CD Skripsi

Analisis Korelasi Dan Sidik Lintas Berbagai Karakter Kuantitatif Pada 20 Genotipe Cabai (Capsicum Annuum) Di Lahan Gambut

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ABSTRACT
Productivity of chili (Capsicum annuum) in Riau is still low due to the condition
of the land which is mostly peatland. Producing superior varieties of peatland
tolerant chilies through plant breeding requires specific selection criteria. The
purpose of this research was to obtain information about the close relationship
between quantitative characters and yield characters and the direct or indirect
effect between quantitative characters and chili yields using correlation and path
analysis. This research was conducted on Manunggal Street, Tuah Karya Village,
Tampan District, Pekanbaru City, Riau and the Plant Breeding Laboratory of the
Faculty of Agriculture, Riau University in November 2020-April 2021 using a
randomized block design with 20 genotypes of chili treatment and 3 replications.
There are 13 quantitative characters observed. Data were analyzed using
correlation and path analysis through SAS 9.0 and MINITAB 14 software. The
results of the correlation analysis showed the highest and very significant positive
correlation with fruit weight per plant, that is weight per fruit, fruit length, fruit
diameter, and fruit flesh thickness. Path analysis showed that the character of the
weight per fruit had a direct effect on the weight of the fruit per plant, while the
character of fruit length, fruit diameter and fruit flesh thickness had an indirect
effect on the weight of the fruit per plant through the weight per fruit.
Keywords: chili, correlation and path analysis.

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Ketersediaan

Informasi Detail

Judul Seri

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No. Panggil

06 01. 122 (0031)

Penerbit

Pekanbaru : Universitas Riau –Fakultas Pertanian - Agroteknologi., 2022

Deskripsi Fisik

x, 66 hlm.; ill.: 29 cm

Bahasa

Indonesia

ISBN/ISSN

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Klasifikasi

06 01. 122 (0031)

Tipe Isi

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Tipe Media

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Tipe Pembawa

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Edisi

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Subjek

Agroteknologi

Info Detail Spesifik

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Pernyataan Tanggungjawab

Daus

Versi lain/terkait

Lampiran Berkas

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