@article{fdi:010069382,
  title = {{P}redicting stem borer density in maize using {R}apid{E}ye data and generalized linear models},
  author = {{A}bdel-{R}ahman, {E}. {M}. and {L}andmann, {T}. and {K}yalo, {R}. and {O}ng'amo, {G}. and {M}walusepo, {S}. and {S}ulieman, {S}. and {L}e {R}ü, {B}runo},
  editor = {},
  language = {{ENG}},
  abstract = {{A}verage maize yield in eastern {A}frica is 2.03 t ha(-1) as compared to gibbal average of 6.06 t ha(-1) due to biotic and abiotic constraints. {A}mongst the biotic production constraints in {A}frica, stem borers are the most injurious. {I}n eastern {A}frica, maize yield losses due to stem borers are currently estimated between 12% and 21% of the total production. {T}he objective of the present study was to explore the possibility of {R}apid{E}ye spectral data to assess stem borer larva densities in maize fields in two study sites in {K}enya. {R}apid{E}ye images were acquired for the {B}omet (western {K}enya) test site on the 9th of {D}ecember 2014 and on 27th of {J}anuary 2015, and for {M}achakos (eastern {K}enya) a {R}apid{E}ye image was acquired on the 3rd of {J}anuary 2015. {F}ive {R}apid{E}ye spectral bands as well as 30 specttal vegetation indices ({SVI}s) were utilized to predict per field maize stem borer larva densities using generalized linear models ({GLM}s), assuming {P}oisson ('{P}o') and negative binomial ('{NB}') distributions. {R}oot mean square error ({RMSE}) and ratio prediction to deviation ({RPD}) statistics were used to assess the {M}odels performance using a leave one -out cross-validation approach. {T}he {Z}ero-inflated {NB} ('{ZINB}') models outperformed the '{NB}' models and stem borer larva densities could only be predicted during the mid growing season in {D}ecember and early {J}anuary in both study sites, respectively ({RMSE}=0.69-1.06 and {RPD} = 8.25-19.57). {O}verall, all models performed similar when all the 30 {SVI}s (non-nested) and only the significant (nested) {SVI}s were used. {T}he models developed could improve decision making regarding controlling maize stem borers within integrated pest management ({IPM}) interventions.},
  keywords = {{R}apid{E}ye ; {M}aize ; {S}tem borer density ; {G}eneralized linear models ; {A}frica ; {C}rop productivity ; {KENYA}},
  booktitle = {},
  journal = {{I}nternational {J}ournal of {A}pplied {E}arth {O}bservation and {G}eoinformation},
  volume = {57},
  numero = {},
  pages = {61--74},
  ISSN = {0303-2434},
  year = {2017},
  DOI = {10.1016/j.jag.2016.12.008},
  URL = {https://www.documentation.ird.fr/hor/fdi:010069382},
}