Evidence map›Paper›PMID 35050044›Full record

ArticlePlants (Basel, Switzerland)2022

A Crop Modelling Strategy to Improve Cacao Quality and Productivity.

Angela Patricia Romero Vergel, Anyela Valentina Camargo Rodriguez, Oscar Dario Ramirez, Paula Andrea Arenas Velilla, Adriana Maria Gallego

Open access · goldAbstract read
In one paragraph

Article in Plants (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
4.7field-weighted citation impact, top 7% of its field
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

1 citing paper in PubMed, 17 citations in OpenAlex.

  1. Article
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

5 authors at 2 institutions in 2 countries.

Angela Patricia Romero VergelThe John Bingham Laboratory, The National Institute of Agricultural Botany NIAB, 93 Lawrence Weaver Road, Cambridge CB3 0LE, UK.
Anyela Valentina Camargo RodriguezThe John Bingham Laboratory, The National Institute of Agricultural Botany NIAB, 93 Lawrence Weaver Road, Cambridge CB3 0LE, UK.ORCID 0000-0003-4277-0356
Oscar Dario RamirezFederación Nacional de Cafeteros FEDECACAO, Calle 31 No. 17-27, Bogota 999076, Colombia.
Paula Andrea Arenas VelillaFederación Nacional de Cafeteros FEDECACAO, Calle 31 No. 17-27, Bogota 999076, Colombia.
Adriana Maria GallegoGrupo BIOS, Centro de Bioinformática y Biología Computacional de Colombia-BIOS, Manizales 170001, Colombia.
Federación Nacional de Cultivadores de Palma de Aceite · CONational Institute of Agricultural Botany · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cacao production systems in Colombia are of high importance due to their direct impact in the social and economic development of smallholder farmers. Although Colombian cacao has the potential to be in the high value markets for fine flavour, the lack of expert support as well as the use of traditional, and often times sub-optimal technologies makes cacao production negligible. Traditionally, cacao harvest takes place at exactly the same time regardless of the geographic and climatic region where it is grown, the problem with this strategy is that cacao beans are often unripe or over matured and a combination of both will negatively affect the quality of the final cacao product. Since cacao fruit development can be considered as the result of a number of physiological and morphological processes that can be described by mathematical relationships even under uncontrolled environments. Environmental parameters that have more association with pod maturation speed should be taken into account to decide the appropriate time to harvest. In this context, crop models are useful tools to simulate and predict crop development over time and under multiple environmental conditions. Since harvesting at the right time can yield high quality cacao, we parameterised a crop model to predict the best time for harvest cacao fruits in Colombia. The cacao model uses weather variables such as temperature and solar radiation to simulate the growth rate of cocoa fruits from flowering to maturity. The model uses thermal time as an indicator of optimal maturity. This model can be used as a practical tool that supports cacao farmers in the production of high quality cacao which is usually paid at a higher price. When comparing simulated and observed data, our results showed an RRMSE of 7.2% for the yield prediction, while the simulated harvest date varied between +/-2 to 20 days depending on the temperature variations of the year between regions. This crop model contributed to understanding and predicting the phenology of cacao fruits for two key cultivars ICS95 y CCN51.

Indexed as

biomassflowering date (FD)harvest predictionlight interceptionthermal time

Identifiers

PMID35050044
PMCPMC8778100
OpenAlexW4206692315

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.