配置方式对矮秆糯高粱光合特性及干物质生产影响
Journal of Shanxi Agricultural University(Natural Science Edition)(2020)
Abstract
[目的]探究适宜机械化栽培管理的矮秆糯高粱在单位面积内的合理配置方式,明确同一适宜密度下,不同田间配置方式对辽粘6号单株光合效率、单株干物质积累和群体产量的影响,为矮秆糯高粱生产提供技术参考.[方法]以适于机械化种植矮秆糯高粱辽粘6号为试材,研究在12万株?hm-2密度下二比空、一穴双株、交错种植和常规种植方式(CK)对其株高、柄伸长、叶面积指数、光合参数、籽粒产量和收获指数的影响.[结果]交错种植配置方式的单株干物质积累量最大,一穴双株的单株干物质积累量最小;交错种植的单株光合作用强于其它配置方式的单株,一穴双株配置方式下单株光合作用受抑制明显.交错种植方式的生物产量最大为24096.2 kg?hm-2,其籽粒产量最高为8915.6 kg?hm-2,收获指数也最大(0.37);其次是二比空配置方式,生物产量为23824.4 kg?hm-2,籽粒产量8915.6 kg?hm-2,收获指数为0.36;再次是常规种植方式(CK),一穴双株配置方式最低,生物产量为23638.8 kg?hm-2,籽粒产量8037.2 kg?hm-2,收获指数为0.36.从产量构成因素来看,密度相同情况下,交错种植的穗粒重、千粒重最高,其次是二比空,再次是常规种植方式,最低的是一穴双株配置方式.[结论]辽粘6号在种植密度为12万株?hm-2时,首选交错种植配置方式,其次选用二比空配置方式,这2种配置方式构建了比较合理的群体光合结构,它们比常规配置方式具有更高的光合效能利用率,产出了较高的籽粒产量,同时得出了较高的收获指数.
More求助PDF
上传PDF
View via Publisher
AI Read Science
AI Summary
AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.
Example
Background
Key content
Introduction
Methods
Results
Related work
Fund
Key content
- Pretraining has recently greatly promoted the development of natural language processing (NLP)
- We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
- We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
- The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
- Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance
Upload PDF to Generate Summary
Must-Reading Tree
Example

Generate MRT to find the research sequence of this paper
Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn
Chat Paper
Summary is being generated by the instructions you defined