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Hyperspectral Reflectance Response of Seagrass (Enhalus acoroides) and Brown Algae (Sargassum sp.) to Nutrient Enrichment at Laboratory Scale.
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- Journal of Coastal Research, 2012, v. 28, n. 4, p. 956, doi. 10.2112/JCOASTRES-D-11-00222.1
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- Article
Variation in lowland rice yield and its determinants in a rainfed area in Savannakhet Province, Laos.
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- Paddy & Water Environment, 2019, v. 17, n. 2, p. 121, doi. 10.1007/s10333-019-00704-7
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Rice plant growth and nutrient leaching under different patterns of split chemical fertilization on sandy soil using a pot.
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- Paddy & Water Environment, 2019, v. 17, n. 2, p. 91, doi. 10.1007/s10333-019-00701-w
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- Article
Green Polymers from Geobacillus thermodenitrificans DSM465 – Candidates for Molecularly Imprinted Materials.
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- Macromolecular Bioscience, 2006, v. 6, n. 3, p. 210, doi. 10.1002/mabi.200500187
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- Article
Circularly Polarized Luminescence of a Fluorescent Chiral Binaphtylene-Perylenebiscarboxydiimide Dimer.
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- ChemPhysChem, 2007, v. 8, n. 10, p. 1465, doi. 10.1002/cphc.200600747
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- Article
Prediction of Soil Oxalate Phosphorus using Visible and Near-Infrared Spectroscopy in Natural and Cultivated System Soils of Madagascar.
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- Agriculture; Basel, 2020, v. 10, n. 5, p. 177, doi. 10.3390/agriculture10050177
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MORE PANICLES 3, a natural allele of OsTB1/FC1, impacts rice yield in paddy fields at elevated CO<sub>2</sub> levels.
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- Plant Journal, 2023, v. 114, n. 4, p. 729, doi. 10.1111/tpj.16143
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Nuclear and chloroplast DNA phylogeography reveals Pleistocene divergence and subsequent secondary contact of two genetic lineages of the tropical rainforest tree species Shorea leprosula ( Dipterocarpaceae) in South- East Asia.
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- Molecular Ecology, 2013, v. 22, n. 8, p. 2264, doi. 10.1111/mec.12243
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Temporal change and its spatial variety on land surface temperature and land use changes in the Red River Delta, Vietnam, using MODIS time-series imagery.
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- Environmental Monitoring & Assessment, 2015, v. 187, n. 7, p. 1, doi. 10.1007/s10661-015-4691-3
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Using a One-Dimensional Convolutional Neural Network on Visible and Near-Infrared Spectroscopy to Improve Soil Phosphorus Prediction in Madagascar.
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- Remote Sensing, 2021, v. 13, n. 8, p. 1519, doi. 10.3390/rs13081519
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Laboratory Visible and Near-Infrared Spectroscopy with Genetic Algorithm-Based Partial Least Squares Regression for Assessing the Soil Phosphorus Content of Upland and Lowland Rice Fields in Madagascar.
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- Remote Sensing, 2019, v. 11, n. 5, p. 506, doi. 10.3390/rs11050506
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- Article
Canopy Hyperspectral Sensing of Paddy Fields at the Booting Stage and PLS Regression can Assess Grain Yield.
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- Remote Sensing, 2018, v. 10, n. 8, p. 1249, doi. 10.3390/rs10081249
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Vis-NIR Spectroscopy and PLS Regression with Waveband Selection for Estimating the Total C and N of Paddy Soils in Madagascar.
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- Remote Sensing, 2017, v. 9, n. 10, p. 1081, doi. 10.3390/rs9101081
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Retrieval of Chlorophyll-a and Total Suspended Solids Using Iterative Stepwise Elimination Partial Least Squares (ISE-PLS) Regression Based on Field Hyperspectral Measurements in Irrigation Ponds in Higashihiroshima, Japan.
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- Remote Sensing, 2017, v. 9, n. 3, p. 264, doi. 10.3390/rs9030264
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Spectral Index for Quantifying Leaf Area Index of Winter Wheat by Field Hyperspectral Measurements: A Case Study in Gifu Prefecture, Central Japan.
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- Remote Sensing, 2015, v. 7, n. 5, p. 5329, doi. 10.3390/rs70505329
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Evaluation of ASTER GDEM2 in Comparison with GDEM1, SRTM DEM and Topographic-Map-Derived DEM Using Inundation Area Analysis and RTK-dGPS Data.
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- Remote Sensing, 2012, v. 4, n. 8, p. 2419, doi. 10.3390/rs4082419
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Inter- and intra-specific genetic divergence of Asian tiger frogs (genus Hoplobatrachus), with special reference to the population structure of H. tigerinus in Bangladesh.
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- Genes & Genetic Systems, 2016, v. 91, n. 4, p. 217, doi. 10.1266/ggs.16-00006
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Effects of calving interval on milk production of dairy herd at Hiroshima University Farm.
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- Nihon Chikusan Gakkaiho, 2019, v. 90, n. 2, p. 111, doi. 10.2508/chikusan.90.111
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Effect of relationships among clinical mastitis incidence, reproductive performance, and culling rate on the lifetime of dairy cows at Hiroshima University Farm.
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- Animal Science Journal, 2021, v. 92, n. 1, p. 1, doi. 10.1111/asj.13591
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Effect of varying fermentation conditions with ensiling period and inoculum on photosynthetic pigments and phytol content in Italian ryegrass (Lolium multiflorum Lam.) silage.
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- Animal Science Journal, 2020, v. 91, n. 1, p. 1, doi. 10.1111/asj.13309
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Effects of nitrogen fertilizer and harvesting stage on photosynthetic pigments and phytol contents of Italian ryegrass silage.
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- Animal Science Journal, 2017, v. 88, n. 10, p. 1513, doi. 10.1111/asj.12810
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A comparison of plasma glucose and oxidative status in lactating dairy cows in summer and autumn.
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- Animal Science Journal, 2016, v. 87, n. 10, p. 1212, doi. 10.1111/asj.12548
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P-dipping of rice seedlings increases applied P use efficiency in high P-fixing soils.
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- Scientific Reports, 2020, v. 10, n. 1, p. 1, doi. 10.1038/s41598-020-68977-1
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The Relationship between the Physical Quality of Rice and the Market Price: A Case Study in Savannakhet, Laos, Using a Bayesian Approach.
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- Sustainability (2071-1050), 2018, v. 10, n. 11, p. 4151, doi. 10.3390/su10114151
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A Growth Performance and Nonlinear Growth Curve Functions of Large- and Normal-Sized Japanese Quail (Coturnix japonica).
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- Journal of Poultry Science, 2021, v. 58, n. 2, p. 88, doi. 10.2141/jpsa.0200020
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Cattle dung detection in pastures from drone images using YOLOv5.
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- Grassland Science, 2024, v. 70, n. 4, p. 168, doi. 10.1111/grs.12429
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Changes of photosynthetic pigments and phytol content at different levels of nitrogen fertilizer in Italian ryegrass fresh herbage and hay.
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- Grassland Science, 2022, v. 68, n. 1, p. 53, doi. 10.1111/grs.12335
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Discriminating Pennisetum alopecuoides plants in a grazed pasture from unmanned aerial vehicles using object‐based image analysis and random forest classifier.
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- Grassland Science, 2021, v. 67, n. 1, p. 73, doi. 10.1111/grs.12288
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Simple in‐field evaluation of moisture content in curing forage using normalized differece vegetation index (NDVI).
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- Grassland Science, 2020, v. 66, n. 4, p. 238, doi. 10.1111/grs.12275
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Counting of Pennisetum alopecuroides at heading stage in a grazed pasture using images from an unmanned aerial vehicle.
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- Grassland Science, 2020, v. 66, n. 4, p. 285, doi. 10.1111/grs.12277
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Low‐cost visible and near‐infrared camera on an unmanned aerial vehicle for assessing the herbage biomass and leaf area index in an Italian ryegrass field.
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- Grassland Science, 2018, v. 64, n. 2, p. 145, doi. 10.1111/grs.12184
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Spring growth stage detection in Italian ryegrass field using a ground-based camera system.
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- Grassland Science, 2016, v. 62, n. 3, p. 188, doi. 10.1111/grs.12122
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Estimation of herbage biomass and nutritive status using band depth features with partial least squares regression in Inner Mongolia grassland, China.
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- Grassland Science, 2016, v. 62, n. 1, p. 45, doi. 10.1111/grs.12112
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Evaluating a hand-held crop-measuring device for estimating the herbage biomass, leaf area index and crude protein content in an Italian ryegrass field.
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- Grassland Science, 2015, v. 61, n. 2, p. 101, doi. 10.1111/grs.12083
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Preliminary study to predict the spatial distribution of dung from beef cattle in a slope-grazed pasture.
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- Grassland Science, 2015, v. 61, n. 1, p. 50, doi. 10.1111/grs.12077
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Use of a hand-held crop growth measuring device to estimate forage crude protein mass of pasture.
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- Grassland Science, 2014, v. 60, n. 4, p. 214, doi. 10.1111/grs.12064
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Genetic algorithm-based partial least squares regression for estimating legume content in a grass-legume mixture using field hyperspectral measurements.
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- Grassland Science, 2013, v. 59, n. 3, p. 166, doi. 10.1111/grs.12026
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Estimating the spatial distribution of green herbage biomass and quality by geostatistical analysis with field hyperspectral measurements.
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- Grassland Science, 2011, v. 57, n. 3, p. 142, doi. 10.1111/j.1744-697X.2011.00221.x
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Waveband selection using a phased regression with a bootstrap procedure for estimating legume content in a mixed sown pasture.
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- Grassland Science, 2011, v. 57, n. 2, p. 81, doi. 10.1111/j.1744-697X.2011.00212.x
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Testing genetic algorithm as a tool to select relevant wavebands from field hyperspectral data for estimating pasture mass and quality in a mixed sown pasture using partial least squares regression.
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- Grassland Science, 2010, v. 56, n. 4, p. 205, doi. 10.1111/j.1744-697X.2010.00196.x
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Utilization by cattle of a pasture including aged hilly sections.
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- Grassland Science, 2010, v. 56, n. 3, p. 160, doi. 10.1111/j.1744-697X.2010.00189.x
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Development of an automatic classification system for eating, ruminating and resting behavior of cattle using an accelerometer.
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- Grassland Science, 2008, v. 54, n. 4, p. 231, doi. 10.1111/j.1744-697X.2008.00126.x
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Estimating forage biomass and quality in a mixed sown pasture based on partial least squares regression with waveband selection.
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- Grassland Science, 2008, v. 54, n. 3, p. 131, doi. 10.1111/j.1744-697X.2008.00116.x
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Grassland degradation in China: Methods of monitoring, management and restoration.
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- Grassland Science, 2007, v. 53, n. 1, p. 1, doi. 10.1111/j.1744-697X.2007.00073.x
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Estimating the spatial distribution of available biomass in grazing forests with a satellite image: A preliminary study.
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- Grassland Science, 2005, v. 51, n. 2, p. 107, doi. 10.1111/j.1744-697X.2005.00015.x
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Comparing MODIS vegetation indices with AVHRR NDVI for monitoring the forage quantity and quality in Inner Mongolia grassland, China.
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- Grassland Science, 2005, v. 51, n. 1, p. 33, doi. 10.1111/j.1744-697X.2005.00006.x
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- Article