Abstract
Integrated pest control is a practice commonly used in apple orchards in southern Brazil. This type of management is an important tool to help improve quality and increase yields. This study aimed to identify areas with higher and lower incidence of aerial pests in a commercial apple orchard, regarding data collected from three different crops using georeferenced traps. Geostatistical analyses were performed, based on the modeling of semivariograms and spatial interpolation using the kriging method; and clustering, based on specific unsupervised machine learning algorithms for count data. The algorithms were selected from measures of stability, connectivity and homogeneity, seeking to identify areas with different incidence of pests that could help farmer decision making regarding insect population control using pesticides. The geostatistical analysis verified the presence of individual pest infestations in specific sites of the study area. Additionally, the analysis using machine learning allowed the identification of areas with incidence above the average for all analyzed pests, especially in the central area of the map. The process of evaluation described in this study can serve as an aid for risk analysis, promoting management benefits and reducing cost in the farms.
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Claims 3
Claim · model-written summary
Geostatistical analysis verified the presence of individual pest infestations in specific sites of the apple orchard.
- Taxon
- apple
Malus domesticae0 - Interactor
- aerial pestse0pest
- Outcome
- presence of individual pest infestationse1
- Qualifier
- in specific sites of the study areae1
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“incidence of aerial pests in a commercial apple orchard”
e1“The geostatistical analysis verified the presence of individual pest infestations in specific sites of the study area”
Claim · model-written summary
Machine-learning clustering identified apple orchard areas with pest incidence above the average for all analyzed pests, especially in the central area.
- Taxon
- appleMalus domesticae0
- Interactor
- analyzed pestse1pest
- Outcome
- areas with incidence above the averagee1
- Qualifier
- especially in the central area of the mape1
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“incidence of aerial pests in a commercial apple orchard”
e1“the analysis using machine learning allowed the identification of areas with incidence above the average for all analyzed pests, especially in the central area of the map”
Claim · model-written summary
The evaluation process can serve as an aid for risk analysis in apple orchards, promoting management benefits and reducing cost on farms.
- Taxon
- appleMalus domesticae0
- Outcome
- an aid for risk analysise1
- Qualifier
- promoting management benefits and reducing cost in the farmse1
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“incidence of aerial pests in a commercial apple orchard”
e1“The process of evaluation described in this study can serve as an aid for risk analysis, promoting management benefits and reducing cost in the farms”