MAPIR Research Publications

MAPIR offers solutions that are commonly used by customers in the research community. Below you can find a selection of papers using our products (click to view).

Over time we continue to improve our solution so the newer publications may contain better results. Notably our software processing was greatly improved in Q4 2022, and our spectrometer light sensor was introduced in Q4 2023. The use of our calibration targets and ambient light sensor are required for the most accurate results.


(2024) Use of different vegetation indices for the evaluation of the kinetics of the cherry tomato (Solanum lycopersicum var. cerasiforme) growth based on multispectral images by UAV

"The vegetation indices obtained from drone imagery were used to create spatial maps of plant growth. These maps can be used for accurately identifying stressed or infected plant areas, targeting fertilizer, pesticide, and irrigation applications precisely where needed, reducing waste,and increasing efficiency."


(2024) Rice Leaf Nitrogen Content Estimation Through A Methodological Framework Using Single-Sensor Multispectral Images


(2024) Modelling Chlorophyll and Nutrient Contents of Peperomia obtusifolia ‘Green Gold’ Using MAPIR RGN and RGB Sensors


(2024) A Cutting-Edge Precision Agriculture Technology to Support the Sustainable Oil Palm Industry

"The UAV and Mapir camera have potentially been utilized to estimate the N, P, K, and Mg content of the leaves and to monitor the nutritional status of the leaves after fertilizing. By generating data from the field quickly and precisely, crop production inputs can be managed in an environmentally friendly way, which is fundamental to sustainability in oil palm plantations."


(2023) Feasibility of Early Yield Prediction per Coffee Tree Based on Multispectral Aerial Imagery: Case of Arabica Coffee Crops in Cauca-Colombia

"The manual data collection process is very expensive, both in terms of time and money.The multispectral image approach to facilitate manual collection of crop yield data is one of the contributions of this research."


(2023) USO DE IMAGENS DE ALTA RESOLUÇÃO ESPACIAL PARA A ANÁLISE QUÍMICA DA UVA

(2023) USE OF HIGH SPATIAL RESOLUTION IMAGES FOR THE CHEMICAL ANALYSIS OF GRAPES

"Os resultados obtidos no presente estudo são promissorese apresentam uma nova forma de avaliação da viticultura nosemiárido, com uso de imagens centimétricas e de técnicascomputacionais no processamento e obtenção de informaçõesuteis para a gestão da produção de frutíferas."

"The results obtained in this study are promising and present a new way of evaluating viticulture in the semi-arid region, using centimetric images and computational techniques in the processing and obtaining of useful information for the management of fruit production."


(2023) Multispectral images for discrimination of sources and doses of fertilizer in coffee plants

"With a higher accuracy to analyze the agronomic parameters, the use of multispectral images for classification and monitoring of the crop constitutes a low-cost option for large-scale, reliable, and constant monitoring of the crop, reaching up to 86.66% of global accuracy in the RGN data classification and vegetation indices using the Randon Forest algorithm."


(2023) Analysis of Vegetation Index of Oil Palm Plants infected with Ganoderma Disease

"All the results of the analysis of NDVI, GNDVI, and SAVI on healthy oil palm plants, consistently have high values and decrease in line with the level of infection..."


(2023) Proportions of Green Area and Tree Health on University Campus: The Impact of Pavement Presence


(2022) Early Detection of Coffee Leaf Rust Caused by Hemileia vastatrix Using Multispectral Images

"This study demonstrates the potential of using multispectral images to monitor early-stage infection of coffee plants by H. vastatrix, the most important pathogen of coffee plants worldwide, using an unmanned aerial vehicle (UAV). The early detection of this pathogen in the field with low-cost technology can be an important tool for the monitoring of coffee leaf rust and, consequently, a more sustainable management of this pathogen, making applications of chemical fungicides only when necessary."


(2022) Commercially available unoccupied aerial systems for monitoring harmful algal blooms: A comparative study


(2022) Estimation of Paddy Leaf Nitrogen Status using a Single Sensor Multispectral Camera


(2022) Simulating a Hybrid Acquisition System for UAV Platforms


(2021) Estimation of biometric, physiological, and nutritional variables in lettuce seedlings using multispectral images


(2021) Detection of Lesions in Lettuce Caused by Pectobacterium carotovorum Subsp. carotovorum by Supervised Classification Using Multispectral Images


(2019) Spectral Vegetation Index Sensor Evaluation for Greenhouse Precision Agriculture


(2018) UAV Mapping of an Archaeological Site Using RGB and NIR High-Resolution Data