MétaCan
Menu
Back to cohort
Record W2113426111 · doi:10.21273/hortsci.47.3.414

Effects of Drip Irrigation Configuration and Rate on Yield and Fruit Quality of Young Highbush Blueberry Plants

2012· article· en· W2113426111 on OpenAlex

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.

Bibliographic record

VenueHortScience · 2012
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicBerry genetics and cultivation research
Canadian institutionsAgriculture and Agri-Food Canada
FundersAgriculture and Agri-Food Canada
KeywordsDrip irrigationIrrigationSowingLoamAgronomyWater potentialYield (engineering)Water contentEnvironmental scienceSoil waterHorticultureBiologySoil science

Abstract

fetched live from OpenAlex

A 4-year study was conducted to establish the effects of drip irrigation configuration and rate on fruit yield and quality of young highbush blueberry plants ( Vaccinium corymbosum L. ‘Duke’). Plants were grown in a silt loam soil on raised beds and were non-irrigated or irrigated using either one or two lines of suspended drip tape. Each line configuration had in-line emitters spaced every 0.3 or 0.45 m for a total of four drip configurations. Water was applied by each drip configuration at two rates, a moderate rate of 5 L/plant per irrigation event, and a heavy rate of 10 L/plant. The frequency of irrigation was guided by measurements of soil matric potential. Irrigation was applied each year, and plants were cropped beginning the second year after planting. Rainfall was above normal in the first 2 years of the study, and differences in soil moisture were most evident in the last 2 years, in which soil matric potential increased with irrigation volume. Neither the number of irrigation lines nor emitter spacing had an effect on yield or fruit quality. Yield was unaffected by irrigation rate until the fourth year after planting and was only higher when 5 L/plant was applied. The yield increase was the result of differences in fruit weight during the second of two harvests and was associated with delays in fruit maturation. Irrigation affected plant mineral concentrations but leaves and berries responded differently; affected minerals tended to decrease in leaves but increase in the fruit. Many irrigation-induced changes in fruit quality were evident 1 or 2 years before changes in yield. Higher irrigation volume increased fruit size and water content but reduced fruit firmness and soluble solids. Irrigation reduced fruit water loss during storage and thereby promoted longer shelf life. Irrigation also resulted in a change in anthocyanin composition in the fruit but did not affect antioxidants or total anthocyanin content.

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 score0.086

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 head0.051
GPT teacher head0.283
Teacher spread0.232 · 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