Evidence map›Paper›PMID 38867991›Full record

ArticleHeliyon2024

Organic amendment composition and sowing depth in coffee Arabica: Effects on seedling growth biometrics.

Dargie Tsegay Berhe

Abstract read
In one paragraph

Article in Heliyon, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author.

Dargie Tsegay BerheDilla University, College of Agriculture and Natural Resources, Dilla, Ethiopia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

There is a significant production of coffee in the Gedeo zone, southern Ethiopia, which has could generate a huge amount of coffee husk wastes that have polluted the environment. However, organically enriching the soil is an effective method to enhance the development and productivity of coffee. Thus, this study aims to understand the effects of the interaction between sowing depth and organic amending practices. Three sowing depths and sixteen different organic amendment compositions were tested in a complete randomized design with three replications. Coffee seedling growth biometrics was measured, and R-program was used to calculate the statistical difference at a 5 % significance level. The organic amendment composition with 3:2:1 (topsoil: forest soil: sand) sown at a depth of 2 cm had statistically higher values of seedling stem height, leaf length, and taproot length by 82.82 %, 93.35 %, and 85.41 % than in the topsoil at a depth of 3 cm. Likewise, the main effect of organic amendment with 3:2:1 (topsoil: forest soil: sand) in internode length, number of nodes per seedling stem, number of true leaves per seedling, and leaf width were also higher by 70.42 %, 63.16 %, 92.23 % and 91.80 % than seedlings grown in topsoil solely. Interestingly, the days of 50 % emergence in 3:2:1 (ratio of topsoil: forest soil: sand) organic amendment composition were earlier by 62.11 days than using topsoil. This could be because of the accessibility of a significant quantity of organic carbon, primary macronutrients, alkaline nature of the growth media in addition to having low bulk and particle densities in the forest soil that could increase coffee seedling growth biometrics by improving soil porosity, aeration and nutrient uptake capacity, producing important soil microbes and neutralizing organic acids in comparison with the topsoil.

Indexed as

Coffee seedlingEnvironmentOrganic amendmentSoil fertilitySowing depth

Identifiers

PMID38867991
PMCPMC11168387

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.