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【科研快讯 - Plant and Soil 等】植物根系观测系统 等

发布时间:2013-06-08 【字体:       

【植物根系观测系统】Chantal Planchamp Dirk Balmer Andreas Hund Brigitte Mauch-Mani. A soil-free root observation system for the study of root-microorganism interactions in maize.Plant and Soil June 2013 Volume 367 Issue 1-2 pp 605-614

Abstract

Background and aims

The root surface of a plant usually exceeds the leaf area and is constantly exposed to a variety of soil-borne microorganisms. Root pathogens and pests as well as belowground interactions with beneficial microbes can significantly influence a plants' performance. Unfortunately the analysis of these interactions is often limited because of the arduous task of accessing roots growing in soil. Here we present a soil-free root observation system (SF-ROBS) designed to grow maize (Zea mays) plants and to study root interactions with either beneficial or pathogenic microbes.

Methods

The SF-ROBS consists of pouches lined with wet filter paper supplying nutrient solution.

Results

The aspect of maize grown in the SF-ROBS was similar to soil-grown maize; the plant growth was similar for the shoot but different for the roots (biomass and length increased in the SF-ROBS). SF-ROBS-grown roots were successfully inoculated with the hemi-biotrophic maize fungal pathogen Colletotrichum graminicola and the beneficial rhizobacteria Pseudomonas putida KT2440. Thus the SF-ROBS is a system suitable to study two major belowground phenomena namely root fungal defense reactions and interactions of roots with beneficial soil-borne bacteria.

Conclusions

This system contributes to a better understanding of belowground plant microbe interactions in maize and most likely also in other crops.


【估算灌溉和旱作农业生态系统下土壤呼吸作用】Ni Huang Zheng Niu. Estimating soil respiration using spectral vegetation indices and abiotic factors in irrigated and rainfed agroecosystems.Plant and Soil June 2013 Volume 367 Issue 1-2 pp 535-550
Abstract
Aims

Our aims were to identify the primary factors involved in soil respiration (Rs) variability and the role that spectral vegetation indices played in Rs estimation in irrigated and rainfed agroecosystems during the growing season.

Methods

We employed three v

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