Pea-oats intercropping: Agronomy and the benefits of including oats as a companion crop
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.
Bibliographic record
Abstract
Intercropping field pea ( Pisum sativum L.) and oat ( Avena sativa L.) can offer some benefits over monocropping to conventional grain and forage producers. Most studies have been conducted in organic systems with little information for conventional producers prompting a 2-year field study conducted at three Saskatchewan, Canada sites (SERF, IHARF, WCA). This study aimed to assess pea-oat intercropping with oats sown at different seeding rates under conventional systems. Also, it investigates the profitability of pea-oat intercropping. Treatments included monoculture pea (with and without weed control) and oats seeded at recommended rates; pea-oat intercrop with oats seeded at five seeding rates thus: Pea-oat (PO) intercrop with oats seeding rates targeted at 25 plant m −2 (PO 25 ), 50 plants m −2 (PO 50 ), 75 plants m −2 (PO 75 ), 100 plants m −2 (PO 100 ), and 125 plants m −2 (PO 125 ). In pea-oat intercropping, increased oat seeding rates reduced pea plant height, pea dry matter and total dry matter compared with monoculture. The highest Pea-oat seeding rate (PO 125) decreased weeds by ∼ 50 % compared to pea monocrop at one site-year. Pea-oat intercropping, especially at high oat seeding rates reduced lodging. Oat grain yield showed a quadratic relationship with increasing seeding rate (r = 0.69; P < 0.020), and maximum oat grain yield was predicted at 163.7 plants m −2 . The Partial land equivalent ratios (PLER) for peas for grains and biomass was > 0.5 mostly at lower densities (PO 25 and PO 50 ) while for oat it was > 0.5 at higher densities (PO 75 , PO 100 and PO 125 ). Land equivalent ratio (LER) differed with site-year with only 2 out of 5 site-years having LER > 1. Net revenue generated for grain yields were higher in Pm while intercropping reduced net revenue gains. Forage revenue did not differ between pea-oat intercropping seeding rates and was comparable to monocrops. Our findings suggest that pea-oat intercrop significantly reduced grain yields of peas and oats. Furthermore, with oat as a companion crop, intercropping can potentially be beneficial for weed control and lodging especially when oat is sown at higher seeding rates. This study provides an approach in which pea-oat intercropping could be a potential option for increased profitability in forage production systems. • Pea-oat intercropping reduced pea and oat grain yields across various sites in conventional systems. • Increasing oat seeding rates increased total dry matter in pea-oat intercropping systems. • Increasing oat seeding rates consistently reduced lodging and the presence of weed did not impact lodging. • Land equivalent ratio for grains was only influenced by site-year and not seeding rates. • Net revenue gains for grain yields were higher in monocrops than intercropping 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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it