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The Japanese mealybug Planococcus kraunhiae (Kuwana) is an important pest which spoils many kinds of fruit in Japan. Because conventional application of insecticides is often ineffective, alternative strategies are being investigated for management of this pest. Recent studies revealed that a pheromone-based technique which interferes with sexual communication, i. e. mating disruption, was promising. However, mating disruption usually requires a substantial amount of a pheromone. I therefore developed a new and convenient route for synthesis of the P. kraunhiae pheromone, 2-isopropyliden-5-methyl-4-hexen-1-yl butyrate (fujikonyl butyrate). First, a commercially available isomer of fujikonol, 2-isopropenyl-5-methyl-4-hexen-1-ol (lavandulol), was oxidized, furnishing the corresponding aldehyde (lavandulal). The β,γ double bond of lavandulal smoothly migrated to the α,β position in the presence of acids, and as a consequence, the corresponding aldehyde of fujikonol (fujikonal) was obtained. Fujikonal was then reduced to fujikonol, which was esterified with butyric acid to give the pheromone of P. kraunhiae. All the reactions were accomplished under very mild conditions (room temperature to 50 °C) with good yields. Moreover, only small amounts of by-products were generated. The synthetic pheromone obtained by this method can be used as a mating disruptant. © 2013 The Japanese Society of Applied Entomology and Zoology. Source

Yamamura K.,Japan National Institute for Agro - Environmental Sciences
Population Ecology | Year: 2016

Ronald A. Fisher, who is the founder of maximum likelihood estimation (ML estimation), criticized the Bayes estimation of using a uniform prior distribution, because we can create estimates arbitrarily if we use Bayes estimation by changing the transformation used before the analysis. Thus, the Bayes estimates lack the scientific objectivity, especially when the amount of data is small. However, we can use the Bayes estimates as an approximation to the objective ML estimates if we use an appropriate transformation that makes the posterior distribution close to a normal distribution. One-to-one correspondence exists between a uniform prior distribution under a transformed scale and a non-uniform prior distribution under the original scale. For this reason, the Bayes estimation of ML estimates is essentially identical to the estimation using Jeffreys prior. © 2015, The Society of Population Ecology and Springer Japan. Source

Inoue Y.,Japan National Institute for Agro - Environmental Sciences | Sakaiya E.,Aomori ITC Agricultural Research Institute | Wang C.,University of Missouri
Remote Sensing of Environment | Year: 2014

High-resolution (ca. 1m) synthetic aperture radar (SAR) sensors have great potential for all-weather monitoring of crop biophysical variables in small and mosaic crop fields in Asia. Rice is the most important staple crop in monsoon Asia, and the timely monitoring of rice growth is critical for precision farming and the assessment of productivity. The objective of this study was to determine the potential capability of backscattering coefficients (σ0) from satellite C-band SAR sensors for the assessment of biophysical variables in rice. SAR images were acquired by a Radarsat-2 sensor in spotlight mode during the critical growth stages over 4years in one of the major rice-producing areas of Japan. Detailed plant biophysical measurements were made concurrently with the SAR observations. The seasonal consistency of C-band σ0 was clearly demonstrated. The baseline σ0 values (minimum σ0 for zero-biomass paddy fields) were determined to be -28.5dB in VH and -21.1dB in HH and VV, respectively. The dynamic change in σ0 during the full range of rice growth was similar (ca. 12dB) in all polarizations. A comprehensive analysis revealed the response of C-band σ0 to biophysical canopy variables. High or moderate sensitivity of σ0 to canopy height, water content, or chlorophyll content was superficial and was attributable to the change in leaf biomass and structure. Both the leaf area index (LAI) and leaf biomass were significantly and consistently correlated with σ0 throughout all growth stages. These relationships were expressed by exponential curves with high coefficients of determination, although σ0 saturates at around a LAI of 3 and a leaf biomass of 180gDWm-2. The response of σ0 to total biomass was expressed by an exponential function with a high coefficient of determination, but the sensitivity was clear only within the lower 20% range of the seasonal maximum biomass. The C-band σ0 had the highest correlation with fAPAR, and the σ0-fAPAR relationship was linear throughout the growth stages. The results suggest the suitability of C-band σ0 for the assessment of LAI or fAPAR and show promise for the timely monitoring of rice growth by C-band SAR and/or through its constellation with optical sensors. © 2013 Elsevier Inc. Source

Uchimiya M.,U.S. Department of Agriculture | Hiradate S.,Japan National Institute for Agro - Environmental Sciences
Journal of Agricultural and Food Chemistry | Year: 2014

Pyrolysis of plant and animal wastes produces a complex mixture of phosphorus species in amorphous, semicrystalline, and crystalline inorganic phases, organic (char) components, and within organo-mineral complexes. To understand the solubility of different phosphorus species, plant (cottonseed hull) and manure (broiler litter) wastes were pyrolyzed at 350, 500, 650, and 800 C and exposed to increasingly more rigorous extraction procedures: water (16 h), Mehlich 3 (1 mM EDTA at pH 2.5 for 5 min), oxalate (200 mM oxalate at pH 3.5 for 4 h), NaOH-EDTA (250 mM NaOH + 5 mM EDTA for 16 h), and total by microwave digestion (concentrated HNO3/HCl + 30% H2O 2). Relative to the total (microwave digestible) P, the percentage of extractable P increased in the following order: M3 < oxalate ≈ water < NaOH-EDTA for plant biochars and water < M3 < NaOH-EDTA < oxalate for manure biochars. Solution phase 31P NMR analysis of NaOH-EDTA extracts showed the conversion of phytate to inorganic P by pyrolysis of manure and plant wastes at 350 C. Inorganic orthophosphate (PO4 3-) became the sole species of ≥500 C manure biochars, whereas pyrophosphate (P2O7 4-) persisted in plant biochars up to 650 C. These observations suggested the predominance of (i) amorphous (rather than crystalline) calcium phosphate in manure biochars, especially at ≥650 C, and (ii) strongly complexed pyrophosphate in plant biochars (especially at 350-500 C). Correlation (Pearson's) was observed (i) between electric conductivity and ash content of biochars with the amount of inorganic P species and (ii) between total organic carbon and volatile matter contents with the organic P species. © 2014 American Chemical Society. Source

Sakamoto T.,Japan National Institute for Agro - Environmental Sciences | Gitelson A.A.,University of Nebraska - Lincoln | Arkebauer T.J.,University of Nebraska - Lincoln
Remote Sensing of Environment | Year: 2013

A crop yield estimation model using time-series MODIS WDRVI was developed. The main feature of the proposed model is the incorporation of crop phenology detection using MODIS data, called the "Shape-Model Fitting Method". MODIS WDRVI taken 7-10. days before the corn silking stage had strong linear correlation with corn final grain yield at both field and regional scales. The model revealed spatial patterns of corn final grain yield all over the U.S. from 2000 to 2011. State-level corn yield was estimated accurately with coefficient of variation below 10% especially for the 18 major corn producing states including Iowa, Illinois, Delaware, Minnesota, Ohio, West Virginia, Wisconsin, Michigan, Indiana, Nebraska, Kentucky, New York, South Dakota, Missouri, Pennsylvania, Tennessee, New Jersey and Maryland. The results corresponded well with the spatial pattern of high-yield regions derived from the USDA/NASS data. However, the model tended to underestimate corn grain yield in three irrigated regions: the Midwestern region depending on the Ogallala Aquifer, the downstream basin of the Mississippi, and the southwestern region of Georgia. In contrast, it tended to overestimate corn grain yield around the outlying regions of the U.S. Corn Belt, specifically, the East Coast, North Dakota, Minnesota, Wisconsin, and Missouri. The estimation accuracy of the proposed model differed depending on the region. However, the annual variation of state level corn grain yield could be detected with high accuracy, especially in the major corn producing states. © 2012 Elsevier Inc. Source

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