DOSES DE BOKASHI EM COBERTURA NA PRODUÇÃO DE BETERRABA

A produção orgânica de hortaliças tem apresentado crescimento constante. Porém, ainda há necessidade de pesquisas em algumas etapas da produção, como a adubação. Na cultura da beterraba, são escassas as informações sobre a adubação orgânica em cobertura. Desta forma, objetivou-se com este trabalho avaliar a influência de doses de bokashi aplicadas em cobertura na produção de beterraba. Foram realizados dois experimentos na Fazenda Experimental São Manuel (FCA/UNESP) e estudadas cinco doses de bokashi em cobertura (0, 150, 300, 450 e 600 g m-2) e uma testemunha com cobertura inorgânica, utilizando-se um delineamento experimental de blocos ao acaso, com quatro repetições. No primeiro experimento, a adubação de plantio constou apenas de composto orgânico e no segundo, além do composto orgânico foi realizada a adubação inorgânica com NPK 4-14-8. As características avaliadas foram: altura da planta, massa da matéria fresca e seca da parte aérea e raiz, diâmetro e comprimento da raiz e produtividade. A aplicação de até 600 g m-2 de bokashi em cobertura proporcionou incremento na altura da planta, massa da matéria fresca de raiz, comprimento de raiz e produtividade da beterraba nos dois experimentos: com e sem adubação inorgânica no plantio. A adubação de plantio orgânica quando associada à inorgânica apresentou os melhores resultados dos caracteres avaliados, quando comparada à orgânica

Nitrogen doses and splitting in top dressing in the production and macronutrient content in fruits of zucchini

Nitrogen fertilization in cucurbits must be splitted, one part being supplied before planting and the rest applied in top dressing. However, there is a lack of research about this splitting throughout the cycle. The objective of this study was to evaluate the effect of nitrogen doses and splitting of this fertilization in top dressing on production and macronutrient content in fruits of zucchini. Two experiments were carried out, with thirteen treatments, in the factorial scheme 4x3+1, with four nitrogen doses in top dressing (62.5, 125.0, 187.5, 250.0 kg ha-1 of N), three splitting forms (1/6+1/3+1/2; 1/4+1/2+1/4; 1/3+1/3+1/3 of total dose in each application) and one treatment without fertilization in top dressing (control = dose zero), with four replicates. Experiment 1 and 2 were conducted in 2014 and 2015, respectively. Total and commercial fruit production (g), total and commercial fruit number per plant, length, diameter and average commercial fruit weight were evaluated. Only in experiment 2 the macronutrient content in the fruits were evaluated. In experiment 1, the 1/4+1/2+1/4 splitting provided greater number of total and commercial fruits per plant. In experiment 2, the increasing of the doses in the 1/6+1/3+1/2 and 1/3+1/3+1/3 splitting resulted in a linear increase in total and commercial fruit production. The decreasing order of macronutrient content in fruits was K>N>P>Ca>Mg>S

Pre-germination treatments of Paricá (Schizolobium amazonicum) seeds

Paricá seeds have dormancy and, even after mechanical scarification, these seeds show slow and uneven germination. Pre-germination treatments can be used to increase seed germination performance. Thus, the aimed to evaluate the physiological potential and initial growth of paricá seeds after pre-germination treatments, using different substances as plant regulators and nutrients, in addition to mechanical scarification. The experimental design was completely randomized, in a 2x7 factorial scheme, consisting of the following pre-germination treatments: mechanical scarification (10% and 50% of the seed coat) and seed pre-soaking [control-water, KNO3 ­0.2%, Ca(NO3)2 0.2%, gibberellin 0.02%, cytokinin 0.02%, and mixture of gibberellin + cytokinin (1:1)] besides a control group without pre-soaking, with four replicates. The study evaluated germination and emergence rates, germination and emergence speed indices, collar diameter, plant height, seedling dry mass, hypocotyl and seedling length, and electrical conductivity. It was observed that pre-soaking the seeds in gibberellin after mechanical scarification at 50% as a pre-germination treatment resulted in seeds with higher vigor expression and greater initial seedling growth

Castor bean cake in top-dressing application as a source of nitrogen on the production and quality of zucchini organic seeds

Studies in vegetables show that fertilization influences seed production positively, however, when the quality of the seeds is analyzed, the results are mostly inconsistent. The objective of this study was to evaluate the effect of castor bean cake (CBC) dose splitting in top-dressing application on the production and quality of zucchini organic seeds, as well as its effect on the macronutrient content of fruits and seeds. The experimental design was a randomized block design and four replications. There were 13 treatments with four doses of CBC in top-dressing (1.7, 3.4, 5.1 and 6.8 t ha-1) per three applications (33.3-33.3-33.3%, 50-50% and 33-50-17%) and the control treatment without any kind of top-dressing fertilization. The study evaluated the number of ripe fruits per plant, the production (number and mass) of seeds per fruit and per plant, the mass of one hundred seeds, seed germination, first germination count, and macronutrient content in the diagnosis leaf, in mature fruits (without seeds) and seeds. The number of ripe fruits per plant was not affected by the CBC doses in top-dressing, neither by the splitting of the applications. It was observed that the number of seeds per fruit, mass of seeds per fruit and mass of seeds per plant showed quadratic behavior. Regarding seed quality, only the 1.7; 3.4 and 5.1 t ha-1 doses produced seed with superior quality than the other doses. In conclusion, the CBC doses increased the number of seeds per fruit, mass of seeds per fruit and per plant up to the 4.5t ha-1 dose, approximately

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