scholarly journals Pengaruh Genetik dan Lingkungan Terhadap Pertumbuhan Sengon (Falcataria molucanna) Ras Lahan Jawa

2018 ◽  
Vol 4 (2) ◽  
pp. 35-41
Author(s):  
Mudji Susanto ◽  
Liliana Baskorowati

Tegakan sengon (Falcataria molucanna) ras lahan Jawa dibangun di  Bali dengan tujuan untuk mengetahui keragaman pertumbuhan yang disebabkan oleh faktor lingkungan dan genetik pada umur 1-3 tahun. Tegakan sengon tersebut dibangunsebagai uji keturunan dengan rancangan Baris Kolom Incomplete Block Design (IBD). Tegakan sengon tersebut menguji 25 famili half-sib dengan single plot. Hasil penelitian menunjukkan bahwa keragaman pertumbuhan yang disebabkanoleh faktor genetik (aditif ) maupun faktor lingkungan berubah-ubah setiap tahun. Pada tahun pertama ragam aditif mempunyai peranan 3,38% untuk tinggi pohon dan 0,67% untuk diameter batang; pada tahun kedua ragam aditif sebesar3,40% untuk tinggi pohon dan 3,05% untuk diameter batang; dan pada tahun ketiga ragam aditif sebesar 3,90% untuk tinggi pohon dan 7,00% untuk diameter batang. Sedangkan sisanya mulai tahun pertama sampai ketiga pertumbuhandipengaruhi oleh ragam lingkungan. Berdasarkan hasil penelitian disimpulkan bahwa pertumbuhan tanaman sengon ras lahan Jawa mayoritas dipengaruhi oleh faktor lingkungan, sehingga disarankan tanaman sengon ras lahan Jawa harusmenggunakan sitim silvikultur yang tepat yang dapat mempercepat pertumbuhan tanaman sengon.

2006 ◽  
Vol 55 (1-6) ◽  
pp. 70-77 ◽  
Author(s):  
Chang-Yi Xie ◽  
Y.-B. Fu ◽  
A. D. Yanchuk

Abstract A computer simulation was conducted to investigate the accuracy of ranking individual trees in field tests of different designs. A test population that consists of 900 trees from 45 full-sib families generated by three 6-parent disconnected half-diallels was considered. One incomplete block design with single-tree plots and four complete block designs with 1, 2, 4, and 10-tree row plots were examined. Various narrow-sense heritabilities, site variation patterns (patch sizes and gradient slopes), and two levels of dominant to additive genetic variance ratios (0 and 0.30) were evaluated. Results indicate that the accuracy of ranking depends more on the heritability of the trait and less on the magnitude of the dominant genetic variance, site variation patterns, and field designs. With patchy site variation, differences in ranking accuracy were observed for different designs, but became smaller with higher heritabilities. Impact of environmental gradient on the accuracy of individual ranking was negligible. Incomplete block design with single-tree plots (ICB1) provided the most accurate ranking when heritability was low while complete block design with 2-tree plots (RCB2) appeared to be the best when heritability was high. Large row plot designs were among the least effective in all the simulated scenarios. For traits with medium heritabilities, the statistical efficiencies of ICB1 and RCB with 1 and 2-tree plots are comparable.


2015 ◽  
pp. 113-130
Author(s):  
Premadhis Das ◽  
Ganesh Dutta ◽  
Nripes Kumar Mandal ◽  
Bikas Kumar Sinha

1979 ◽  
Vol 28 (4) ◽  
pp. 471-478 ◽  
Author(s):  
S. A. Vanstone

AbstractIt is well known that in any (v, b, r, k, λ) resolvable balanced incomplete block design that b≧ ν + r − l with equality if and only if the design is affine resolvable. In this paper, we show that a similar inequality holds for resolvable regular pairwise balanced designs ((ρ, λ)-designs) and we characterize those designs for which equality holds. From this characterization, we deduce certain results about block intersections in (ρ, λ)-designs.


2019 ◽  
Vol 15 (1) ◽  
pp. 155014771982624 ◽  
Author(s):  
Woosik Lee ◽  
Jong-Hoon Youn ◽  
Teukseob Song

During the initial deployment time, wireless sensors continually search their neighbors. The neighbor discovery is not an one-time event because the network topology can be changed anytime due to node mobility and failure. The neighbor discovery protocol helps sensor nodes to find neighboring sensors within their communication range. This study proposes a novel neighbor discovery protocol called the prime-number-assisted block-based neighbor discovery protocol, which intelligently changes the sensor schedules based on the greater common divisor of two sensors’ discovery cycle lengths. For example, for two sensors whose duty cycles are different, if the lengths of their discovery schedules are relatively prime, the prime-number-assisted block-based neighbor discovery protocol simply uses the balanced incomplete block design–based neighbor discovery protocol without adding any additional active slots; otherwise, it changes the original balanced incomplete block design–based schedule using a prime number. In this study, we compare the performances of prime-number-assisted block-based neighbor discovery protocol and other recently proposed neighbor discovery protocols (U-Connect, Disco, SearchLight, and Hedis) using a TOSSIM simulator. The experimental results confirm the superiority of prime-number-assisted block-based neighbor discovery protocol over other neighbor discovery protocols in terms of discovery latency and energy consumptions.


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