Acessibilidade / Reportar erro

Growth and Quality of Yerba Mate Seedlings Affected by Fertilizer Doses in South Brazil

Abstract:

Given the lack of information on the use of controlled-release fertilizers in yerba mate seedlings production, this study aimed to evaluate growth and morphological characteristics of seedlings produced with two controlled-release fertilizers applied at different doses. We used seeds from a clonal seed orchard, which were sown in a commercial substrate based on peat and vermiculite, with Osmocote® MiniPrill 3M (CRF 3M) and Basacote® Plus 9M (CRF 9M) fertilizers, both in doses of 0, 2, 4, 6, 8, 10, and 12 kg m-3. Seedling height and stem diameter were measured at 60, 90, 120, and 180 days after sowing and, at 180 days, shoot, root, and total biomass, tube withdrawal ease, and root aggregation. From these data, we calculated Dickson's quality index, technical efficiency, Height/Stem diameter ratio, and maximum technical efficiency dose. We verified values statistically superior to control treatment (0 kg m-3) in all variables in response to controlled-release fertilizer 3M and 9M, demonstrating the viability of yerba mate seedling production using controlled-release fertilizers. This is also evidenced through results obtained for growth in height and stem diameter. Although CRF 3M favored seedling growth, CRF 9M showed similar efficiency. The Osmocote® MiniPrill 3M is more efficient than Basacote® Plus 9M in most of the variables analyzed and has a lower input required to obtain quality seedlings. For these reasons, Osmocote® MiniPrill 3M is indicated to produce yerba mate seedlings in the dose 8.50 kg m-3.

Keywords:
controlled-release fertilizer; Ilex paraguariensis; plant nutrition; seedling production; forest nursery

HIGHLIGHTS

  • Cardiac mass image noise is diminished by Adaptive Vector Median Filter.

  • The masses were automatically segmented dependent on Linear Iterative Vessel Segmentation strategy followed by texture features extracted utilizing the Multiscale Local Binary Pattern method.

  • The classification done by Robust back propagation neural network.

Instituto de Tecnologia do Paraná - Tecpar Rua Prof. Algacyr Munhoz Mader, 3775 - CIC, 81350-010 Curitiba PR Brazil, Tel.: +55 41 3316-3052/3054, Fax: +55 41 3346-2872 - Curitiba - PR - Brazil
E-mail: babt@tecpar.br