References
- Aggelopoulou, K.D., Wulfsohn, D., Fountas, S., Gemtos, T.A., Nanos, G.D. and S. Blackmore (2010): Spatial variation in yield and quality in a small apple orchard. Precision Agriculture 11, 538–556.
- Albetis, J., Duthoit, S., Guttler F., Jacquin, A., Goulard, M., Poilvé, P., Féret, J.B. and G. Dedieu (2017): Detection of Flavescence dorée Grapevine Disease Using Unmanned Aerial Vehicle (UAV) Multispectral Imagery. Remote Sensing 9, 308.
- Bietresato, M., Carabin, G., Vidoni, R., Gasparetto, A. and F. Mazzetto (2016): Evaluation of a LiDAR-based 3D-stereoscopic vision system for crop-monitoring applications. Computers and Electronics Agriculture 124, 1–13.
- D’Auria, D., Ristorto, G., Persia, F., Vidoni, R. and F. Mazzetto (2016): Development and preliminary tests of a crop monitoring mobile lab based on a combined use of optical sensors. International Journal of Computer & Software Engineering 1, 103.
- Dias, P.A., Tabb, A. and H. Medeiros (2018): Apple flower detection using deep convolutional networks. Computers in Industry 99, 17–28.
- Di Gennaro, S.F., Battiston, E., Di Marco, S., Facini, O., Matese, A., Nocentini, M., Palliotti, A. and L. Mugnai (2016): Unmanned Aerial Vehicle (UAV)-based remote sensing to monitor grapevine leaf stripe disease within a vineyard affected by esca complex. Phytopathologia Mediterranea 55, 262–275.
- Gallo, R., Ristorto, G., Daglio, G., Massa, N., Berta, G., Lazzari, M. and F. Mazzetto (2017): New solutions for the automatic early detection of diseases in vineyards through ground sensing approaches integrating lidar and optical sensors, Chemical Engineering Transactions 58, 673–678.
- Gongal, A., Karkee, M. and S. Amatya (2018): Apple fruit size estimation using a 3D machine vision system. Information Processing Agriculture 5, 498–503.
- Hočevar, M., Širok, B., Godeša, T. and M. Stopar (2014): Flowering estimation in apple orchards by image analysis. Precision Agriculture 15, 466–478.
- Maharlooei, M., Sivarajan, S., Nowatzki, J., Bajwa, S.G. and H. Kandel (2014): Evaluation of in-field sensors to monitor nitrogen status in soybean crops. 12th International Conference on Precision Agriculture, 20–23 July 2014, Sacramento, California, International Society of Precision Agriculture.
- Ristorto, G., Gallo, R., Gasparetto, A., Scalera, L., Vidoni, R. and F. Mazzetto (2017): A mobile laboratory for orchard health status monitoring in precision farming. Chemical Engineering Transactions 58, 661–666.
- Rosell, J.R, Llorens, j., Sanz, R., Arnó, J., Ribes-Dasi, M., Masip, J., Escolá, A., Camp, F., Solanelles, F., Gràcia, F., Gil, E., Val, L., Planas, S. and J. Palacin (2009): Obtaining the three-dimensional structure of tree orchards from remote 2D terrestrial LIDAR scanning. Agricultural and Forest Meteorology 149, 1505–1515.
- Xiao, C., Zheng, L., Sun, H., Zhang, Y. and M. Li (2014): Estimation of the apple flowers based on aerial multi-spectral image. American Society of Agricultural and Biological Engineers, Paper No. 141912593.