Sustainable potato production : global case studies edited by Z. He , R. Larkin and W. Honeycuff
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
This book addresses many of the agronomic and environmental issues of sustainable potato production, but almost to the exclusion of economic and social sustainability. Organised in nine parts, the first admirably sets the global scene and the remainder focus geographically on Northeast United States, West United States, Eastern Canada, Tasmania (Australia), Northern China, Brazil and Peru, Italy, Egypt and the tropical highlands of Africa. While the work and references are very up-to-date, the whole book is not greater than the sum of the individual chapters. The lack of a concluding chapter leaves the reader seeking a synthesis on the degree of current un-sustainability in potato production and of the relative importance of the practices leading to sustainable production. The main content of the book is data and information dense, spanning comparisons between entire cropping systems to those of specific (e.g. humic substances) interventions, but not to the exclusion of integrated management of pests and diseases. Indeed, perhaps the most satisfying chapter is that on integrated pest management in Peru. A major justifiable focus is on the management of nitrogen (N), with the contributions of soil and plant nitrogen tests, modelling of nitrogen recommendations, green manure crops and nitrous oxide emissions to sustainable potato production all being highlighted. Despite variable quality of its chapters, this is a book that should deck the shelves (or hard drives) of potato scientists; all will find aspects of interest, reinforcing current concepts and at times providing new knowledge. At the price one might have expected a tighter final edit.
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 | 0.000 | 0.000 |
| 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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.014 | 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