Spatial stochastic volatility for lattice data

Spatial heteroscedasticity may arise jointly with spatial autocorrelation in lattice data collected from agricultural trials and environmental studies. This leads to spatial clustering not only in the level but also in the variation of the data, the latter of which may be very important, for example, in constructing prediction intervals. This article introduces a spatial stochastic volatility (SSV) component into the widely used conditional autoregressive (CAR) model to capture the spatial clustering in heteroscedasticity. The SSV component is a mean zero, conditionally independent Gaussian process given a latent spatial process of the variances. The logarithm of the latent variance process is specified by an intrinsic Gaussian Markov random field. The SSV model relaxes the traditional homoscedasticity assumption for spatial heterogeneity and brings greater flexibility to the popular spatial statistical models. The Bayesian method is used for inference. The full conditional distribution of the heteroscedasticity components can be shown to be log-concave, which facilitates an adaptive rejection sampling algorithm. Application to the well-known wheat yield data illustrates that incorporating spatial stochastic volatility may reveal the spatial heteroscedasticity hidden from existing analyses.     

Palladium immobilized on aminated polyacrylonitrile nanofiber as an efficient heterogeneous catalyst for Heck reaction

Aminated polyacrylonitrile (PAN-NH) nanofiber mats prepared by electrospinning and then aminated by multiamines with different chemical structures have been used for the immobilization of palladium. The PAN-NH fiber morphologies were characterized by scanning electron microscopy (SEM) and the dispersion of palladium particles on the PAN-NH fiber were examined by transmission electron microscopy (TEM). The catalytic activity and recyclability of the prepared heterogeneous palladium catalysts have been evaluated by the Heck reaction of iodobenzene with n-butyl acrylate. It was found that the catalytic activities of PAN-NH-Pd catalysts could be correlated with the chelating energies of the PAN-NH fiber mats with Pd active species.     

Coexpression of 16.8 kDa antigen of Mycobacterium avium paratuberculosis and murine gamma interferon in a bicistronic vector and studies on its potential as DNA vaccine

Paratuberculosis or Johne’s disease is a chronic gastric disease of ruminants. For this disease there is no effective treatment or preventive measure available. 16.8 kDa protein is an immunogenic protein of Mycobacterium avium paratuberculosis and can be an ideal candidate for developing a DNA vaccine construct. In present study a bicistronic DNA vaccine construct pIR16.8/IFN was developed using eukaryotic vector pIRES 6.1. Two genes MPT (expressing 16.8 kDa protein) and murine IFNγ were cloned, expressed and immunoreactivity was studied in murine model. Immunoreactivity was also compared with monocistronic construct pIR16.8 expressing 16.8 kDa protein. Both pIR16.8 and pIR16.8/IFN showed eukaryotic expression of respective proteins in BHK21 cells. The expressed proteins also showed immunoreactivity when reacted with hyperimmune sera raised against recombinant 16.8 kDa protein in western blot assay and immunofluorence assay. Both constructs were used as DNA vaccine in murine model and immunogenecity was studied by DTH, lymphocyte proliferation assay and NO determination. DTH reaction was significantly high in pIR16.8/IFN than pIR16.8 group, similarly lymphocyte proliferation and NO release was higher in pIR16.8/IFN group than pIR16.8 group. This indicated T cell epitopic nature of 16.8 kDa protein. The study also showed that co-expression of IFNγ with mycobacterial gene can enhance immunogenecity of DNA vaccine and can be used as immunoadjuvant.     

Participatory plant breeding approach for host plant resistance to bean fly in common bean under semi-arid Kenya conditions

Common bean (Phaseolus vulgaris L.) is the most important legume crop in Kenya. It is cultivated across a wide range of agro-ecologies which include high potential and marginal areas. Eastern Kenya alone, largely semi-arid, accounts for 35% of the country’s total bean production. Bean farmers mainly small-scale have limited access to quality seed, chemical pesticides and fertilizer. Therefore, bean yield under on-farm conditions still remains below 500 kg ha⁻¹ while the potential is about 1,200 kg ha⁻¹ under semi-arid conditions. To asses the farmers’ views on bean varieties and a key insect pest and associated constraints contributing to yield loss, research was undertaken. The research included survey to quantify the yield loss and Participatory Rural Appraisal to determine the level of adoption and criteria for variety choice in semi-arid eastern Kenya (SAEK). The results show that farmers consider drought and insect pest problems as main causes for low yields. The adoption rate for improved varieties is high but self sufficiency in beans stands at 23% in the dry transitional (DT) agro-ecology and at 18% in the dry mid-altitude (DM) agro-ecology, respectively. This could be attributed to low adaptability since most of the improved varieties grown were selected for high potential areas but now found in marginal areas. Drought, earliness, yield stability, and insect pest resistance are the main reasons for choice of varieties by farmers. Bean fly (Ophiomyia sp.) was identified as one of the key crop pests of beans limiting yield. Besides, African bollworm (Helicoverpa armigera) and bean aphid (Aphis fabae) were ranked higher. Due to limitations of the conventional breeding approach, a participatory plant breeding approach is suggested so as to provide an opportunity to develop insect pest resistant varieties adapted to the SAEK region.     

Hyper-spectral remote sensing to monitor vegetation stress

Background, aim, and scope  Vegetation stress diagnoses based on plant sampling and physiochemical analysis using traditional methods are commonly time-consuming, destructive and expensive. The measurement of field spectral reflectance is one basis of airborne or spaceborne remote sensing monitoring. Materials and methods  In this study, paddy plants were grown in the barrels evenly filled with 10.0 kg soil that was mixed respectively with 0, 2.5 × 207.2 and 5.0 × 207.2 mg Pb per 1,000 g soil. Rice canopy spectra were gathered by mobile hyper-spectral radiometer (ASD FieldSpec Pro FR, USA). Meanwhile, canopy leaves in the field-of-view (FOV) of spectroradiometer were collected and then prepared in the laboratory, (1) for chlorophyll measurement by Model 721 spectrophotometer, and (2) for Pb determination by atomic absorption spectrophotometer (SpectraAA-220FS). Results and discussion  Canopy spectral reflectance in the region of visible-to-near-infrared light (VNIR) increased, because ascended Pb concentration caused the decrease of canopy chlorophyll content. In the agro-ecosystem, however, heavy metal contamination is presented typically as mixture and their interactions strongly affect actually occurring effects. Normalized spectral absorption depth (D _n), and shifting distance (DS) of red edge position (REPs) revealed the differences in Pb concentration for canopy leaves, especially at the early tillering stage. Due to insufficient biomass of rice plants, the 30th day was not reliable enough for the selection of crucial growth stages. Some special sensitive bands might be omitted at the same time because of limited sample sets. Conclusions  Our initial experiments are still too few in the amounts of both metals and plants neither to build accurate prediction models nor to discuss the transformation from ground to air/spaceborne remote sensing. However, we are pleased to communicate that ground remote sensing measurements would provide reliable information for the estimation of Pb concentration in rice plants at the early tillering stage when proper features (such as DS and D _n) of reflectance spectra are applied. Recommendations and perspectives  Hyper-spectral remote sensing is a potential and promising technology for monitoring environmental stresses on agricultural vegetation. Further ground remote sensing experiments are necessary to evaluate the possibility of hyper-spectral reflectance spectroscopy in monitoring different kinds of metals’ stress on various plants.     

Quantitative trait loci influencing fruit-related characteristics of tomato grown in high-temperature conditions

The objective of this study was to identify molecular markers linked to fruit-related traits in the tomato subjected to high temperatures. In total, 160 F₂ plants derived from a cross between a heat-tolerant breeding line, CL5915-93D4-1-0-3 (Solanum esculentum), and a heat-sensitive wild accession, L4422 (S. pimpinellifolium), were grown in a greenhouse. Six traits including fruit number, fruit weight, brix, seed number, fruit setting, and flower number were scored. The distributions of fruit number, fruit set, flower number, and seed number were skewed towards heat susceptibility which is known to be characteristic of L4422. Polymorphic bands were generated by PCR-derived methods of RAPD, ISSR and AFLP Polymorphism, the segregation ratio, and distribution over the genome of the above 3 markers were compared. Ten linkage groups, ranging 20.6–151.6 cM in size, were constructed with 62 informative markers spanning a total of 776.3 cM. Fruit-related quantitative trait loci (QTLs) were non-randomly distributed in the tomato genome. For the 6 traits investigated, 21 QTLs were dispersed on linkage groups 2–5. The genetic effects of the various QTLs were differently exhibited, in our study we have respectively found from 10.5% to 30.2% of the variation explained by the QTL for flower number (FRN4) and brix (BX2). Thirteen QTL-mapped markers were unique to 1 trait, and 4 markers were linked to more than 1 trait. Among them, QTLs linked to the I868-470 marker had effects on fruit weight and brix, and a significant positive correlation between these 2 traits was noted (r = 0.35, P < 0.05). Thus, the I868-470 marker may have the potential for simultaneous selection of high fruit weight and brix. These markers also allowed us to align genome linkage maps across distantly related species and to reveal the co-localization between these QTLs and major genes.