New statistical methods for agro-environmental research


Cassandra developed a new statistical method for determining optimum sample size, free from the assumptions of the parametric methods (normality and variance homogeneity) and particularly suitable for agro-environmental researches. The method (Visual Jackknife) is based on the extensive use of re-sampling techniques and can be considered an evolution of the jackknife.
The Visual Jackknife was successfully used to determine optimum sample size for different development stages, nitrogen fertilization levels, sowing technique and varieties based on their effect on plant heterogeneity (Confalonieri et al., 2006). It was also used to analyze changes in sample size in case of different variables (Confalonieri et al., 2009), in light of the different variability observed - in the same field - for plant (carbon and nitrogen concentration and biomass of different organs) and soil (physical properties, organic and mineral nitrogen content, respirometric activity of microbial communities) analyses.
The visual jackknife is made available in the desktop application SISSI (Confalonieri et al., 2007); a simplified version of the method is implemented in the smartphone app PocketVJ.

A protocol for the evaluation of in vivo field methods was recently proposed (Confalonieri et al., 2014), by adapting the ISO 5725 protocol for the validation of analytical methods. The new protocol is based on assumptions that allowed to redefine the concepts of levels, reference material, and inter-laboratory test. The protocol allows assigning a clear and quantitative meaning to words like accuracy, trueness, precision, repeatability and reproducibility, often used - when indirect field methods (e.g., for LAI or nutritional status estimates) are evaluated - without a real attempt to give these terms rigorous and shared meanings.

References:

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., Francone, C., Chiodini, M.E., Cantaluppi, E., Caravati, L., Colombi, V., Fantini, D., Ghiglieno, I., Gilardelli, C., Guffanti, E., Inversini, M., Paleari, L., Pochettino, G.G., Bocchi, S., Bregaglio, S., Cappelli, G., Dominoni, P., Frasso, N., Stella, T., Acutis, M., 2014. Any chance to evaluate in vivo field methods using standard protocols? Field Crops Research, 161, 128-136.

2016 - Ecological Indicators, 67, 807-820
Designing ecological corridors in a fragmented landscape: a fuzzy approach to circuit connectivity analysis.
Pierik, M.E., Dell'Acqua, M., Confalonieri, R., Bocchi, S., Gomarasca, S.

2014 - Field Crops Research, 161, 128-136
Any chance to evaluate in vivo field methods using standard protocols?
Confalonieri, R., Francone, C., Chiodini, M.E., Cantaluppi, E., Caravati, L., Colombi, V., Fantini, D., Ghiglieno, I., Gilardelli, C., Guffanti, E., Inversini, M., Paleari, L., Pochettino, G.G., Bocchi, S., Bregaglio, S., Cappelli, G., Dominoni, P., Frasso, N., Stella, T., Acutis, M.

2013 - Soil Use and Management, 29, 576-585
The development of a methodology using fuzzy logic to assess the performance of cropping systems based on a case study of maize in the Po Valley.
Carozzi, M., Bregaglio, S., Scaglia, B., Bernardoni, E., Acutis, M., Confalonieri, R.

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

2008 - Agrochimica, 52, 71-82
Wet Aggregate Stability Index: precision assessment of Tiulin method trough an inter-laboratory test.
Bocchi, S., Confalonieri, R., Frigeni, S., Morari, F., Patruno, A.

2008 - Food Analytical Methods, 1, 126-135
Expanding horizons in the validation of GMO analytical methods: fuzzy-based expert systems.
Bellocchi, G., Acutis, M., Paoletti, C., Confalonieri, R., Trevisiol, P., Grazioli, E., Delobel, C., Savini, C., Mazzara, M., Van den Eede, G.

2007 - Journal of AOAC INTERNATIONAL, 90, 1432-1438
Analytical Method Performance Evaluation (AMPE) – A software tool for analytical method validation.
Acutis, M., Trevisiol, P., Confalonieri, R., Bellocchi, G., Grazioli, E., van den Eede, G., Paoletti, C.

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

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