Enhancing Yields in Organic Crop Production by Eco-Functional Intensification
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
<p>Organic agriculture faces challenges to enhance food production per unit area and simultaneously reduce the environmental and climate impacts, e.g. nitrate leaching per unit area and greenhouse gas (GHG) emissions per unit mass produced. Eco-functional intensification is suggested as a means to reach these objectives. Eco-functional intensification involves activating more knowledge and refocusing the importance of ecosystem services in agriculture. Organic farmers manage agrobiodiversity by crop rotation (diversification in time). However, sole cropping (SC) of genetically identical plants in organic agriculture may limit resource use efficiency and yield per unit area. Intercropping (IC) of annual grain species, cultivar mixes, perennial grains, or forage species and forestry and annual crops (agroforestry) are examples of spatial crop diversification. Intercropping is based on eco-functional intensification and may enhance production by complementarity in resource use in time and space. Intercropping is based on the ecological principles of competition, facilitation and complementarity, which often increases the efficiency in acquisition and use of resources such as light, water and nutrients compared to sole crops, especially in low-input systems. Here we show that IC of cereals and grain legumes in European arable organic farming systems is an efficient tool for enhancing total grain yields compared to their respective sole crops. Simultaneously, we display how intercropping of cereals and legumes can be used as an efficient tool for weed management and to enhance product quality (i.e. cereal grain protein concentration). We discuss how intercropping contributes to efficient use of soil N sources and minimizes losses of N by nitrate leaching via <em>Ecological Precision Farming</em>. It is concluded that intercropping has a strong potential to increase yield and hereby reduce global climate impacts such as GHG kg<sup>-1</sup> grain. Finally, we discuss likely barriers and lock-in effects for increased use of intercropping in organic farming and suggest a roadmap for innovation and implementation of IC strategies in organic agriculture.</p>
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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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