Effect of Varieties and Plant Population Densities on Dry Matter Production, Radiation Interception and Radiation Energy Conversion in Peanut

A. Suprapto,Y. Sugito,S. M. Sitompul,S. Sudaryono

Published 2012 in Journal of Tropical Life Science

ABSTRACT

The solar radiation is one of the major criteria to obtaining advantages on peanuts (Arachishypogaea L.). Although various combinations of crops have been reported, but variety association and plant population densities (PPD) during the periodically stage of growth on peanuts have yet to be analyzed. Dry matter production (DM), radiation energy interception, and radiation energy conversions were monitored over the growth period of two varieties of peanut. An experiment was conducted in Jambegede Research Farm, Indonesian Legume and  Tuber Crops Research Institute, Malang, East Java, Indonesia, from July until October 2011. The experiment was arranged in a Split Plot Design with three replications. Peanut varieties, as the main plot consisted of two treatments: Kelinci and Kancil variety. In addition, five PPD variations as sub plot consisted of 8.1, 11.1, 16.0, 25.0 and 44.4 plant m-2 were arranged in a square spacing. The results showed that DM production  from high PPD increased gradually to lower PPD in all varieties. Interception efficiency (IE) increased in all varieties from early sowing. A plant population density of 25.0 m-2 and 44.4 plants m-2 intercepted more radiation over 11.1 or 16.0 plants m-2. Conversion efficiency of radiation energy (CE) to total dry matter production on Kelinci variety (1.52%) indicated  a  slight higher percentage than on Kancil variety (1.41%). Moreover, the CE and IE values indicated a decrease  as the PPD  increased on maximum DM.

PUBLICATION RECORD

  • Publication year

    2012

  • Venue

    Journal of Tropical Life Science

  • Publication date

    2012-09-01

  • Fields of study

    Agricultural and Food Sciences, Mathematics

  • Identifiers
  • External record

    Open on Semantic Scholar

  • Source metadata

    Semantic Scholar

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