 15.57 % for genotype. The sowing dates significantly increased the yield variation of the breeding lines. The differences between the average yields of the lines depending on sowing date within the year were 1.05 t/ha in 2012/2013, 0.90 t/ha in 2013/2014, and 1.25 t/ha in 2014/2015. For genotype–environment interaction interpretation and ranking lines by yield a number of the most known statistical parameters of adaptability, stability, and plasticity and GGE biplot were applied. The use of different sowing dates at the final stage of the winter barley breeding process is a simple but effective approach that allows a more detailed assessment of the adaptive potential of breeding lines in various growing conditions. As compared to statistical parameters, GGE biplot has some advantages for interpretation of genotype–environment interaction. This graphic model allows ranking environments to be visualized for their discriminating ability and representativeness, as well as both specifically adapted genotypes and the ones with the optimal combination of yield potential and stability to be identified in a set of environments (mega-environment). The breeding line Pallidum 4816 with the optimal combination of yield and stability, as well as the high-yielding breeding lines Pallidum 4857 and Pallidum 4659 were identified and submitted to the State Variety Testing of Ukraine as the new winter barley varieties MIP Yason, MIP Oskar and MIP Hladiator.</p></trans-abstract><kwd-group xml:lang="ru"><kwd>озимый ячмень</kwd><kwd>селекционные линии</kwd><kwd>срок сева</kwd><kwd>урожайность</kwd><kwd>взаимодействие генотип– среда</kwd><kwd>параметры адаптивности</kwd><kwd>пластичности</kwd><kwd>стабильности</kwd><kwd>GGE biplot</kwd></kwd-group><kwd-group xml:lang="en"><kwd>winter barley</kwd><kwd>breeding lines</kwd><kwd>sowing date</kwd><kwd>yield</kwd><kwd>genotype–environment interaction</kwd><kwd>parameters of adaptability</kwd><kwd>plasticity</kwd><kwd>stability</kwd><kwd>GGE biplot</kwd></kwd-group></article-meta></front><back><ref-list><title>References</title><ref id="cit1"><label>1</label><citation-alternatives><mixed-citation xml:lang="ru">Гудзенко В.М., Демидов О.А., Василькiвський С.П., Коляденко С.С. Графiчний аналiз адаптивнiстi селекцiйних лiнiй ячменю ярого в Центральному Лiсостепу Украïни. Сортовивчення та охорона прав на сорти рослин. 2017;13(1):20-27. DOI 10.21498/2518-1017.1.2017.97233.</mixed-citation><mixed-citation xml:lang="en">Gudzenko V.N., Demydov A.A., Vasylkivskyi S.P., Koliadenko S.S. Graphical analysis of adaptability of spring barley breeding lines in the Central Forest-Steppe zone of Ukraine. Plant Varieties Studying and Protection. 2017;13(1):20-27. DOI 10.21498/2518-1017.1. 2017.97233. (in Ukrainian)</mixed-citation></citation-alternatives></ref><ref id="cit2"><label>2</label><citation-alternatives><mixed-citation xml:lang="ru">Кильчевский А.В., Хотылева Л.В. Метод оценки адаптивной способности и стабильности генотипов дифференцирующей способности среды. Сообщение 1. Обоснование метода. Генетика. 1985;21(9):1481-1490.</mixed-citation><mixed-citation xml:lang="en">Kilchevskiy A.V., Khotyleva L.V. Method of evaluation of adaptive ability and stability of genotypes, the differentiating ability of environment. Report 1. Validation of the method. Genetika = Genetics (Moscow). 1985;21(9):1481-1490. (in Russian)</mixed-citation></citation-alternatives></ref><ref id="cit3"><label>3</label><citation-alternatives><mixed-citation xml:lang="ru">Ahmadi J., Vaezi B., Fotokian M.H. Graphical analysis of multi-environment trials for barley yield using AMMI and GGE-biplot under rain-fed conditions. J. Plant Physiol. Breed. 2012;2(1):43-54.</mixed-citation><mixed-citation xml:lang="en">Ahmadi J., Vaezi B., Fotokian M.H. Graphical analysis of multi-environment trials for barley yield using AMMI and GGE-biplot under rain-fed conditions. J. Plant Physiol. Breed. 2012;2(1):43-54.</mixed-citation></citation-alternatives></ref><ref id="cit4"><label>4</label><citation-alternatives><mixed-citation xml:lang="ru">Dimitrova-Doneva M., Valcheva D., Mihova G., Dyulgerova B. Genotype-environment interaction and stability analysis for grain yield of winter barley in the conditions of North-East and South Bulgaria. Agric. Sci. Technol. 2016;8(1):19-23.</mixed-citation><mixed-citation xml:lang="en">Dimitrova-Doneva M., Valcheva D., Mihova G., Dyulgerova B. Genotype-environment interaction and stability analysis for grain yield of winter barley in the conditions of North-East and South Bulgaria. Agric. Sci. Technol. 2016;8(1):19-23.</mixed-citation></citation-alternatives></ref><ref id="cit5"><label>5</label><citation-alternatives><mixed-citation xml:lang="ru">Dimova D., Krasteva L., Panayotov N., Svetleva D., Dimitrova M., Georgieva T. Evaluation of the yield and the yield stability of perspective lines of barley. Agroznanje. 2012;13(1):55-60.</mixed-citation><mixed-citation xml:lang="en">Dimova D., Krasteva L., Panayotov N., Svetleva D., Dimitrova M., Georgieva T. Evaluation of the yield and the yield stability of perspective lines of barley. Agroznanje. 2012;13(1):55-60.</mixed-citation></citation-alternatives></ref><ref id="cit6"><label>6</label><citation-alternatives><mixed-citation xml:lang="ru">Eberhart S.A., Russel W.A. Stability parameters for comparing varieties. Crop. Sci. 1966;6:36-40. DOI 10.2135/cropsci1966.0011183X0 00600010011x.</mixed-citation><mixed-citation xml:lang="en">Eberhart S.A., Russel W.A. Stability parameters for comparing varieties. Crop. Sci. 1966;6:36-40. DOI 10.2135/cropsci1966.0011183X0 00600010011x.</mixed-citation></citation-alternatives></ref><ref id="cit7"><label>7</label><citation-alternatives><mixed-citation xml:lang="ru">Fashadfar E., Mohammadi R., Aghaee M., Vaisi Z. GGE biplot analysis of genotype×environment interaction in wheat-barley disomic addition lines. Aust. J. Crop Sci. 2012;6(6):1074-1079.</mixed-citation><mixed-citation xml:lang="en">Fashadfar E., Mohammadi R., Aghaee M., Vaisi Z. GGE biplot analysis of genotype×environment interaction in wheat-barley disomic addition lines. Aust. J. Crop Sci. 2012;6(6):1074-1079.</mixed-citation></citation-alternatives></ref><ref id="cit8"><label>8</label><citation-alternatives><mixed-citation xml:lang="ru">Finlay K.W., Wilkinson G.N. The analysis adaptation in a plant breeding programme. Aust. J. Agric. Res. 1963;14:742-754. DOI 10.1071/AR9630742.</mixed-citation><mixed-citation xml:lang="en">Finlay K.W., Wilkinson G.N. The analysis adaptation in a plant breeding programme. Aust. J. Agric. Res. 1963;14:742-754. DOI 10.1071/AR9630742.</mixed-citation></citation-alternatives></ref><ref id="cit9"><label>9</label><citation-alternatives><mixed-citation xml:lang="ru">Frutos E., Galindo M.P., Leiva V. An interactive biplot implementation in R for modeling genotype-by-environment interaction. Stoch. Environ. Res. Risk Assess. 2014;28:1629-1641. DOI 10.1007/s00477013-0821-z.</mixed-citation><mixed-citation xml:lang="en">Frutos E., Galindo M.P., Leiva V. An interactive biplot implementation in R for modeling genotype-by-environment interaction. Stoch. Environ. Res. Risk Assess. 2014;28:1629-1641. DOI 10.1007/s00477013-0821-z.</mixed-citation></citation-alternatives></ref><ref id="cit10"><label>10</label><citation-alternatives><mixed-citation xml:lang="ru">Gebremedhin W., Firew M., Tesfye B. Stability analysis of food barley genotypes in Northern Ethiopia. Afr. Crop Sci. J. 2014;22(2): 145-153.</mixed-citation><mixed-citation xml:lang="en">Gebremedhin W., Firew M., Tesfye B. Stability analysis of food barley genotypes in Northern Ethiopia. Afr. Crop Sci. J. 2014;22(2): 145-153.</mixed-citation></citation-alternatives></ref><ref id="cit11"><label>11</label><citation-alternatives><mixed-citation xml:lang="ru">Huehn M. Nonparametric measures of phenotypic stability. Part 1: Theory. Euphytica. 1990;47:189-194. DOI 10.1007/BF00024241.</mixed-citation><mixed-citation xml:lang="en">Huehn M. Nonparametric measures of phenotypic stability. Part 1: Theory. Euphytica. 1990;47:189-194. DOI 10.1007/BF00024241.</mixed-citation></citation-alternatives></ref><ref id="cit12"><label>12</label><citation-alternatives><mixed-citation xml:lang="ru">Ingvordsen C.H., Backes G., Lyngkjær M.F., Peltonen-Sainio P., Jensen J.D., Jalli M., Jahoor A., Rasmussen M., Mikkelsen T.N., Stockmarr A., Jørgensen R.B. Significant decrease in yield under future climate conditions: Stability and production of 138 spring barley accessions. Europ. J. Agron. 2015;63:105-113.</mixed-citation><mixed-citation xml:lang="en">Ingvordsen C.H., Backes G., Lyngkjær M.F., Peltonen-Sainio P., Jensen J.D., Jalli M., Jahoor A., Rasmussen M., Mikkelsen T.N., Stockmarr A., Jørgensen R.B. Significant decrease in yield under future climate conditions: Stability and production of 138 spring barley accessions. Europ. J. Agron. 2015;63:105-113.</mixed-citation></citation-alternatives></ref><ref id="cit13"><label>13</label><citation-alternatives><mixed-citation xml:lang="ru">Jalata Z. GGE-biplot analysis of multi-environment yield trials of barley (Hordeum vulgare L.) genotypes in Southeastern Ethiopia Highlands. Int. J. Plant Breed. Genet. 2011;5(1):59-75.</mixed-citation><mixed-citation xml:lang="en">Jalata Z. GGE-biplot analysis of multi-environment yield trials of barley (Hordeum vulgare L.) genotypes in Southeastern Ethiopia Highlands. Int. J. Plant Breed. Genet. 2011;5(1):59-75.</mixed-citation></citation-alternatives></ref><ref id="cit14"><label>14</label><citation-alternatives><mixed-citation xml:lang="ru">Lin C.S., Binns M.R. A superiority measure of cultivar performance for cultivar×location data. Can. J. Plant Sci. 1988;68:193-198. DOI 10.4141/cjps88-018.</mixed-citation><mixed-citation xml:lang="en">Lin C.S., Binns M.R. A superiority measure of cultivar performance for cultivar×location data. Can. J. Plant Sci. 1988;68:193-198. DOI 10.4141/cjps88-018.</mixed-citation></citation-alternatives></ref><ref id="cit15"><label>15</label><citation-alternatives><mixed-citation xml:lang="ru">Macholdt J., Honermeier B. Impact of climate change on cultivar choice: adaptation strategies of farmers and advisors in German cereal production. Agronomy. 2016;6(40). DOI 10.3390/agronomy 6030040.</mixed-citation><mixed-citation xml:lang="en">Macholdt J., Honermeier B. Impact of climate change on cultivar choice: adaptation strategies of farmers and advisors in German cereal production. Agronomy. 2016;6(40). DOI 10.3390/agronomy 6030040.</mixed-citation></citation-alternatives></ref><ref id="cit16"><label>16</label><citation-alternatives><mixed-citation xml:lang="ru">Mirosavljevic M., Przulj N., Bocanski J., Stanisavljevic D., Mitrovic B. The application of AMMI model for barley cultivars evaluation in multi-year trials. Genetika. 2014;46(2):445-454.</mixed-citation><mixed-citation xml:lang="en">Mirosavljevic M., Przulj N., Bocanski J., Stanisavljevic D., Mitrovic B. The application of AMMI model for barley cultivars evaluation in multi-year trials. Genetika. 2014;46(2):445-454.</mixed-citation></citation-alternatives></ref><ref id="cit17"><label>17</label><citation-alternatives><mixed-citation xml:lang="ru">Mohammadi M., Noorinia A.A., Khalilzadeh G.R., Hosseinpoo T. Application of GGE biplot analysis to investigate GE interaction on barley grain yield. Curr. Opin. Agric. 2015;4(1):25-32.</mixed-citation><mixed-citation xml:lang="en">Mohammadi M., Noorinia A.A., Khalilzadeh G.R., Hosseinpoo T. Application of GGE biplot analysis to investigate GE interaction on barley grain yield. Curr. Opin. Agric. 2015;4(1):25-32.</mixed-citation></citation-alternatives></ref><ref id="cit18"><label>18</label><citation-alternatives><mixed-citation xml:lang="ru">Mortazavian S.M.M., Nikkhah H.R., Hassani F.A., Sharif-al-Hosseini M., Taheri M., Mahlooji M. GGE biplot and AMMI analysis of yield performance of barley genotypes across different environments in Iran. J. Agr. Sci. Tech. 2014;16:609-622.</mixed-citation><mixed-citation xml:lang="en">Mortazavian S.M.M., Nikkhah H.R., Hassani F.A., Sharif-al-Hosseini M., Taheri M., Mahlooji M. GGE biplot and AMMI analysis of yield performance of barley genotypes across different environments in Iran. J. Agr. Sci. Tech. 2014;16:609-622.</mixed-citation></citation-alternatives></ref><ref id="cit19"><label>19</label><citation-alternatives><mixed-citation xml:lang="ru">Nicotra A.B., Atkin O.K., Bonser S.P., Davidson A.M., Finnegan E.J., Mathesius U., Poot P., Purugganan M.D., Richards C.L., Valladares F., van Kleunen M. Plant phenotypic plasticity in a changing climate. Trends Plant Sci. 2010;15(12):684-692. DOI 10.1016/j.tplants.2010.09.008.</mixed-citation><mixed-citation xml:lang="en">Nicotra A.B., Atkin O.K., Bonser S.P., Davidson A.M., Finnegan E.J., Mathesius U., Poot P., Purugganan M.D., Richards C.L., Valladares F., van Kleunen M. Plant phenotypic plasticity in a changing climate. Trends Plant Sci. 2010;15(12):684-692. DOI 10.1016/j.tplants.2010.09.008.</mixed-citation></citation-alternatives></ref><ref id="cit20"><label>20</label><citation-alternatives><mixed-citation xml:lang="ru">Sarkar B., Sharma R.C., Verma R.P.S., Sarkar A., Sharma I. Identifying superior feed barley genotypes using GGE biplot for diverse environments in India. Indian J. Genet. Plant Breed. 2014;74(1): 26-33. Shukla G.K. Some statistical aspects of partitioning genotype-enviromental components of variability. Heredity. 1972;29:237-245. DOI 10.1038/hdy.1972.87.</mixed-citation><mixed-citation xml:lang="en">Sarkar B., Sharma R.C., Verma R.P.S., Sarkar A., Sharma I. Identifying superior feed barley genotypes using GGE biplot for diverse environments in India. Indian J. Genet. Plant Breed. 2014;74(1): 26-33. Shukla G.K. Some statistical aspects of partitioning genotype-enviromental components of variability. Heredity. 1972;29:237-245. DOI 10.1038/hdy.1972.87.</mixed-citation></citation-alternatives></ref><ref id="cit21"><label>21</label><citation-alternatives><mixed-citation xml:lang="ru">Solonechnyi P., Vasko N., Naumov O., Solonechnaya O., Vazhenina O., Bondareva O., Logvinenko Yu. GGE biplot analysis of genotype by environment interaction of spring barley varieties. Zemdirbyste-Agriculture. 2015;102(4):431-436. DOI 10.13080/z-a.2015.102.055.</mixed-citation><mixed-citation xml:lang="en">Solonechnyi P., Vasko N., Naumov O., Solonechnaya O., Vazhenina O., Bondareva O., Logvinenko Yu. GGE biplot analysis of genotype by environment interaction of spring barley varieties. Zemdirbyste-Agriculture. 2015;102(4):431-436. DOI 10.13080/z-a.2015.102.055.</mixed-citation></citation-alternatives></ref><ref id="cit22"><label>22</label><citation-alternatives><mixed-citation xml:lang="ru">Tai G.C.C. Genotypic stability analysis and its application to potato regional traits. Crop Sci. 1971;11:184-190. DOI 10.2135/cropsci1971.0011183X001100020006x.</mixed-citation><mixed-citation xml:lang="en">Tai G.C.C. Genotypic stability analysis and its application to potato regional traits. Crop Sci. 1971;11:184-190. DOI 10.2135/cropsci1971.0011183X001100020006x.</mixed-citation></citation-alternatives></ref><ref id="cit23"><label>23</label><citation-alternatives><mixed-citation xml:lang="ru">Wricke G. Über eine methode zur erfassung der okologischen streubreite in feldversuchen. Z. Pflanzenzuchtg. 1962;47:92-96.</mixed-citation><mixed-citation xml:lang="en">Wricke G. Über eine methode zur erfassung der okologischen streubreite in feldversuchen. Z. Pflanzenzuchtg. 1962;47:92-96.</mixed-citation></citation-alternatives></ref><ref id="cit24"><label>24</label><citation-alternatives><mixed-citation xml:lang="ru">Yan W., Hunt L.A., Sheny Q., Szlavnics Z. Cultivar evaluation and mega-environment investigation based on the GGE biplot. Crop Sci. 2000;40:597-605. DOI 10.2135/cropsci2000.403597x.</mixed-citation><mixed-citation xml:lang="en">Yan W., Hunt L.A., Sheny Q., Szlavnics Z. Cultivar evaluation and mega-environment investigation based on the GGE biplot. Crop Sci. 2000;40:597-605. DOI 10.2135/cropsci2000.403597x.</mixed-citation></citation-alternatives></ref><ref id="cit25"><label>25</label><citation-alternatives><mixed-citation xml:lang="ru">Yan W., Kang M.S., Ma B., Woods S., Cornelius P.L. GGE biplot vs. AMMI analysis of genotype-by-environment data. Crop Sci. 2007; 47:641-653. DOI 10.2135/cropsci2006.06.0374.</mixed-citation><mixed-citation xml:lang="en">Yan W., Kang M.S., Ma B., Woods S., Cornelius P.L. GGE biplot vs. AMMI analysis of genotype-by-environment data. Crop Sci. 2007; 47:641-653. DOI 10.2135/cropsci2006.06.0374.</mixed-citation></citation-alternatives></ref><ref id="cit26"><label>26</label><citation-alternatives><mixed-citation xml:lang="ru">Yan W., Tinker N.A. Biplot analysis of multi-environment trial data: principles and applications. Can. J. Plant. Sci. 2006;86:623-645. DOI 10.4141/P05-169.</mixed-citation><mixed-citation xml:lang="en">Yan W., Tinker N.A. Biplot analysis of multi-environment trial data: principles and applications. Can. J. Plant. Sci. 2006;86:623-645. DOI 10.4141/P05-169.</mixed-citation></citation-alternatives></ref></ref-list><fn-group><fn fn-type="conflict"><p>The authors declare that there are no conflicts of interest present.</p></fn></fn-group></back></article>
