| Literature DB >> 27092146 |
Shun-Lin Zheng1, Liang-Jun Wang2, Nian-Xin Wan1, Lei Zhong1, Shao-Meng Zhou1, Wei He3, Ji-Chao Yuan1.
Abstract
The aim of this study was to explore the effects of different density treatments onEntities:
Keywords: artificial neural network model; growing season; plant density; potato; spatial distribution; tuber yield
Year: 2016 PMID: 27092146 PMCID: PMC4824783 DOI: 10.3389/fpls.2016.00365
Source DB: PubMed Journal: Front Plant Sci ISSN: 1664-462X Impact factor: 5.753
Soil conditions in the two experimental sites.
| Spring site | PS | 5.09 | 25.09 | 1.98 | 0.83 | 14.20 | 136.82 | 163.33 | 107.00 |
| Fall site | PS | 5.92 | 24.54 | 1.85 | 0.92 | 14.12 | 191.94 | 126.99 | 91.29 |
PS, paddy soil; Soil type in both seasons was consistent, and the experimental sites were previously planted with rice.
Meteorological factors at each growing stage of spring and fall potatoes.
| SS-MS | 139.0 | 1381.5 | 332.9 | 1025.03 | 17.3 | |
| Spring | SS-TBS | 7.9 | 513.0 | 149.9 | 411.45 | 15.5 |
| TBS-MS | 131.1 | 868.5 | 183.0 | 613.58 | 18.5 | |
| SS-MS | 209.3 | 1239.7 | 146.7 | 873.20 | 16.1 | |
| Fall | SS-TBS | 165.6 | 594.6 | 70.0 | 346.43 | 20.5 |
| TBS-MS | 43.7 | 645.1 | 76.7 | 526.77 | 13.4 |
Yield and yield components under different plant densities in the two growing seasons.
| Spring | 6 | 42.05c | 5.52e | 7.82a | 103.22a |
| 9 | 44.27b | 8.20d | 7.75ab | 73.87b | |
| 12 | 47.71a | 11.00c | 7.00b | 65.60c | |
| 15 | 48.05a | 13.94b | 5.87c | 62.18d | |
| 18 | 47.63a | 16.41a | 6.08c | 49.53e | |
| Average | 45.94 | 11.01 | 6.90 | 70.88 | |
| Fall | 6 | 21.29d | 5.84e | 5.67a | 62.77a |
| 9 | 22.52cd | 8.73d | 4.27b | 56.53ab | |
| 12 | 23.95bc | 11.18c | 4.40b | 50.36b | |
| 15 | 25.91b | 13.65b | 3.67b | 54.75b | |
| 18 | 28.17a | 15.42a | 3.87b | 51.26b | |
| Average | 24.37 | 10.97 | 4.38 | 55.13 | |
Data are presented as means of three replicates in each treatment. Different letters in each column represent significant differences at p < 0.05.
Contribution of yield components to yield.
| Spring | Effective plants | 0.8484** | −0.1791 | 14.15 |
| Tuber number per plant | −0.7567** | −0.3408 | 24.02 | |
| Single tuber weight | −0.8602** | −0.7717 | 61.83 | |
| Effective plants | 0.8946** | 1.4000 | 77.20 | |
| Fall | Tuber number per plant | −0.7091** | 0.2828 | 12.36 |
| Single tuber weight | −0.4511 | 0.3755 | 10.44 |
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Average longitudinal and transverse distance under different densities in the two growing seasons.
| 6 | 6.90c | 5.42d | 13.63a | 10.48a |
| 9 | 7.20b | 5.82c | 12.09b | 9.58b |
| 12 | 7.32b | 5.90b | 11.41c | 8.92c |
| 15 | 7.86a | 5.92b | 10.31d | 8.44cd |
| 18 | 8.05a | 6.05a | 10.60d | 7.93d |
| Average | 7.47 | 5.82 | 11.61 | 9.07 |
Data are presented as means of three replicates in each treatment. Different letters in each column represent significant differences at p < 0.05.
Figure 1Cumulative percentage of tuber number under different densities in the two growing seasons. Plant densities: D1, 6 × 104 strains hm−2; D2, 9 × 104 strains hm−2; D3, 12 × 104 strains hm−2; D4, 15 × 104 strains hm−2; and D5, 18 × 104 strains hm−2.
Cumulative percentage equation parameter values associated with potato tuber number and equations used to determine coefficients (.
| Spring | 6 | 128.04 | −4.32 | 7.67 | 0.9894** | 100.10 | −3.93 | 12.34 | 0.9975** |
| 9 | 121.23 | −4.67 | 7.69 | 0.9977** | 102.49 | −3.78 | 11.24 | 0.9987** | |
| 12 | 118.49 | −4.90 | 7.73 | 0.9972** | 124.03 | −3.62 | 12.53 | 0.9936** | |
| 15 | 102.72 | −6.41 | 7.75 | 0.9959** | 111.87 | −3.75 | 10.46 | 0.9928** | |
| 18 | 146.33 | −2.84 | 10.04 | 0.9960** | 106.27 | −4.22 | 10.34 | 0.9933** | |
| 6 | 106.26 | −5.23 | 5.39 | 0.9979** | 99.49 | −4.07 | 9.15 | 0.9920** | |
| Fall | 9 | 112.68 | −4.46 | 5.94 | 0.9961** | 102.10 | −3.88 | 8.62 | 0.9959** |
| 12 | 106.90 | −5.57 | 5.87 | 0.9980** | 106.92 | −3.89 | 8.59 | 0.9784** | |
| 15 | 109.59 | −4.71 | 5.83 | 0.9631** | 103.35 | −4.19 | 7.98 | 0.9796** | |
| 18 | 129.71 | −3.92 | 6.71 | 0.9943** | 114.10 | −2.94 | 7.84 | 0.9918** | |
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Potato tuber distribution distance of 50 and 90% at each plant density in the two growing seasons.
| Spring | 6 | 6.92 | 12.33 | 9.36 | 21.53 |
| 9 | 7.13 | 11.10 | 9.65 | 18.95 | |
| 12 | 7.25 | 11.24 | 9.78 | 16.39 | |
| 15 | 7.69 | 9.88 | 10.52 | 15.25 | |
| 18 | 7.97 | 10.05 | 11.84 | 15.51 | |
| 6 | 5.27 | 9.17 | 7.48 | 15.90 | |
| Fall | 9 | 5.65 | 8.53 | 8.09 | 14.46 |
| 12 | 5.74 | 8.31 | 7.93 | 13.20 | |
| 15 | 5.62 | 7.86 | 8.06 | 12.58 | |
| 18 | 5.96 | 7.20 | 8.27 | 12.27 | |
Artificial neural network model of the spatial distribution of potato tuber weight parameters during different growing seasons.
| Spring | 0.8911 | 0.8933 | 11.7885 | 12.3637 | 9.6917 | 10.6256 | 100 | 51 |
| Fall | 0.9135 | 0.8677 | 11.3406 | 12.9161 | 9.3813 | 11.0060 | 100 | 50 |
Figure 2Contour maps of potato tuber weight distribution model predictions under different plant densities. (A) Longitudinal distance (cm); (B) Transverse distance (cm).