长期少免耕对中国东北玉米农田土壤呼吸及碳氮变化的影响

在黑土区37年不同耕作模式定位试验田，采用原位法比较常规旋耕灭茬起垄（CT）、旋耕留高茬行间深松-少耕（RT）、免耕（NT）和深翻（PT）4种耕作模式土壤呼吸速率及其与土壤温度和湿度的关系，测定土壤总碳氮、无机氮，微生物碳氮的变化。结果表明，玉米生育期间土壤呼吸呈单峰变化，开花期达最大值，生长季平均呼吸速率依次为RT > NT > CT > PT。4个处理土壤温度与土壤呼吸速率间存在显著指数关系。不同耕作模式0~10 cm土壤温度可解释土壤呼吸速率变异的38.3%~67.9%，温度敏感性系数Q10范围为2.1~5.3；RT和NT处理显著提高0~20 cm土壤碳氮含量；RT处理在0~20 cm土壤中微生物碳含量均高于CT、NT和PT处理。RT处理土壤呼吸对温度响应提高，RT和NT处理显著增加上层土壤总碳氮含量，利于土壤质量提升。     

微生物素在果蔬采后保鲜中的应用进展

微生物素在果蔬采后保鲜中有重要的应用价值,但目前实际应用在果蔬采后保鲜领域中的并不多。本文分析了目前已经应用到果蔬保鲜领域的微生物素种类,有乳酸链球菌肽、溶菌酶、木霉发酵液等,分析了其抑菌保鲜原理及研究现状;并结合微生物素的特点,提出了微生物素在未来果蔬采后保鲜中的发展趋势,即面对冷藏技术使用不完善的现象,可以开发利用更多的微生物素种类,如纳他霉素、红曲霉素、短梗霉多糖等,为今后果蔬采后保鲜领域的健康可持续发展提供参考。     

黄河故道区域不同种植模式及秸秆还田方式对土壤的改良效果

由于长期受到流水冲击,黄河故道区域农田以中低产田为主,因此本区域农田质量提升成为黄河中下游平原绿色发展的重要研究课题。在河南濮阳清丰地区秸秆还田方式的基础上,选取黄河故道区域广泛种植的小麦、玉米和花生三大主要农作物,于2009年进行4种种植模式长期定位试验：小麦-玉米、小麦-花生、小麦-玉米-小麦-花生和单季花生,其中小麦和玉米秸秆全部还田,花生秸秆不还田,探究不同种植模式对土壤理化性质和微生物群落结构的影响。结果表明,秸秆还田量越多,土壤有机质含量提高越多,小麦-花生、小麦-玉米-小麦-花生种植模式下土壤有机质含量最高,且其土壤含水量也显著高于其他处理,上层土壤容重有所降低,显著改善了土壤砂质化,提升了土壤的蓄水能力;秸秆还田量较大的种植模式的养分保持能力明显提高,养分含量显著增加;微生物群落结构对不同种植模式响应结果为,花生可以显著提升微生物丰度,微生物群落多样性随种植作物类型的增加而增加。因此,小麦-玉米-小麦-花生种植模式较为适宜濮阳清丰黄河故道区域,有利于土壤改良和区域农业的可持续发展。     

Identification of culturable microbial functional groups isolated from the rhizosphere of four species of mangroves and their biotechnological potential

This study identified microbial functional groups like total culturable bacteria, potential N₂-fixing free living bacteria, N₂-fixing hydrocarbonoclastic bacteria, N-assimilating hydrocarbonoclastic bacteria, total fungi, actinobacteria, P-solubilizers, lipolytic microorganisms, and starch, cellulose, pectin and protein degrading microorganisms, isolated from the rhizosphere of four species of mangroves (Red, Black, White, and Button) from the natural protected area at the Terminos Lagoon, Campeche, México. Overall, microbial populations showed significant differences (P < 0.05) among the four mangrove species. The rhizosphere of White mangrove showed better chemical and textural soil properties, and harbored the highest microbial populations when compared to the remaining mangrove species. The principal component analysis indicated that two components accounted the 85.3% of the total variation. The most significant textural and chemical soil properties were the major components, CP1 (organic matter and total organic carbon) and CP2 (sand and clay). Microbial populations correlated (P < 0.05, Pearson coefficient) with sand and clay particles, and with some soil chemical properties such as organic matter. The total nitrogen and organic carbon significantly correlated with cellulose degraders, while phosphorus with N₂-fixing bacteria, total fungi, and with pectin and starch degraders.     

Artificial neural network modeling of microbial community structures in the Atlantic Forest of Brazil

Microbial communities vary across the landscape in forest soils, but prediction of their biomass and composition is a difficult challenge due to the large numbers of variables that influence their community structures. Here we examine the use of artificial neural network (ANN) models for extraction of patterns among soil chemical variables and microbial community structures in forest soils from three regions of the Atlantic Forest of Brazil. At each location, variations in soil chemical properties and FAME profiles of microbial community structures were mapped at 20 × 20 m intervals within 10 ha parcels. Geostatistical analyses showed that spatial variability in soil physical and chemical variables could be mapped at scale distances of 20 m, but that FAME profiles representing the microbial communities were highly variable and had no spatial dependence at the same scale in most cases. RDA analysis showed that FAME signatures representing different microbial groups were positively associated with soil pH, OM, P and base cations concentrations, whereas microbial biomass was negatively associated with the same environmental factors. In contrast, ANN models revealed clear relationships between microbial community structures at each parcel location, and generated verifiable predictions of variations in FAME profiles in relation to soil pH, texture, and the relative abundances of base cations. The results suggest that ANN modeling provides a useful approach for describing the relationships between microbial community structures and soil properties in tropical forest soils that were not able to be captured using geostatistical and RDA analyses.     

Indicators and trade-offs of ecosystem services in agricultural soils along a landscape heterogeneity gradient

Soil functions can be classified as supporting (nutrient cycling) and provisioning (crop production) ecosystem services (ES). These services consist of multiple and dynamic functions and are typically assessed using indicators, e.g. microbial biomass as an indicator of supporting services. Agricultural intensification negatively affects indicators of soil functions and is therefore considered to deplete soil ES. It has been suggested that incorporating leys into crop rotations can enhance soil ES. We examined this by comparing indicators of supporting soil services – organic carbon, nitrogen, water holding capacity and available phosphorous (carbon storage and nutrient retention); net nitrogen mineralisation rate and microbial biomass (nutrient cycling and retention) – in barley fields, leys and permanent pastures along a landscape heterogeneity gradient (100, 500 and 1000 m radii). In addition, barley yields (provisioning service) were analysed against these indicators to identify trade-offs among soil services. Levels of most indicators did not differ between barley and ley fields and were consistently lower than in permanent pastures. Leys supported greater microbial biomass than barley fields. Landscape heterogeneity had no effect on the indicators or microbial community composition. However, landscape heterogeneity correlated negatively with yield and soil pH, suggesting that soils in heterogeneous landscapes are less fertile and therefore have lower yields. No trade-offs were found between increasing barley yield and the soil indicators. The results suggest that soil ES are determined at the field level, with little influence from the surrounding landscape, and that greater crop yields do not necessarily come at the expense of supporting soil services.     

油茶皂苷的制备及提纯工艺研究

为研究油茶皂苷的制备及提纯工艺,为中试化生产提供科学的技术支撑,通过正交试验得到最佳工艺为乙醇体积分数75%,料液比1∶2,提取时间120 min,提取温度60℃,得到纯度为55.65%的油茶皂苷粗品,得率16.12%。油茶皂苷粗品配置成质量分数3%水溶液,加入10%体积的1%壳聚糖絮凝剂絮,经凝沉、淀除去杂质,澄清液经AB-8型大孔树脂吸附90 min,用质量分数2%氢氧化钠溶液洗脱杂质,再用体积分数70%乙醇溶液洗脱油茶皂苷,将洗脱液旋转蒸发,除去乙醇并烘干,即得到纯度85.36%的油茶皂苷。     

Effect of the particle size on the ammonia removal rate and the bacterial community composition of bioflocs

The total ammonia nitrogen (TAN) removal efficiency and bacterial community composition of bioflocs with <50-μm particle size, > 50-μm particle size and un-sieved bioflocs were investigated in the current study. The initial ratio of dissolved organic carbon to TAN (DOC/TAN) in the three groups were about 14:1. No significant difference was found in the removal rate of TAN, average concentrations of TAN and nitrite nitrogen among the three groups (P > 0.05). The C/N (w/w) ratio of the > 50-μm bioflocs was significantly higher than those of the other groups. No significant differences were found in the crude protein content in the bioflocs among the three groups. The development of the bacterial community compositions of the bioflocs was analyzed by Illumina MiSeq sequencing analyses. Most OTUs were shared among the three groups at all the sampled time points. With the increase in the relative abundance of phylum Firmicutes, that of phylum Proteobacteria, Chorolexi, and Bacteroidetes decreased in all the three groups. The phylum Firmicutes and genus Bacillus were predominant in all the sampled time points. At the end of the experiment, genus Bacillus accounted for 81% in the < 50-μm group, 82% in the > 50-μm group, and 75% in the un-sieved group.     

微生物技术在秸秆饲料中的应用

作物秸秆是农业生产系统中一项重要的生物资源,由于秸秆本身的难降解性和当前处理秸秆的技术水平有限,目前存在秸秆过剩问题。如何合理利用好秸秆资源是现代农业面临的难题。本文从农作物秸秆成分及其化学结构,降解秸秆的微生物种类,微生物降解秸秆的过程,利用微生物处理秸秆的方法,微生物发酵秸秆类饲料的应用效果,微生物发酵农作物秸秆生...     

微生物燃料电池在环境监测中的研究进展

微生物燃料电池在环境监测领域有巨大的应用潜力.概述微生物燃料电池应用于环境监测的基本原理,对目前已有的微生物燃料电池型传感器为监测方法进行详细的介绍,包括微生物燃料电池用于易降解碳源、有毒污染物及微生物数量检测三方面的研究.最后探讨了微生物燃料电池传感器目前还未被广泛应用于实际水质监测的原因,以期为未来研究开发高性能微生物燃料电池传感器提供理论参考依据.