Preliminary Results on Agronomic Behavior of Table Grapes on Different Rootstocks in Brazilian Cerrado Conditions

Studies are necessary to understand the productive behavior of grape cultivars on different rootstocks, in regions where their cultivation is potentially favorable. Thus, the objective of this work was to evaluate the influence of the combination of canopy x rootstocks on production, fruit quality, thermal requirement and maturation curve of table grape cultivars, in brazilian Cerrado conditions. A randomized block design was adopted, with five repetitions. The studied combinations were composed by the rootstocks IAC 766 ‘Campinas’ and IAC 572 ‘Jales’ under the cultivars ‘BRS Vitória’, ‘BRS Núbia’, ‘BRS Isis’ and ‘Niágara rosada’. Each cultivar was evaluated in isolation according to the two rootstocks. The cultivar ‘BRS Vitória’ showed higher productivity on the rootstock IAC 766 and greater development of bunches and berries on the IAC 572. This cultivar presented a thermal requirement of 1419 Degrees-Day from pruning until harvest. The ‘BRS Núbia’ cultivar showed higher productivity on the IAC 572 rootstock. The thermal requirement for ‘BRS Núbia’ to complete its cycle was 1725 Degrees-Day. The cultivar ‘‘BRS Isis’’ on the rootstock IAC 572 showed higher values of productivity, yield and number of bunches per plant. The IAC 766 ‘BRS Isis’ rootstock showed a thermal requirement of 1958 Degrees-Day. For IAC 572, 2079 Degrees-Day were required. The rootstocks evaluated did not influence the productive and physical-chemical characteristics of the cultivar ‘Niágara rosada’, the thermal requirement was 1622 Degrees-Day, for both rootstocks

PARCHMENT PRESENCE AND TREATMENT WITH VITAMINS ON THE EMERGENCE OF COFFEE SEEDLINGS

The seedling production of is a stage of great importance for several crops. The seeds of the coffee tree present germination difficulties due to the physical barrier imposed by the parchment. The objective of this study was to evaluate the effect of parchment presence and pre-sowing treatment with vitamins on the emergence of coffee seedlings. The experimental design was completely randomized, in a 2x4 factorial design (parchment presence x types of vitamins), in four replicates with 15 seeds per plot. Vitamins concentration was 100 mg l-1 of thiamine, 100 mg l-1 niacin, 50 mg l-1 thiamine + 50 mg l-1 niacin and a control treatment. The evaluations were performed weekly, with the emerged seedlings being counted until the 76th day after sowing. The emergence percentage was obtained after the 146th day after sowing, counting the number of normal seedlings obtained. The parchment removal increases the speed and the emergence percentage of the coffee seedlings. The treatment with vitamin did not influenced the emergence characteristics of the coffee tree

VEGETATIVE DEVELOPMENT OF VINE ROOTSTOCK CULTIVARS IN BRAZILIAN CERRADO CONDITIONS

In the State of Goiás, studies related to the vine's responses to the region's edaphoclimatic conditions are scarce. Therefore, the objective of this work was to evaluate the growth of three vine rootstock cultivars, IAC 572 'Jales', IAC 313 'Tropical' and IAC 766 'Campinas', in the region of Goiânia, GO, after drastic pruning for uniformity. To evaluate the growth of rootstocks, the experiment was carried out in random blocks, in a double factorial scheme (3x7), with five replications, each repetition formed by a plant. The first factor consisted of three rootstocks: IAC 313 ‘Tropical’, IAC 572 ‘Jales’ and IAC 766 ‘Campinas’. The plants were evaluated after 45 days after a drastic uniformization pruning, totaling seven evaluations (45, 60, 75, 90, 105, 120, 135 days after pruning), this being the second factor. The diameter of the main branch at the height of grafting (80 cm) and length of the main branch were evaluated. With the data on the diameter and length of the main branch, the absolute growth rate was calculated. The IAC 572 'Jales' rootstock cultivar has greater vigor for branch growth, being 69% and 47.3% longer in length, and 49.8% and 18.8% longer in diameter than the IAC rootstock. IAC 313 'Tropical' 'and' IAC 766 'Campinas', respectively. The IAC 766 ‘Campinas’ rootstock cultivar, although it has low vigor in branch growth, presents satisfactory development.No Estado de Goiás são escassos os estudos relacionados às respostas da videira às condições edafoclimáticas da região. Portanto, objetivou-se com este trabalho avaliar o crescimento de três cultivares porta-enxerto de videira, IAC 572 ‘Jales’, IAC 313 ‘Tropical’ e IAC 766 ‘Campinas’, na região de Goiânia, GO, após poda drástica para uniformização. Para avaliar o crescimento dos porta-enxertos, o experimento foi realizado em blocos ao acaso, em esquema fatorial duplo (3x7), com cinco repetições, cada repetição formada por uma planta. O primeiro fator consistiu em três porta-enxertos: IAC 313 ‘Tropical’, IAC 572 ‘Jales’ e IAC 766 ‘Campinas’. As plantas foram avaliadas a partir de 45 dias após uma poda drástica de uniformização, totalizando sete avaliações (45, 60, 75, 90, 105, 120, 135 dias após a poda), sendo este o segundo fator. Foram avaliados o diâmetro do ramo principal à altura de enxertia (80 cm), e comprimento do ramo principal. De posse dos dados do diâmetro e comprimento do ramo principal, calculou-se a taxa de crescimento absoluto. O cultivar porta-enxerto IAC 572 ‘Jales’ apresenta maior vigor para crescimento de ramo, sendo em comprimento 69% e 47,3% superior, e em diâmetro 49,8% e 18,8% superior aos porta-enxertos IAC 313 ‘Tropical’’ e ‘IAC 766 ‘Campinas’, respectivamente. A cultivar porta-enxerto IAC 766 ‘Campinas’ embora, tenha vigor baixo em crescimento de ramo, apresenta desenvolvimento satisfatório

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost