Abstract: The current design for maize regional trials on the number of rows in plot and plants of yield estimate mostly depends on experiences instead of sufficient, and it was short of statistical foundation. Sampling method for grain yield based on common regional trials was studied in the known population of 7 200 plants in an area of 1 209.60 m2 with summer maize cultivar Jingyu 11 in Changping District, Beijing through the “Sampling Software” designed by Jin and Li, and number of sampling rows (lines) and sample size were approached as key points. Sampling with four sorts of sample sizes of 60, 120, 180, and 240 by random piece sample of 1–6 rows and 10 rows, according to the comparative analysis of variance of sample means, sampling method of 3–6 rows was better than that of 1–2 rows and 10 rows. Frequency distribution of the means of 500 samples showed that for dif-ferent sample sizes, the sampling should choose a different number of rows, and for the sample size of 60, 120, 240, and 420, 3, 4, 5, and 6 rows were the better sampling number of rows respectively. Considering precision and labor load, sampling 4–6 rows was better than sampling 3 rows. In labor-saving strategy with lower precision, sample size of 120 was suggested for sampling 4–6 rows; while in higher precision strategy, sample size of 420 was better for sampling 4 and 6 rows, and that of 480 for sampling 5 rows. Sampling methods with different number of rows and sample sizes were significantly different in frequency distribution of the sample means and the variance of sample means, and the better sampling methods could be distinguished from the others. Comprehensive analyses of the above results indicate that the best methods are sampling 6 rows with 420 plants for high precise trials, and 4 rows with 120 plants for common trials lower in precision.

Key words: Maize, Sampling method, Regional trial, Grain yield