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Record W4366300701 · doi:10.1016/j.agwat.2023.108318

Effects of ridge-furrow with plastic film mulching combining with various urea types on water productivity and yield of potato in a dryland farming system

2023· article· en· W4366300701 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.

Bibliographic record

VenueAgricultural Water Management · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicIrrigation Practices and Water Management
Canadian institutionsUniversity of OttawaAgriculture and Agri-Food Canada
Fundersnot available
KeywordsMulchAgronomyUreaNitrogenPlastic filmWater-use efficiencyYield (engineering)ProductivitySoil waterEnvironmental scienceChemistryMaterials scienceBiologySoil scienceIrrigation

Abstract

fetched live from OpenAlex

Ridge-furrow with plastic film mulching (RM) has the potential to enhance crop yields and water productivity, particularly in semi-arid regions. However, the combined effects of RM and various urea types on rainfed potato (Solanum tuberosum L.) production remain unclear. A three-year field experiment (2018–2020) was conducted to elucidate the effects of the RM combined with various urea types on water productivity, tuber yield, and economic benefits in a dryland farming system. Treatments consisted of two mulching patterns [RM and no plastic film mulching (NM)], combined with the application of three urea types [common urea (U), controlled-release urea (C), and mixed C and U at a ratio of 1:1 (CU)]. Our results indicated that compared to NM, the RM system reduced soil evaporative losses, which ultimately increased average soil water storage for the 0–60 cm soil layer by 6.7% (P < 0.05). In addition, RM increased the mean soil temperature for the 0–10 cm soil layer by 1.4 °C compared with NM. These changes in soil under RM helped increase plant height, leaf chlorophyll, and nitrogen balance index, but reduced leaf flavonoid, thereby improving tuber yield. The application of CU further improved plant height, leaf chlorophyll, and nitrogen balance index, which allowed the exploitation of more soil water to increase tuber yield and water productivity (P < 0.05). The interactions of mulching and urea type had significant influence on the tuber yield, water productivity, and partial factor productivity of nitrogen, especially with the RMCU. RMCU significantly (P < 0.05) increased potato yield (up to 23.5%), water productivity (23.7%), partial factor productivity of nitrogen (23.5%), and economic benefit (38.4%), compared to the NMU during both drought and non-drought growing seasons. We conclude that compared with other treatments, RMCU resulted in the highest tuber yield, water productivity, and economic benefit across three growing seasons and should be considered an effective strategy to foster sustainable potato production in dryland farming systems.

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)0.000
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 score0.644
Threshold uncertainty score0.198

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.007
GPT teacher head0.176
Teacher spread0.169 · 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