Cassava NDVI Analysis: A Nonlinear Mixed Model Approach Based on UAV-Imagery

Author(s):  
D. Grados ◽  
E. Schrevens
Author(s):  
Lauri Kortelainen ◽  
Jouni Helske ◽  
Taija Finni ◽  
Lauri Mehtätalo ◽  
Olli Tikkanen ◽  
...  

Toxins ◽  
2021 ◽  
Vol 13 (3) ◽  
pp. 214
Author(s):  
Agathe Roucou ◽  
Christophe Bergez ◽  
Benoît Méléard ◽  
Béatrice Orlando

The levels of fumonisins (FUMO)—mycotoxins produced by Fusarium verticillioides—in maize for food and feed are subject to European Union regulations. Compliance with the regulations requires the targeting of, among others, the agroclimatic factors influencing fungal contamination and FUMO production. Arvalis-Institut du végétal has created a national, multiyear database for maize, based on field survey data collected since 2003. This database contains information about agricultural practices, climatic conditions and FUMO concentrations at harvest for 738 maize fields distributed throughout French maize-growing regions. A linear mixed model approach highlights the presence of borers and the use of a late variety, high temperatures in July and October, and a water deficit during the maize cycle as creating conditions favoring maize contamination with Fusarium verticillioides. It is thus possible to target a combination of risk factors, consisting of this climatic sequence associated with agricultural practices of interest. The effects of the various possible agroclimatic combinations can be compared, grouped and classified as promoting very low to high FUMO concentrations, possibly exceeding the regulatory threshold. These findings should facilitate the creation of a national, informative and easy-to-use prevention tool for producers and agricultural cooperatives to manage the sanitary quality of their harvest.


2004 ◽  
Vol 83 (8) ◽  
pp. 1253-1259 ◽  
Author(s):  
R.L. Sapp ◽  
R. Rekaya ◽  
I. Misztal ◽  
T. Wing

2021 ◽  
pp. 101857
Author(s):  
Karen Melissa Polanco Zuleta ◽  
Marina Medina-Corrales ◽  
Franciso Javier Mendoza-Farías ◽  
Claudia Cristina Santos Lozano ◽  
José Tristán ◽  
...  

2016 ◽  
Vol 64 (2) ◽  
pp. 163-167
Author(s):  
Tahmidul Islam ◽  
Md Golam Rabbani ◽  
Wasimul Bari

Child malnutrition is a serious issue for overall child health and future development. Stunting is a key anthropometric indicator of child malnutrition. Because of the nature of sampling design used in Bangladesh Demographic Health Survey, 2011, responses obtained from children under same family might be correlated. Again, children residing in same cluster may also be correlated. To tackle this problem, generalized linear mixed model (GLMM), instead of usual fixed effect logistic regression model, has been utilized in this paper to find out potential factors affecting child malnutrition. Model performances have also been compared. Dhaka Univ. J. Sci. 64(2): 163-167, 2016 (July)


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