Long-term application of nitrogen and phosphorus fertilizers changes the process of community construction by affecting keystone species of crop rhizosphere microorganisms.

Keystone species of microbial communities play a very important role in community structure and ecosystem function; however, the effect of long-term nitrogen (N) and phosphorus (P) fertilizers on key taxa and the mechanisms of community construction of rhizosphere microbial communities remain unclear. In this study, the effect of nine fertilization treatments (N0P0, N0P1, N0P2, N1P0, N1P1, N1P2, N2P0, N2P1, and N2P2) on soil microbial community diversity, keystone species, and construction methods in the crop rhizosphere were studied in a loess hilly area after 26 years of fertilization. The results showed that fertilization significantly increased the nutrient contents of the rhizospheric soil and root system and significantly affected microbial community composition (based on the Bray-Curtis distance) and community construction process (ß-nearest taxon index: ßNTI). The decrease in the abundance of oligotrophic bacteria (from phyla Acidobacteriota and Chloroflexi) in the keystone species of bacterial communities shifted the community construction process from homogenizing dispersal to variable selection process and was significantly regulated by soil factors (total P and carbon-N ratio). However, the decrease in the abundance of keystone species (from phylum Basidiomycota) in the fungal communities did not have a significant effect on community construction, which was mainly affected by root characteristics (root N content and soluble sugar). This study found that long-term N and P fertilization changed the keystone species composition of bacterial communities by affecting the nutrient content of the rhizospheric soil, such as total P, so that the construction mode of communities changed from a stochastic to a deterministic process, and the N2 fertilization, especially the N1P2 treatment was better for increasing network stability (modularity and clustering coefficient).

Genetic diversity of Venturia inaequalis isolates (Apple scab) in China and U.K. determined by SSR markers.

Apple scab caused by Venturia inaequalis is a serious disease of cultivated apple worldwide. In this study, we collected 132 V. inaequalis isolates from Shaanxi, Gansu, Xinjiang, and the U.K. and analyzed their genetic diversity by using 13 microsatellite markers. Cluster analysis based on population structure and genetic distances suggested high similarity among the four regions. Population differentiation values ranged from 0.044 to 0.155, indicating there is a high level of kinship among the four regions. All isolates could be divided into 5 lineages with a 0.76 similarity coefficient. Among the four regions, Shaanxi had only one lineage, Group II; Gansu had four lineages, Group I, Group II, Group IV, and Group V; Xinjiang had all five lineages, Group I, Group II, Group III, Group IV, and Group V; and the U.K. had three lineages, Group I, Group II and Group IV. High molecular variance was detected for populations in the four regions, with 91% of the variance occurring within the populations and 9% among the populations. Structure analysis there are three common ancestors of these four regions. The results of the present study shed light on the genetic diversity of V. inaequalis in Shaanxi, Gansu and Xinjiang, which will lead to the development of more effective management strategies and new resistant apple cultivars through molecular marker-assisted selection.

Changes in the Microbiome in the Soil of an American Ginseng Continuous Plantation.

American ginseng is an important herbal medicinal crop in China. In recent years, there has been an increasing market demand for ginseng, but the production area has been shrinking due to problems associated with continuous monocropping. We analyzed the microbiome in bulk soils to assess whether and, if so, what changes in the bulk soil microbiome are associated with continuous American ginseng cropping. The alpha diversity of fungi and bacteria was significantly lower in the soils planted with American ginseng than the virgin (non-planted) land. The relative abundance of Fusarium spp. and Ilyonectria spp., known plant root pathogens, was much higher in the soils cropped with American ginseng than the non-planted. On the other hand, a number of bacteria with biodegradation function, such as Methylibium spp., Sphingomonas spp., Variovorax spp., and Rubrivivax spp., had lower abundance in the soils cropped with American ginseng than the non-cropped. In addition, soil pH was lower in the field planted with American ginseng than the non-planted. Accumulation of fungal root pathogens and reduction of soil pH may, therefore, have contributed to the problems associated with continuous monocropping of American ginseng.

Maze learning by a hybrid brain-computer system.

The combination of biological and artificial intelligence is particularly driven by two major strands of research: one involves the control of mechanical, usually prosthetic, devices by conscious biological subjects, whereas the other involves the control of animal behaviour by stimulating nervous systems electrically or optically. However, to our knowledge, no study has demonstrated that spatial learning in a computer-based system can affect the learning and decision making behaviour of the biological component, namely a rat, when these two types of intelligence are wired together to form a new intelligent entity. Here, we show how rule operations conducted by computing components contribute to a novel hybrid brain-computer system, i.e., ratbots, exhibit superior learning abilities in a maze learning task, even when their vision and whisker sensation were blocked. We anticipate that our study will encourage other researchers to investigate combinations of various rule operations and other artificial intelligence algorithms with the learning and memory processes of organic brains to develop more powerful cyborg intelligence systems. Our results potentially have profound implications for a variety of applications in intelligent systems and neural rehabilitation.

Ratbot automatic navigation by electrical reward stimulation based on distance measurement in unknown environments.

Traditional automatic navigation methods for bio-robots are constrained to configured environments and thus can't be applied to tasks in unknown environments. With no consideration of bio-robot's own innate living ability and treating bio-robots in the same way as mechanical robots, those methods neglect the intelligence behavior of animals. This paper proposes a novel ratbot automatic navigation method in unknown environments using only reward stimulation and distance measurement. By utilizing rat's habit of thigmotaxis and its reward-seeking behavior, this method is able to incorporate rat's intrinsic intelligence of obstacle avoidance and path searching into navigation. Experiment results show that this method works robustly and can successfully navigate the ratbot to a target in the unknown environment. This work might put a solid base for application of ratbots and also has significant implication of automatic navigation for other bio-robots as well.

Bio-robots automatic navigation with graded electric reward stimulation based on Reinforcement Learning.

Bio-robots based on brain computer interface (BCI) suffer from the lack of considering the characteristic of the animals in navigation. This paper proposed a new method for bio-robots' automatic navigation combining the reward generating algorithm base on Reinforcement Learning (RL) with the learning intelligence of animals together. Given the graded electrical reward, the animal e.g. the rat, intends to seek the maximum reward while exploring an unknown environment. Since the rat has excellent spatial recognition, the rat-robot and the RL algorithm can convergent to an optimal route by co-learning. This work has significant inspiration for the practical development of bio-robots' navigation with hybrid intelligence.

Within- and between-orchard variability in the sensitivity of Venturia inaequalis to myclobutanil, a DMI fungicide, in the UK.

BACKGROUND: Myclobutanil, a demethylation inhibitor (DMI) fungicide, is an important fungicide for controlling apple scab and powdery mildew. Overuse of this fungicide has led to establishment of scab isolates with reduced sensitivity to this fungicide in several countries. Experiments were conducted to determine the sensitivity of the causal agent of apple scab, Venturia inaequalis (Cooke) Winter, to myclobutanil in the UK, in order to assess whether there is a relationship between fungal insensitivity and the number of DMI applications, and establishing whether fungal sensitivity varied greatly within an orchard. RESULTS: Reduced sensitivity of V. inaequalis to myclobutanil was positively related linearly to the number of DMI applications. ED(50) values ranged from 0.028 to 1.017 mg L(-1) (average = 0.292) for the baseline population, whereas isolates from two other orchards had much greater ED(50) values, ranging from 0.085 to 5.213 mg L(-1) (average = 1.852). There was significant variation in fungal sensitivity to myclobutanil among fungal isolates from different locations within a single orchard. CONCLUSIONS: Spatial spread of insensitive isolates of V. inaequalis to myclobutanil is likely to be limited in distance. Conidia may be an important source of primary inoculum. Myclobutanil should still be effective for most field isolates, but its use should be strategically integrated with other groups of fungicides.

A genetic linkage map of Venturia inaequalis, the causal agent of apple scab.

BACKGROUND: Venturia inaequalis is an economically-important disease of apple causing annual epidemics of scab worldwide. The pathogen is a heterothallic ascomycete with an annual cycle of sexual reproduction on infected apple leaf litter, followed by several cycles of asexual reproduction during the apple growing season. Current disease control is achieved mainly through scheduled applications of fungicides. Genetic linkage maps are essential for studying genome structure and organisation, and are a valuable tool for identifying the location of genes controlling important traits of interest such as avirulence, host specificity and mating type in V. inaequalis. In this study, we performed a wide cross under in vitro conditions between an isolate of V. inaequalis from China and one from the UK to obtain a genetically diverse mapping population of ascospore progeny isolates and produced a map using AFLP and microsatellite (SSR) markers. FINDINGS: Eighty-three progeny were obtained from the cross between isolates C0154 (China) x 01/213 (UK). The progeny was screened with 18 AFLP primer combinations and 31 SSRs, and scored for the mating type locus MAT. A linkage map was constructed consisting of 294 markers (283 AFLPs, ten SSRs and the MAT locus), spanning eleven linkage groups and with a total map length of 1106 cM. The length of individual linkage groups ranged from 30.4 cM (Vi-11) to 166 cM (Vi-1). The number of molecular markers per linkage group ranged from 7 on Vi-11 to 48 on Vi-3; the average distance between two loci within each group varied from 2.4 cM (Vi-4) to 7.5 cM (Vi-9). The maximum map length between two markers within a linkage group was 15.8 cM. The MAT locus was mapped to a small linkage group and was tightly linked to two AFLP markers. The map presented is over four times longer than the previously published map of V. inaequalis which had a total genetic distance of just 270 cM. CONCLUSION: A genetic linkage map is an important tool for investigating the genetics of important traits in V. inaequalis such as virulence factors, aggressiveness and mating type. The linkage map presented here represents a significant improvement over currently published maps for studying genome structure and organisation, and for mapping genes of economic importance on the V. inaequalis genome.