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Record W2414661815 · doi:10.21273/hortsci.42.3.503

Yield and Russeting of Greenhouse Tomato as Influenced by Leaf-to-fruit Ratio and Relative Humidity

2007· article· en· W2414661815 on OpenAlex
Dominique‐André Demers, Martine Dorais, Athanasios P. Papadopoulos

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueHortScience · 2007
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicGreenhouse Technology and Climate Control
Canadian institutionsResearch CanadaAgriculture and Agri-Food Canada
FundersAgriculture and Agri-Food Canada
KeywordsBiologyGreenhouseHorticultureYield (engineering)Relative humidityPruningCultivarAgronomyAscorbic acidLycopersiconFructification

Abstract

fetched live from OpenAlex

Three experiments were conducted in greenhouses 1) to determine the optimal leaf-to-fruit ratio for minimizing the incidence of russeting (miniature cuticle cracks on fruit) while optimizing fruit yield of greenhouse tomato ( Lycopersicon esculentum Mill.) and 2) to investigate the effect of day/night relative humidity (RH) regimens on the development of russeting. Leaf-to-fruit ratio treatments (0.5–2.0) were achieved by varying the number of fruit (two to six fruit) per cluster and the number of leaves (two to four leaves) between clusters. In one experiment, plants were also subjected to either high day/low night or low day/high night RH regimens (low RH, 60% to 70%; high RH, 85% to 95%). Results showed that russeting of greenhouse tomato was mostly influenced by the number of fruit per cluster (total fruit load), and very little by the number of leaves between clusters. In general, decreasing the number of fruit per cluster resulted in a progressive increase in the occurrence of russeting. Furthermore, as the number of fruit per cluster decreased, the percentage of fruit with no russeting and with little russeting decreased whereas the percentage of fruit with the more severe russeting increased (except for the summer). For beefsteak cultivars Trust and Rapsodie grown under southwestern Ontario conditions, the best pruning practices for minimizing russeting and optimizing yield was to prune clusters to three fruit in early spring and late fall, to four fruit during spring and fall, and to five fruit during the summer, with three leaves between clusters all year long. In the current study, no significant effect of day/night RH regimens on fruit russeting was observed. Of the cultivars used, Rz 74/56 was less sensitive to russeting than ‘Trust’, whereas ‘Rapsodie’ was not different from the two other cultivars. However, all three cultivars had a very high incidence of russeting (>65% of fruit affected), and none should be regarded as russeting resistant. Breeding programs and genetic investigations with the objective of developing greenhouse tomato cultivars resistant to russeting are needed.

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.

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)0.001
metaresearch head score (Gemma)0.000
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 score0.724
Threshold uncertainty score0.206

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.014
GPT teacher head0.233
Teacher spread0.219 · 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