Use of Sister‐Lines and the Performance of Modified Single‐Cross Maize Hybrids
Bibliographic record
Abstract
In hybrid maize (Zea mays L.) seed production, yield of the female parent is a major factor affecting production costs. As an alternative to using an inbred line as the female parent, sister‐lines (SLs), the F1 between two highly related inbred lines (A×A*), have been used in seed corn production. Hybrids produced using SLs are referred to as modified single‐cross (MSC) hybrids. This study examined (i) yield changes associated with MSC hybrids compared with their respective single‐cross (SC) hybrid counterparts and (ii) differences in grain yield of inbred lines and SLs. Three families of six inbred lines each were used to produce three diallel groups of 15 SLs. Simple sequence repeat (SSR) primer pairs were used to establish the degree of relatedness between inbred lines. The SLs and the inbred lines were mated to four unrelated inbred lines to form MSC and SC hybrids. The SC and MSC hybrids were evaluated for grain yield, grain moisture, test weight, and broken stalks in six environments. The six inbred lines and 15 SLs from each family were grown in five environments and evaluated for grain yield, grain moisture, test weight, and broken stalks. Most of the MSC hybrids (72–83%, depending on inbred line family) were not significantly different than the “best” SC counterpart. However, a low frequency of the MSC hybrids, 11 out of 180 (6.1%), had grain yields that were significantly lower than both SC hybrid counterparts. And surprisingly, three out of 180 (1.7%) of the MSC hybrids had grain yields that were significantly greater than both SC hybrid counterparts. The SLs used in this study exhibited an average grain yield that was two‐fold greater and more stable or predictable than the inbred lines. These results suggest that there are definite advantages in utilizing SLs in hybrid seed production and that, in general, the performance of the resulting MSC hybrids is expected to be similar to the “best” SC hybrid counterpart.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".