Isolation and Characterization of P450 Gene from the Formosan Subterranean Termite, Coptotermes formosanus (Isoptera: Rhinotermitidae)

A cytochrome P450 gene belonging to family9 was isolated from the midgut transcriptome of the termite Coptotermes formosanus Shiraki, for screening enzymes related to biomass degeneration. Some studies show that insect P450 enzymes have ligninase activities for catalyzing lignin degradation. We employed the RACE method to clone this cytochrome P450 gene, named CYP9AX1 (GenBank accession No.JN969113). To the best of our knowledge, CYP9AX1 is the first member of the CYP9 family cloned from this termite. The full-length CYP9AX1 cDNA was 2242 bp long and included a 1599bp open-reading-frame (ORF), a 61-bp 5’-untranslated region (UTR) and a 592-bp 3’-UTR (excluding the poly-A tail). The CYP9AX1 protein deduced from the ORF contains 532 amino acids with a predicted signal peptide composed of 20 amino acid at its N-terminal and the classic heme-binding domain FXXGXXXCXG (residues 468-477). At position 473, residue Arg (R) changes to Gln (Q), this suggests that CYP9AX1 is a new type of CYP subfamily 9A. The phylogenetic tree showed that C. formosanus has high genetic relationship with Blattella germanica and Diploptera punctata. Quantitative RT-PCR assays demonstrated that CYP9AX1 was expressed most abundantly in malpighian tubules, and slightly lower in the head, foregut, midgut and hindgut. The results suggested that CYP9AX1 may be involved in enzymatic detoxification systems of the delignification process in C. formosanus

Introduction from the Wild and Growth Characterization of Three Provenances of Calotropis procera (Ait) in a Domesticated State in Dry lands of South Eastern Kenya

Calotropis procera is a wild species that is drought-resistant and important in production of wool, fibre, biomass among other uses. There exist high demand of the wool in Asian countries and collection from the wild has been going on in Kenya and other countries. However, this collection does not meet the quantity required. Domestication of the species may be the key in bridging the quality and quantity demands for the wool. A study is being undertaken to evaluate growth, phenology and wool productivity of selected provenances of C. procera in dry lands of S. Eastern Kenya. The research site is situated between 01.313580S, 037.755460 E and 01.314220S, 037.755760E and elevation of 1173m a.s.l in South Eastern Kenya University (SEKU), Kitui County, Kenya. The research started in January 2015 with the main focus on monitoring the growth, phenological characteristics and wool productivity of the species in a typical farm setting. This paper focuses on growth characterization of three provenances of C. procera under different spacings (1.5mx1.5m, 2mx2m and 3mx3m). Results indicate that the species can be domesticated, it is hardy and capable of achieving an average field survival of over 97%. The species is multi-stemmed with Tharaka provenance showing highest mean branching of 13.25 followed by Baringo (12.22) then Kibwezi (11.98). Kibwezi recorded a slightly higher DBH growth of 3.90cm followed by Baringo (3.83) then Tharaka (3.82). Tharaka had highest mean height of 187.89cm, Baringo (184.25) and Kibwezi (182.63). Test of homogeneity of variances showed significant statistical differences (P<0.5) with Kibwezi being the least significant (0.043), Baringo (0.01) and Tharaka (0.000). All provenances showed a strong positive correlation (Pearson, P<0.01, n = 12) of branching, DBH and Height with Kibwezi recording rs = 0.975, Baringo (rs = 0.988) and Tharaka (rs = 0.996). Differences in spacing levels started affecting growth parameters from the age of ten months with 3x3 showing highest DBH followed by 2x2 then 1.5x1.5. In terms of height, 1.5x1.5 has the highest (182.85cm), 2x2 (172.42) and 3x3 (168.65). 3x3 was not statistically significant (0.806, P<0.05) while 2x2 and 1.5x1.5 had significance of 0.001 and 0.000 respectively. All spacing levels showed strong positive correlations (Spearman, P<0.01, n = 12) of the study parameters where 1.5x1.5 had rs = 0.614, 2x2 (rs = 0.972) and 3x3 (rs = 0.986) all at P<0.01. The study can authoritatively conclude that the species can establish and grow well in a typical farm setting in dry lands. Spacing affects growth parameters from the age of 10 months. Baringo provenance and 2x2 spacing have performed best. The study recommends analysis of wool productivity to justify the best provenance and spacing. Keywords: Calotropis procera, Domestication, Kibwezi Provenance, Tharaka Provenance, Baringo provenanc

Auxin efflux controls orderly nucellar degeneration and expansion of the female gametophyte in Arabidopsis

The nucellus tissue in flowering plants provides nutrition for the development of the female gametophyte (FG) and young embryo. The nucellus degenerates as the FG develops, but the mechanism controlling the coupled process of nucellar degeneration and FG expansion remains largely unknown. The degeneration process of the nucellus and spatiotemporal auxin distribution in the developing ovule before fertilization were investigated in Arabidopsis thaliana. Nucellar degeneration before fertilization occurs through vacuolar cell death and in an ordered degeneration fashion. This sequential nucellar degeneration is controlled by the signalling molecule auxin. Auxin efflux plays the core role in precisely controlling the spatiotemporal pattern of auxin distribution in the nucellus surrounding the FG. The auxin efflux carrier PIN1 transports maternal auxin into the nucellus while PIN3/PIN4/PIN7 further delivers auxin to degenerating nucellar cells and concurrently controls FG central vacuole expansion. Notably, auxin concentration and auxin efflux are controlled by the maternal tissues, acting as a key communication from maternal to filial tissue

Farm types and farmer motivations to adapt:Implications for design of sustainable agricultural interventions in the rubber plantations of South West China

Tropical land use is one of the leading causes of global environmental change. Sustainable agricultural development aims to reduce the negative environmental impacts of tropical land use whilst enhancing the well-being of the smallholder farmers residing in those areas. Interventions with this goal are typically designed by scientists educated in the Western tradition, and often achieve lower than desired uptake by smallholder farmers. We build on work done in farm type classification and studies of factors that influence adaptation, trialling a suite of household survey questions to elucidate the motivational factors that influence a farmer's willingness to adapt to external change. Based on a sample of 1015 households in the rubber growing region of Xishuangbanna, South-west China, we found that farm types based on structural characteristics (e.g. crops, livelihoods) could not be used to accurately predict farmers' motivations to adapt. Amongst all six farm types identified, the full range of motivational typologies was found. We found six motivational types, from most to least likely to adapt, named: Aspirational Innovators, Conscientious, Copy Cats, Incentive-centric, Well Settled, and Change Resistant. These groups roughly corresponded with those identified in literature regarding diffusion of innovations, but such classifications are rarely used in development literature. We predict that only one third of the population would be potentially willing to trial a new intervention, and recommend that those sectors of the population should be identified and preferentially targeted by development programs. Such an approach requires validation that these motivational typologies accurately predict real behaviour – perhaps through a panel survey approach. Dedicated data gathering is required, beyond what is usually carried out for ex-ante farm typologies, but with some refinements of the methodology presented here the process need not be onerous. An improved suite of questions to appraise farmers' motivations might include value orientations, life satisfaction, and responses to various scenarios, all phrased to be locally appropriate, with a scoring system that uses the full range of potential scores and a minimum of follow up and peripheral questions

Exploring ascomycete diversity in Yunnan, China I: resolving ambiguous taxa in Phaeothecoidiellaceae and investigating conservation implications of fungi

Yunnan, located in southwestern China, is known for its high fungal diversity, and many of which are endemic to the region. As part of our ongoing studies on fungi in Yunnan, we introduce two new genera in Phaeothecoidiellaceae (Mycosphaerellales), to accommodate one Repetophragma-like and another Stomiopeltis-like taxa. Pseudorepetophragma gen. nov. is introduced herein as a monotypic genus to accommodate P. zygopetali comb. nov.(≡ Repetophragma zygopetali), whereas Pseudostomiopeltis gen. nov. is introduced to accommodate Ps. xishuangbannaensis gen. et sp. nov. and Ps. phyllanthi comb. nov.(≡ Stomiopeltis phyllanthi), based on a new collection from Yunnan. In addition, Stomiopeltis sinensis is transferred to Exopassalora as E. sinensis comb. nov. due to its phylogenetic affinity and grouped with E. zambiae, the generic type of Exopassalora. This study provides new insights into the biodiversity of fungal species in this region and adds to our understanding of their ecological roles, as well as the resolution to ambiguous taxa in Phaeothecoidiellaceae

High-resolution maps show that rubber causes substantial deforestation

Understanding the effects of cash crop expansion on natural forest is of fundamental importance. However, for most crops there are no remotely sensed global maps1, and global deforestation impacts are estimated using models and extrapolations. Natural rubber is an example of a principal commodity for which deforestation impacts have been highly uncertain, with estimates differing more than fivefold1,2,3,4. Here we harnessed Earth observation satellite data and cloud computing5 to produce high-resolution maps of rubber (10 m pixel size) and associated deforestation (30 m pixel size) for Southeast Asia. Our maps indicate that rubber-related forest loss has been substantially underestimated in policy, by the public and in recent reports6,7,8. Our direct remotely sensed observations show that deforestation for rubber is at least twofold to threefold higher than suggested by figures now widely used for setting policy4. With more than 4 million hectares of forest loss for rubber since 1993 (at least 2 million hectares since 2000) and more than 1 million hectares of rubber plantations established in Key Biodiversity Areas, the effects of rubber on biodiversity and ecosystem services in Southeast Asia could be extensive. Thus, rubber deserves more attention in domestic policy, within trade agreements and in incoming due-diligence legislation

Model transfer from 2D to 3D study for boxing pose estimation

IntroductionBoxing as a sport is growing on Chinese campuses, resulting in a coaching shortage. The human pose estimation technology can be employed to estimate boxing poses and teach interns to relieve the shortage. Currently, 3D cameras can provide more depth information than 2D cameras. It can potentially improve the estimation. However, the input channels are inconsistent between 2D and 3D images, and there is a lack of detailed analysis about the key point location, which indicates the network design for improving the human pose estimation technology.MethodTherefore, a model transfer with channel patching was implemented to solve the problems of channel inconsistency. The differences between the key points were analyzed. Three popular and highly structured 2D models of OpenPose (OP), stacked Hourglass (HG), and High Resolution (HR) networks were employed. Ways of reusing RGB channels were investigated to fill up the depth channel. Then, their performances were investigated to find out the limitations of each network structure.Results and discussionThe results show that model transfer learning by the mean way of RGB channels patching the lacking channel can improve the average accuracies of pose key points from 1 to 20% than without transfer. 3D accuracies are 0.3 to 0.5% higher than 2D baselines. The stacked structure of the network shows better on hip and knee points than the parallel structure, although the parallel design shows much better on the residue points. As a result, the model transfer can practically fulfill boxing pose estimation from 2D to 3D