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Record W2557172307 · doi:10.5376/ijh.2016.06.0022

Effects of variety and manuring on the growth, yield and nutritional quality of watermelon (<i>Citrullus lanatus</i> L.) in a rainforest zone of Nigeria

2016· article· en· W2557172307 on OpenAlexvenueno aff
Samuel Agele, Sajo Adeola, Aiyelari Peter

Bibliographic record

VenueInternational Journal of Horticulture · 2016
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicBanana Cultivation and Research
Canadian institutionsnot available
Fundersnot available
KeywordsCitrullus lanatusRandomized block designSowingWet seasonFertilizerBiologyRainforestCropAgronomyYield (engineering)HorticultureChicken manureCultivarManureBotanyEcology

Abstract

fetched live from OpenAlex

The effects of variety and manure application on the growth, yield and nutritional quality of watermelon ( Citrullus lanatus L.) were investigated during the rainy and late cropping seasons in Akure, a rainforest zone of Nigeria. Treatments were a factorial combination of five watermelon varieties and three manure types laid out in a randomized complete block design (RCBD) with three replications. The watermelon varieties were Crimson Sweet, Charleston Grey, Kaolac, Anderson and Sugarbaby, while the manures which were applied at 3 weeks after planting, were organomineral fertilizer (OMF) (5 t/ha), NPK (compound) fertilizer (200 kg/ha) and an unmanured control. The watermelon varieties tested responded differently in terms of growth and yield components due to differences in their genetic composition. In the rainy season, Charleston Grey performed well in terms of growth (biomass) but produced poor fruit yield while Kaolac and Anderson recorded high fruit yields. Late season favored growth and yield in Crimson Sweet and Kaolac, however, Kaolac produced good fruit yields as both rainy and late season crop. Fruit quality parameters such as the number of rotten and cracked fruits differed among the varieties, in both rainy and late season, Charleston Grey and Kaolac produced the highest number of rotten and cracked/split fruits. Sugarbaby and Anderson performed best in both seasons while Charleston Grey is not adequately adapted to rainy season growing environmental conditions. The NPK fertilizer enhanced higher growth and yield over OMF and unmanured control in both seasons. Significant interactions between variety and manuring were found for growth and fruit yield characters of watermelon. In the rainy season crop, application of NPK and organomineral fertilizer enhanced fruit yield components of watermelon varieties (Kaolac, Anderson, Crimson Sweet and Sugarbaby). In the late season, NPK fertilizer enhanced number of fruits per plant in Charleston Grey, highest mean fruit diameter and mean fruit weight per plant in Anderson.  The chemical and proximate constituents of fruits of watermelon varieties were significantly affected by manure application. In the rainy season, NPK enhanced fruit contents of N, P, K, moisture, total solids and vitamin C in most varieties except in Anderson. In late season, NPK enhanced the nutritional (total solids) contents of the varieties while OMF enhanced fruit contents of P, Ca, crude fiber, vitamin C and total solids in some of the varieties. However, unmanured Anderson had highest vitamin C content in the late season. It is concluded that application of NPK and OMF fertilizer enhance growth, yield and nutritional quality of watermelon varieties in both rainy and late season in the study area.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.866
Threshold uncertainty score0.096

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.016
GPT teacher head0.247
Teacher spread0.231 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2016
Admission routes1
Has abstractyes

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