Access the full text.
Sign up today, get DeepDyve free for 14 days.
D. Mandallaz (2000)
Estimation of the spatial covariance in Universal Kriging: Application to forest inventoryEnvironmental and Ecological Statistics, 7
S. Blankenship, M. Parker, C. Unrath (1997)
Use of Maturity Indices for Predicting Poststorage Firmness of `Fuji' ApplesHortscience, 32
(2008)
Structure identification in the intrinsic case
Y. Isagi, K. Sugimura, A. Sumida, Hiroki Itô (1997)
How Does Masting Happen and SynchronizeJournal of Theoretical Biology, 187
P. Marquina, M. Venturini, R. Oria, A. Negueruela (2004)
Monitoring Colour Evolution During Maturity in Fuji ApplesFood Science and Technology International, 10
A. Hastings (2004)
Transients: the key to long-term ecological understanding?Trends in ecology & evolution, 19 1
G. Maletti, D. Wulfsohn (2006)
Evaluation of variance models for fractionator sampling of treesJournal of Microscopy, 222
(2006)
Unbiased estimator of the number
R. Bramley, R. Hamilton (2004)
Understanding variability in winegrape production systemsAustralian Journal of Grape and Wine Research, 10
J. Yanai, Choung-Keun Lee, T. Kaho, M. Iida, T. Matsui, M. Umeda, T. Kosaki (2001)
Geostatistical analysis of soil chemical properties and rice yield in a paddy field and application to the analysis of yield-determining factorsSoil Science and Plant Nutrition, 47
Xujun Ye, K. Sakai, M. Manago, S. Asada, A. Sasao (2007)
Prediction of citrus yield from airborne hyperspectral imageryPrecision Agriculture, 8
D. Greer (2005)
Non‐destructive chlorophyll fluorescence and colour measurements of ‘Braeburn’ and ‘Royal Gala’ apple (Malus domestica) fruit development throughout the growing seasonNew Zealand Journal of Crop and Horticultural Science, 33
Radhakrishna Rao (1971)
Minimum variance quadratic unbiased estimation of variance componentsJournal of Multivariate Analysis, 1
S. Best, F. Salazar, R. Bastías, L. León (2008)
Var. Royal GalaJournal of Information Technology in Agriculture, 3
R. Godwin, G. Wood, J. Taylor, S. Knight, J. Welsh (2003)
Precision Farming of Cereal Crops: a Review of a Six Year Experiment to develop Management GuidelinesBiosystems Engineering, 84
L. Pozdnyakova, D. Giménez, P. Oudemans (2005)
Spatial Analysis of Cranberry Yield at Three ScalesAgronomy Journal, 97
(2001)
Geostatistical analysis
G. Pelletier, S. Upadhyaya (1999)
Development of a tomato load/yield monitorComputers and Electronics in Agriculture, 23
(2002)
Precision farming in Europe and the Greek potential
R. Dris (2002)
Environment and Crop Production
N. Zhang, Maohua Wang, Ning Wang (2002)
Precision agriculture—a worldwide overviewComputers and Electronics in Agriculture, 36
T. Gemtos, A. Markinos, T. Nassiou, J. Stafford (2005)
Cotton lint quality spatial variability and correlation with soil properties and yield.
K. Aggelopoulou, D. Pateras, S. Fountas, T. Gemtos, G. Nanos, J. Stafford (2007)
Soil spatial variability in small Greek apple orchards.
(1976)
Linear estimation of nonstationary spatial phenomena
(2004)
Trend yield maps in Greece and the UK
A. Roel, R. Plant (2004)
Factors underlying yield variability in two California rice fieldsAgronomy Journal, 96
A. Roel, R. Plant (2004)
Spatiotemporal Analysis of Rice Yield Variability in Two California FieldsAgronomy Journal
(2008)
Crop load estimation model to optimize yield-quality ratio in apple orchards, Malus Domestica Borkh, Var
F. López-Granados, M. Jurado-Expósito, S. Alamo, L. Garcia-Torres (2004)
Leaf nutrient spatial variability and site-specific fertilization maps within olive (Olea europaea L.) orchardsEuropean Journal of Agronomy, 21
A. Markinos, T. Gemtos, D. Pateras, L. Toulios, G. Zerva, M. Papaeconomou (2005)
The influence of cotton variety in the calibration factor of a cotton yield monitorOperational Research, 5
R. Bramley (2005)
Understanding variability in winegrape production systems 2. Within vineyard variation in quality over several vintagesAustralian Journal of Grape and Wine Research, 11
D. Lambert, J. Lowenberg‐DeBoer, T. Griffin, J. Peone, T. Payne, S. Daberkow (2004)
ADOPTION, PROFITABILITY, AND MAKING BETTER USE OF PRECISION FARMING DATA
(2004)
General and specialized pomology
G. Watson, M. Guarascio, M. David, C. Huijbregts (1977)
Advanced Geostatistics in the Mining IndustryInternational Statistical Review, 47
K. Sakai, Y. Noguchi, S. Asada (2008)
Detecting chaos in a citrus orchard: Reconstruction of nonlinear dynamics from very short ecological time seriesChaos Solitons & Fractals, 38
R. Mcguire (1992)
Reporting of Objective Color MeasurementsHortscience, 27
D. Marcotte, M. David (1988)
Trend surface analysis as a special case of IRF-k krigingMathematical Geology, 20
A. Lakso, T. Robinson (1997)
PRINCIPLES OF ORCHARD SYSTEMS MANAGEMENT OPTIMIZING SUPPLY, DEMAND AND PARTITIONING IN APPLE TREES
S Best, I Zamora (2008)
Tecnologías aplicable en agricultura de precisión. Uso de Tecnología de Precisión en Evaluación, Diagnóstico y Solución de Problemas Productivos
S. Fountas, S. Blackmore, D. Ess, S. Hawkins, G. Blumhoff, J. Lowenberg‐DeBoer, C. Sørensen (2005)
Farmer Experience with Precision Agriculture in Denmark and the US Eastern Corn BeltPrecision Agriculture, 6
(2002)
Influence of orchard management on growth and production of fruits
(2008)
Crop load estimation model to optimize yieldquality ratio in apple orchards , Malus Domestica Borkh , Var . Royal Gala
D. Wulfsohn, G. Maletti, T. Toldam-Andersen (2006)
Unbiased estimator for the total number of flowers on a tree
(2006)
Unbiased estimator of the number of flowers on a tree
Qamar-uz-zaman, A. Schumann (2006)
Nutrient Management Zones for Citrus Based on Variation in Soil Properties and Tree PerformancePrecision Agriculture, 7
A. Dobermann, J. Ping (2004)
Geostatistical Integration of Yield Monitor Data and Remote Sensing Improves Yield MapsAgronomy Journal, 96
(1993)
Statistics for spatial data, revised version
H Wackernagel (2003)
Multivariate geostatistics
We describe the yield and quality of apples from a 0.8 ha apple orchard located in northern Greece over two growing seasons and consider the potential for site-specific management. The orchard has two apple cultivars: Red Chief (main cultivar) and Fuji (pollinator). Yield was measured by weighing all fruit harvested from groups of five adjacent trees and the position of the central tree was recorded by GPS. Apple quality at harvest was evaluated from samples of the two cultivars in both years for which fruit mass, flesh firmness, soluble solids content, juice pH and acidity of the juice were determined. The variation in tree flowering was also measured in the spring of the second season using a stereological sampling procedure. The results showed considerable variability in the number of tree flowers, yield and quality across the orchard for both cultivars. The number of flowers was strongly correlated with the final yield. These data could potentially be used to plan precise thinning and for early prediction of yield; the latter is important for marketing the fruit. Several quality characteristics, including fruit juice soluble solids content and acid content were negatively correlated with yield. The general patterns of spatial variation in several variables suggested that changes in topography and aspect had important effects on apple yield and quality.
Precision Agriculture – Springer Journals
Published: Nov 15, 2009
Read and print from thousands of top scholarly journals.
Already have an account? Log in
Bookmark this article. You can see your Bookmarks on your DeepDyve Library.
To save an article, log in first, or sign up for a DeepDyve account if you don’t already have one.
Copy and paste the desired citation format or use the link below to download a file formatted for EndNote
Access the full text.
Sign up today, get DeepDyve free for 14 days.
All DeepDyve websites use cookies to improve your online experience. They were placed on your computer when you launched this website. You can change your cookie settings through your browser.