Phenology and viticultural performance of different fungus-resistant grapevine advanced selections at three different altitudes in southern Brazil
Andressa Hilha Dias,
Luiz Fernando Spanholi,
André Luiz Kulkamp de Souza
et al.
Abstract:The objective of this work was to characterize the phenology and the viticultural performance of advanced selections of grapevines resistant to fungal diseases obtained by the Julius Kühn Institute, Institute for Grapevine Breeding Geilweilerhof. The experiment was conducted in three different grape-growing regions of Santa Catarina State, Brazil, in the municipalities of Videira (840 m), São Joaquim (1110 m) and Curitibanos (1000 m) during the seasons of 2018/2019 and 2019/2020. The advanced selections evalua… Show more
“…Since the selection of suitable genotypes has always been a challenge for plant breeders, the use of MGIDI has grown widely among breeders, helping to identify superior genotypes that combine desired different traits [33][34][35][36]. Amrate et al [37] used the MGIDI method to identify high-yielding charcoal rot-resistant soybean genotypes.…”
Rice blast disease, caused by the fungus Magnaporthe oryzae, poses a significant threat to rice cultivation. One effective way to deal with this disease is to identify and introduce resistant varieties using different breeding methods. This study utilized a population of 153 recombinant inbred lines (RILs) derived from the crossing of the Shahpasand (SH) and IR28 varieties, characterized by susceptibility and resistance to leaf blast, respectively. In combination with 12 control varieties, these genotypes were subjected to an extensive evaluation of disease severity (5 stages), the area under the disease progress curve (AUDPC), type, and the infection rate in 2021 and 2022. Analysis of variance revealed significant genetic variation, highlighting the potential of the RIL population for identifying and selecting resistant lines. Employing cluster analysis and the multi-trait genotype-ideotype distance index (MGIDI), 17 lines were identified as the most resistant over a two-year evaluation period. The average AUDPC for these resistant lines was estimated at 2.435 ± 0.114, and lines 17 and 111 had the lowest AUDPC (1.526 and 1.630, respectively) and showed the least infection in two years. Conversely, lines 42 and 43 showed the highest AUDPC values (255.312 and 248.209) along with heightened sensitivity. The use of MGIDI yielded a substantial selection differential (SD) of −59.12% for traits related to leaf blast disease resistance, demonstrating the effectiveness of this method. Furthermore, new recombinant populations are expected to be developed in future plant breeding projects by crossing the most susceptible and resistant lines, which will be new sources of resistance to this disease.
“…Since the selection of suitable genotypes has always been a challenge for plant breeders, the use of MGIDI has grown widely among breeders, helping to identify superior genotypes that combine desired different traits [33][34][35][36]. Amrate et al [37] used the MGIDI method to identify high-yielding charcoal rot-resistant soybean genotypes.…”
Rice blast disease, caused by the fungus Magnaporthe oryzae, poses a significant threat to rice cultivation. One effective way to deal with this disease is to identify and introduce resistant varieties using different breeding methods. This study utilized a population of 153 recombinant inbred lines (RILs) derived from the crossing of the Shahpasand (SH) and IR28 varieties, characterized by susceptibility and resistance to leaf blast, respectively. In combination with 12 control varieties, these genotypes were subjected to an extensive evaluation of disease severity (5 stages), the area under the disease progress curve (AUDPC), type, and the infection rate in 2021 and 2022. Analysis of variance revealed significant genetic variation, highlighting the potential of the RIL population for identifying and selecting resistant lines. Employing cluster analysis and the multi-trait genotype-ideotype distance index (MGIDI), 17 lines were identified as the most resistant over a two-year evaluation period. The average AUDPC for these resistant lines was estimated at 2.435 ± 0.114, and lines 17 and 111 had the lowest AUDPC (1.526 and 1.630, respectively) and showed the least infection in two years. Conversely, lines 42 and 43 showed the highest AUDPC values (255.312 and 248.209) along with heightened sensitivity. The use of MGIDI yielded a substantial selection differential (SD) of −59.12% for traits related to leaf blast disease resistance, demonstrating the effectiveness of this method. Furthermore, new recombinant populations are expected to be developed in future plant breeding projects by crossing the most susceptible and resistant lines, which will be new sources of resistance to this disease.
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