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Record W2094838911 · doi:10.1093/aob/mct114

Genetics, genomics and breeding of oilseed brassicas

2013· article· en· W2094838911 on OpenAlexaboutno aff
J. S. Heslop‐Harrison

Bibliographic record

VenueAnnals of Botany · 2013
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Disease Resistance and Genetics
Canadian institutionsnot available
Fundersnot available
KeywordsBiologyGenomicsGeneticsEvolutionary biologyComputational biologyBiotechnologyGenomeGene

Abstract

fetched live from OpenAlex

This is the 14th volume in the series on ‘Genetics, Genomics and Breeding of Crop Plants’, each book covering one or a group of species, so far including many major crops but not the cereals. The three areas discussed in the volumes are some of the most rapidly changing areas of biology today. For each crop, genetics and genomics sees tens if not hundreds of relevant publications every year, while breeding aims and approaches change rapidly. These challenges give both the strengths and weaknesses to this volume. A synthesis of the state-of-the art with respect to oilseed brassicas is certainly needed – but it was substantially out-of-date even before publication. The brassica volume consists of 16 chapters by well-known researchers, ranging from a description of the Brassica genus, through genetic maps, markers and comparative genomics, to mutagenesis and metabolomics. Three chapters discuss breeding objectives. Overall, there is much of interest in the volume. The forward-looking statements in many chapters, and three complete chapters largely about prospects, make some important and thoughtful points. There are also a number of gaps in coverage, where I would have hoped a volume like this would be my first source of reference. For breeding, I was disappointed not to see a strong chapter on hybrid breeding, since within the last decade hybrid Brassica napus has moved from a few percent of the market to representing more than 50 %, in Canada and the UK at least. This change is alluded to in a couple of chapters, but there is no detailed consideration of what this means for the future of the crop and selection approaches. It is important for books, at least for me, to have some degree of timeless information, which I can refer back to at almost any point in the future. There are some highspots here such as a nine-page table of the 58(!) Brassica linkage maps published since 2006, a list of the 15 large-insert BAC libraries available, and three pages of insect pests. But, with a coverage of genetics and breeding, I would have also liked to see more such tables, for example with oil contents and oil compositions of the different brassicas, more information about morphological variation such as seed characters, and data about germplasm collections and what is represented in them (although taxonomy is discussed in some chapters). Somewhat surprisingly, for a book published in September 2011, the genome sequencing initiatives chapter states, ‘We expect the A, C and B genome sequences to become publicaly available of the next few years’: the A genome B. rapa sequence was published online in August 2011, with the chapter authors both being co-authors of the journal paper (Wang et al., 2011). Surely this was in time, and significant enough, to be discussed, but it gives the book immediate obselesence, with no references in this chapter later than the three general papers referrred to from 2009 (before the impact of next-generation sequencing was felt, mentioned as a prospect in other chapters). The chapter itself is largely historical, describing the history of brassica whole-genome sequencing and genetics (noting, for example, that, ‘Genome sequence information will also revolutionise genetic and physical mapping’, without elaborating on what this means and has revealed in Brassica). Is geographical spread of authorship relevant? I think so in a book on genetics and breeding of major crops where location is so important: but we have no perspective of breeding from Asia, with only one chapter on mutagenesis and mutation breeding from China, and no authors from India, or Korea where molecular and other breeding programmes are addressing major challenges. Unfortunately less surprisingly, Africa also receives little mention, despite the huge need there for plant oils, and the use of Abyssynian mustard (the BC genome tetraploid B. carinata). The book will undoubtedly be useful to many specialists in Brassica. However, the very weak index, rather superficial and generalized statements about prospects rather than the details for many techniques, and a few points where one feels the book is long out of date (although in fact only by one or two years), mean its appeal is somewhat limited.

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.

How this classification was reachedexpand

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 score0.856
Threshold uncertainty score0.112

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 head0.041
GPT teacher head0.243
Teacher spread0.202 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations7
Published2013
Admission routes1
Has abstractyes

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