Nutrition Management and Automation

[1]  K. Swain,et al.  Adoption of an unmanned helicopter for low-altitude remote sensing to estimate yield and total biomass of a rice crop. , 2010 .

[2]  Pablo J. Zarco-Tejada,et al.  Thermal and Narrowband Multispectral Remote Sensing for Vegetation Monitoring From an Unmanned Aerial Vehicle , 2009, IEEE Transactions on Geoscience and Remote Sensing.

[3]  Minzan Li,et al.  Development of an optical sensor for crop leaf chlorophyll content detection , 2009 .

[4]  Robert B. Waide,et al.  Tropical forest biomass and successional age class relationships to a vegetation index derived from Landsat TM data , 1989 .

[5]  Lei Tian,et al.  Development of autonomous unmanned helicopter based agricultural remote sensing system , 2006 .

[6]  Yuan Wang,et al.  [Predicting nitrogen concentrations from hyperspectral reflectance at hyperspectral reflectance at leaf and canopy for rape]. , 2008, Guang pu xue yu guang pu fen xi = Guang pu.

[7]  Gamal ElMasry,et al.  Quality classification of cooked, sliced turkey hams using NIR hyperspectral imaging system , 2011 .

[8]  Fan Zhang,et al.  Applying Near-Infrared Spectroscopy and Chemometrics to Determine Total Amino Acids in Herbicide-Stressed Oilseed Rape Leaves , 2011 .

[9]  Lei Tian,et al.  IN-FIELD VARIABILITY DETECTION AND SPATIAL YIELD MODELING FOR CORN USING DIGITAL AERIAL IMAGING , 1999 .

[10]  M. Nilsson.  Estimation of tree heights and stand volume using an airborne lidar system , 1996 .

[11]  Janet Franklin,et al.  Estimating foliage and woody biomass in Sahelian and Sudanian woodlands using a remote sensing model , 1991 .

[12]  W. Walker,et al.  Mapping forest structure for wildlife habitat analysis using waveform lidar: Validation of montane ecosystems , 2005 .

[13]  G. Foody,et al.  Predictive relations of tropical forest biomass from Landsat TM data and their transferability between regions , 2003 .

[14]  Min Huang,et al.  Nondestructive determination of nutritional information in oilseed rape leaves using visible/near infrared spectroscopy and multivariate calibrations , 2011, Science China Information Sciences.

[15]  J. Sinfield,et al.  Review: Evaluation of sensing technologies for on-the-go detection of macro-nutrients in cultivated soils , 2010 .

[16]  Q. Zaman,et al.  Estimation of Rice Yield and Protein Content Using Remote Sensing Images Acquired by Radio Controlled Unmanned Helicopter , 2008 .

[17]  Min Huang,et al.  [Nitrogen stress measurement of canola based on multi-spectral charged coupled device imaging sensor]. , 2006, Guang pu xue yu guang pu fen xi = Guang pu.

[18]  Wenwen Kong,et al.  Nondestructive Estimation of Nitrogen Status and Vegetation Index of Oilseed Rape Canopy Using Multi-Spectral Imaging Technology , 2011 .

[19]  D. Lu.  Aboveground biomass estimation using Landsat TM data in the Brazilian Amazon , 2005 .

[20]  Chenghai Yang,et al.  Airborne Hyperspectral Imaging and Yield Monitoring of Grain Sorghum Yield Variability , 2002 .

[21]  L. Tian,et al.  A review of remote sensing methods for biomass feedstock production. , 2011 .

[22]  J. W Colburn,et al.  Soil Doctor Multi-Parameter, Real-Time Soil Sensor and Concurrent Input Control System , 1999 .

[23]  C. Daughtry,et al.  Evaluation of Digital Photography from Model Aircraft for Remote Sensing of Crop Biomass and Nitrogen Status , 2005, Precision Agriculture.

[24]  D. M. Edwards,et al.  Identifying and Measuring Crop Type Using Satellite Imagery , 1976 .

[25]  R. Dubayah,et al.  Above-ground biomass estimation in closed canopy Neotropical forests using lidar remote sensing: factors affecting the generality of relationships , 2003 .

[26]  P. C. Robert,et al.  Evaluating management zone technology and grid soil sampling for variable rate nitrogen application. , 2000 .

[27]  H. Kage,et al.  Analysis of vegetation indices derived from hyperspectral reflection measurements for estimating crop canopy parameters of oilseed rape (Brassica napus L.) , 2008 .

[28]  T. Schmugge,et al.  Research Article: Using Unmanned Aerial Vehicles for Rangelands: Current Applications and Future Potentials , 2006 .

[29]  J. M. S. Hutchinson,et al.  ESTIMATING NEAR–SURFACE SOIL MOISTURE USING ACTIVE MICROWAVE SATELLITE IMAGERY AND OPTICAL SENSOR INPUTS , 2003 .

[30]  Patrick D. Gerard,et al.  Characterizing vertical forest structure using small-footprint airborne LiDAR , 2003 .

[31]  João Roberto dos Santos,et al.  Airborne P-band SAR applied to the aboveground biomass studies in the Brazilian tropical rainforest , 2003 .

[32]  Noboru Noguchi,et al.  Drafting of Field Map Using Image by Tilted Image Sensor with Unmanned Helicopter , 2008 .

[33]  D. Lu.  The potential and challenge of remote sensing‐based biomass estimation , 2006 .

[34]  Roberto Oberti,et al.  Test of an automatic rate control system for a centrifugal-type dry fertilizer spreader , 1999 .

[35]  Yong He,et al.  Estimation of Acetolactate Synthase Activity in Brassica napus under Herbicide Stress Using Near-Infrared Spectroscopy , 2012 .

[36]  R. Dubayah,et al.  Estimation of tropical forest structural characteristics using large-footprint lidar , 2002 .

[37]  L. C. Guan,et al.  The applications of computer vision system and tomographic radar imaging for assessing physical properties of food , 2004 .

[38]  D. Mulla,et al.  Soil sampling and interpolation techniques for mapping spatial variability of soil properties. , 1997 .

[39]  Lei Tian,et al.  Development of a low-cost agricultural remote sensing system based on an autonomous unmanned aerial vehicle (UAV) , 2011 .

[40]  Ross Nelson,et al.  Estimating forest biomass and volume using airborne laser data , 1988 .

[41]  Thomas R. Crow,et al.  Estimating aboveground biomass using Landsat 7 ETM+ data across a managed landscape in northern Wisconsin, USA , 2004 .

[42]  N. Coops,et al.  Using airborne and ground-based ranging lidar to measure canopy structure in Australian forests , 2003 .

[43]  Lei Tian,et al.  Practical methods for geometric distortion correction of aerial hyperspectral imagery , 2004 .

[44]  E. Hosein,et al.  Effect of chronic alcohol administration on the hormonal sensitivity of isolated perfused rat liver. , 1981, Life sciences.

[45]  P. C. Robert,et al.  Management zones for soil N and P levels in the Northern Great Plains. , 2000 .

[46]  Yong He,et al.  Prediction of soil macronutrients content using near-infrared spectroscopy , 2007 .

[47]  Antonio P. Mallarino,et al.  Identifying cost-effective soil sampling schemes for variable-rate fertilization and liming. , 2000 .

[48]  M. Steininger.  Satellite estimation of tropical secondary forest above-ground biomass: Data from Brazil and Bolivia , 2000 .

[49]  Fumin Wang,et al.  Monitoring rice nitrogen status using hyperspectral reflectance and artificial neural network. , 2007, Environmental science & technology.

[50]  Mohammad-R. Akbarzadeh-T,et al.  Computer vision systems (CVS) for moisture content estimation in dehydrated shrimp , 2009 .

[51]  Fei Liu,et al.  Determination of acetolactate synthase activity and protein content of oilseed rape (Brassica napus L.) leaves using visible/near-infrared spectroscopy. , 2008, Analytica chimica acta.

[52]  José Ranilla,et al.  The usefulness of artificial intelligence techniques to assess subjective quality of products in the food industry , 2001 .

[53]  Yubin Lan,et al.  Development of an Unmanned Aerial Vehicle-Based Spray System for Highly Accurate Site-Specific Application , 2008 .

[54]  Qin Zhang,et al.  Fuzzy logic control of a multispectral imaging sensor for in-field plant sensing , 2008 .

[55]  Yong He,et al.  [Study on the relationship between spectral properties of oilseed rape leaves and their chlorophyll content]. , 2007, Guang pu xue yu guang pu fen xi = Guang pu.

[56]  M. Flood,et al.  LiDAR remote sensing of forest structure , 2003 .

[57]  P. Hardin,et al.  An Unmanned Aerial Vehicle for Rangeland Photography , 2005 .

[58]  Shufeng Han,et al.  Comparison of Satellite Remote Sensing and Aerial Photography for Ability to Detect In-Season Nitrogen Stress in Corn , 2001 .

[59]  Y. E. Shimabukuro,et al.  NOAA-AVHRR data processing for the mapping of vegetation cover , 1997 .

[60]  W. Cohen,et al.  Surface lidar remote sensing of basal area and biomass in deciduous forests of eastern Maryland, USA , 1999 .

[61]  H. Bremner,et al.  Exploration of the Use of NIR Reflectance Spectroscopy to Distinguish and Measure Attributes of Conditioned and Cooked Shrimp (Pandalus borealis) , 2001 .

[62]  W. Cohen,et al.  Lidar Remote Sensing of the Canopy Structure and Biophysical Properties of Douglas-Fir Western Hemlock Forests , 1999 .

[63]  Transition to Twenty-First Century Agriculture: Change of Direction , 2012, Agricultural Research.

[64]  John P. Fulton,et al.  Evaluating the Sensitivity of an Unmanned Thermal Infrared Aerial System to Detect Water Stress in a Cotton Canopy , 2007 .