Development of mobile apps for agroenvironmental research


Cassandra is active in the development of apps for mobile devices (smartphones and tablets) targeting the estimation of variables of interest for agroenvironmental research. The apps are aimed at providing scientists, technicians and farmers with low-cost products for the analysis and management of cropping systems. The design is driven by two main requirements: (i) achieving the highest usability and (ii) providing users with advanced functionalities and supporting tools (e.g., for sample size determination and for exporting data in GIS format).

A brief description of the apps is provided here, although further details are available in the dedicated app pages.

PocketLAI (Confalonieri et al., 2013) is an app for leaf area index (LAI) estimates, based
- on the use of the device accelerometer and camera to automatically acquire frames at 57°C below the canopy while the user is rotating the device along its main axes, and
- on automatic segmentation algorithms to derive the gap franction, in turn used to derive LAI.
The app demonstrated its reliability on a variety of herbaceous species and on grasslands (Confalonieri et al., 2013; Francone et al., 2014), providing trueness and precision (repeatability and reproducibility) comparable to commercial instruments. Extensive tests are being performed for tree species, and preliminary results - after the development of specific measurement protocols - demonstrated the app suitability for most canopy structures, regardless of leaf size, and of canopy height and shape.

PocketVJ implements the Visual Jackkinfe method (Confalonieri, 2014; Confalonieri et al., 2006, 2009) for sample size determination in cases when classical (parametric) techniques cannot be applied (e.g., normality and/or homoschedasticity assumptions violated).
PocketLAI can be used alone (thus representing the mobile version of the SISSI desktop application) or - if other apps from the same family (e.g., PocketLAI) are installed on the same device - used as a supporting tool integrated in the graphical user interface of the others.
A beta version of the app is currently available

PocketN is an app for the estimation of plant nitrogen concentration in herbaceous species. The app - that provided satisfying results in an extensive comparative study with some commercial devices - is currently in its alpha version, and will be released in 2015.

References:

Confalonieri, R., 2004. A jackknife-derived visual approach for sample size determination. Italian Journal of Agrometeorology, 1, 9-13.

Confalonieri, R., Stroppiana, D., Boschetti, M., Gusberti, D., Bocchi, S., Acutis, M., 2006. Analysis of rice sample size variability due to development stage, nitrogen fertilization, sowing technique and variety using the visual jackknife. Field Crops Research, 97, 135-141.

Confalonieri, R., Acutis, M., Bellocchi, G., Genovese, G., 2007. Resampling-based software for estimating optimal sample size. Environmental Modelling & Software, 22, 1796-1800.

Confalonieri, R., Perego, A., Chiodini, M.E., Scaglia, B., Rosenmund, A.S., Acutis, M., 2009. Analysis of sample size for variables related to plant, soil, and soil microbial respiration in a paddy rice field. Field Crops Research, 113, 125-130.

Confalonieri, R., Foi, M., Casa, R., Aquaro, S., Tona, E., Peterle, M., Boldini, A., De Carli, G., Ferrari, A., Finotto, G., Guarneri, T., Manzoni, V., Movedi, E., Nisoli, A., Paleari, L., Radici, I., Suardi, M., Veronesi, D., Bregaglio, S., Cappelli, G., Chiodini, M.E., Dominoni, P., Francone, C., Frasso, N., Stella, T., Acutis, M., 2013. Development of an app for estimating leaf area index using a smartphone. Trueness and precision determination and comparison with other indirect methods. Computers and Electronics in Agriculture, 96, 67-74.

Francone, C., Pagani, V., Foi, M., Cappelli, G., Confalonieri, R., 2014. Comparison of leaf area index estimates by ceptometer and PocketLAI smart app in canopies with different structures. Field Crops Research, 155, 38-41.

2016 - Remote Sensing, 8, 202-17
Multitemporal monitoring of plant area index in the Valencia rice district with PocketLAI.
Campos-Taberner, M., García-Haro, J., Confalonieri, R., Martínez, B., Moreno, Á., Sánchez-Ruiz, S., Gilabert, M.A., Camacho, F., Boschetti, M., Busetto, L.

2015 - Biosystems Engineering, 135, 21-30
Improving in vivo plant nitrogen content estimates from digital images: trueness and precision of a new approach as compared to other methods and commercial devices
Confalonieri, R., Paleari, L., Movedi, E., Pagani, V., Orlando, F., Foi, M., Barbieri, M., Pesenti, M., Cairati, O., La Sala, M.S., Besana, R., Minoli, S., Bellocchio, E., Croci, S., Mocchi, S., Lampugnani, F., Lubatti, A., Quarteroni, A., De Min, D., Signorelli, A., Ferri, A., Ruggeri, G., Locatelli, S., Bertoglio, M., Dominoni, P., Bocchi, S., Sacchi, G.A., Acutis, M.

2015 - Applied Vegetation Science, in press
Estimating leaf area index in tree species using the PocketLAI smart app
Orlando, F., Movedi, E., Paleari, L., Gilardelli, C., Foi, M., Dell'Oro, M., Confalonieri, R.

2014 - Field Crops Research, 155, 38-41
Comparison of leaf area index estimates by ceptometer and PocketLAI smart app in canopies with different structures.
Francone, C., Pagani, V., Foi, M., Cappelli, G., Confalonieri, R.

2013 - Computers and Electronics in Agriculture, 96, 67-74
Development of an app for estimating leaf area index using a smartphone. Trueness and precision determination and comparison with other indirect methods.
Confalonieri, R., Foi, M., Casa, R., Aquaro, S., Tona, E., Peterle, M., Boldini, A., De Carli, G., Ferrari, A., Finotto, G., Guarneri, T., Manzoni, V., Movedi, E., Nisoli, A., Paleari, L., Radici, I., Suardi, M., Veronesi, D., Bregaglio, S., Cappelli, G., Chiodini, M.E., Dominoni, P., Francone, C., Frasso, N., Stella, T., Acutis, M.