## 5 Conclusions  
In this work, we used a digital image processing method to extract the physical characteristics, invariants, and descriptors specific to different pests that, according to our experiments in May to September 2018 (Table 1), are the most common among pepper crops in the state of Zacatecas.  
The digital processing of sticky yellow trap images has been shown to help detect, classify and count different types of pest insects present in crops [11; 19; 20; 21], so there is a need to apply this method in agricultural areas to help entomologists confirm their detections or classifications.  
The SIFT algorithm detected the five genera in images of 17 insects of the species reported in this work with up to 94% accuracy, compared to the image with 5 insects of the species reported, in which an average of 100% accuracy was obtained, suggesting that more insects present in an image increases the accuracy of detection.  
In Table 4, it can be seen that there were similarities in the characteristics between one type of pest and another. This could cause confusion but observing the rest of the characteristics will help to determine the type of pest present.  
One of the most relevant results is the high coefficient of determination, from \(R^{2}=0.69\) to \(R^{2}=0.99\), among the different types of pests analyzed in this study. In the case of themost deficient correlation (_Anthonomus eugenii_), this is due to the minimum number of specimens detected during the experimentation period.  
The proposed method was tested and validated with images of traps containing the insects described in the results and by comparing with the data obtained by an entomologist.  
One of the main drawbacks of the method is the digitization of the traps since they must be scanned under laboratory conditions to avoid contamination.  
To obtain the approximate size of the insect, the digitization of the trap must always be performed with the same distance between the trap and the digitization medium since this characteristic is based on the number of pixels that a square centimeter of the trap occupies, and variation in the distance will affect the precision of this characteristic.  
To try to solve these drawbacks, future work can be done on the structure for digitizing the trap, as well as on the design of the means of transport for the traps to avoid contamination.  
The proposed method was tested and validated with images of traps containing the insects described in the results, but it is not limited to only these genera.  
This method of digital image processing is expected to help entomologists to identify insects present in sticky yellow traps placed on various crops in a timely manner.  
M.M.-L. and C.L.C.-M., investigation; M.M.-L., methodology, data curation, and writing--original draft; G.E.-G., resources and supervision; C.A.O.-O. and H.A.G.-O., writing--review and editing; H.A.G.-O., visualization; L.F.L.-V., A.D.R.-D.S. and M.d.R.M.-B., resources; L.O.S.-S., conceptualization, project administration, data curation, and supervision; L.O.S.-S., agreed to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
Not applicable.  
The authors thank CONACYT for scholarship number 470427, and the National Laboratory CONACYT-SEDEAM. Special thanks to [PERSON] for his valuable support in entomological aspects and teaching on the subject.  
The authors declare no conflict of interest.