Aerial Monitoring of Rice Crop Variables using an UAV Robotic System

This paper presents the integration of an UAV for the autonomous monitoring of rice crops. The system integrates image processing and machine learning algorithms to analyze multispectral aerial imagery. Our approach calculates 8 vegetation indices from the images at each stage of rice growth: vegetative, reproductive and ripening. Multivariable regressions and artificial neural networks have been implemented to model the relationship of these vegetation indices against two crop variables: biomass accumulation and leaf nitrogen concentration. Comprehensive experimental tests have been conducted to validate the setup. The results indicate that our system is capable of estimating biomass and nitrogen with an average correlation of 80% and 78% respectively

Characterization of rice yield based on biomass and SPAD-based leaf nitrogen for large genotype plots

The use of Unmanned Aerial Vehicle (UAV) images for biomass and nitrogen estimation offers multiple opportunities for improving rice yields. UAV images provide detailed, high-resolution visual information about vegetation properties, enabling the identification of phenotypic characteristics for selecting the best varieties, improving yield predictions, and supporting ecosystem monitoring and conservation efforts. In this study, an analysis of biomass and nitrogen is conducted on 59 rice plots selected at random from a more extensive trial comprising 400 rice genotypes. A UAV acquires multispectral reflectance channels across a rice field of subplots containing different genotypes. Based on the ground-truth data, yields are characterized for the 59 plots and correlated with the Vegetation Indices (VIs) calculated from the photogrammetric mapping. The VIs are weighted by the segmentation of the plants from the soil and used as a feature matrix to estimate, via machine learning models, the biomass and nitrogen of the selected rice genotypes. The genotype IR 93346 presented the highest yield with a biomass gain of 10,252.78 kg/ha and an average daily biomass gain above 49.92 g/day. The VIs with the highest correlations with the ground-truth variables were NDVI and SAVI for wet biomass, GNDVI and NDVI for dry biomass, GNDVI and SAVI for height, and NDVI and ARVI for nitrogen. The machine learning model that performed best in estimating the variables of the 59 plots was the Gaussian Process Regression (GPR) model with a correlation factor of 0.98 for wet biomass, 0.99 for dry biomass, and 1 for nitrogen. The results presented demonstrate that it is possible to characterize the yields of rice plots containing different genotypes through ground-truth data and VIs

Aerial Identification of Amazonian Palms in High-Density Forest Using Deep Learning

This paper presents an integrated aerial system for the identification of Amazonian Moriche palm (Mauritia flexuosa) in dense forests, by analyzing the UAV-captured RGB imagery using a Mask R-CNN deep learning approach. The model was trained with 478 labeled palms, using the transfer learning technique based on the well-known MS COCO framework©. Comprehensive in-field experiments were conducted in dense forests, yielding a precision identification of 98%. The proposed model is fully automatic and suitable for the identification and inventory of this species above 60 m, under complex climate and soil conditions

Four-Dimensional Plant Phenotyping Model Integrating Low-Density LiDAR Data and Multispectral Images

High-throughput platforms for plant phenotyping usually demand expensive high-density LiDAR devices with computational intense methods for characterizing several morphological variables. In fact, most platforms require offline processing to achieve a comprehensive plant architecture model. In this paper, we propose a low-cost plant phenotyping system based on the sensory fusion of low-density LiDAR data with multispectral imagery. Our contribution is twofold: (i) an integrated phenotyping platform with embedded processing methods capable of providing real-time morphological data, and (ii) a multi-sensor fusion algorithm that precisely match the 3D LiDAR point-cloud data with the corresponding multispectral information, aiming for the consolidation of four-dimensional plant models. We conducted extensive experimental tests over two plants with different morphological structures, demonstrating the potential of the proposed solution for enabling real-time plant architecture modeling in the field, based on low-density LiDARs

Aerial Identification of Amazonian Palms in High-Density Forest Using Deep Learning

This paper presents an integrated aerial system for the identification of Amazonian Moriche palm (Mauritia flexuosa) in dense forests, by analyzing the UAV-captured RGB imagery using a Mask R-CNN deep learning approach. The model was trained with 478 labeled palms, using the transfer learning technique based on the well-known MS COCO framework©. Comprehensive in-field experiments were conducted in dense forests, yielding a precision identification of 98%. The proposed model is fully automatic and suitable for the identification and inventory of this species above 60 m, under complex climate and soil conditions

Optimal Deployment of WSN Nodes for Crop Monitoring Based on Geostatistical Interpolations

This paper proposes an integrated method for the estimation of soil moisture in potato crops that uses a low-cost wireless sensor network (WSN). Soil moisture estimation maps were created by applying the Kriging technique over a WSN composed of 11×11 nodes. Our goal is to estimate the soil moisture of the crop with a small-scale WSN. Using a perfect mesh approach on a potato crop, experimental results demonstrated that 25 WSN nodes were optimal and sufficient for soil moisture characterization, achieving estimations errors <2%. We provide a strategy to select the number of nodes to use in a WSN, to characterize the moisture behavior for spatio-temporal analysis of soil moisture in the crop. Finally, the implementation cost of this strategy is shown, considering the number of nodes and the corresponding margin of error

Stabliization of excess charge in isolated adenosine 5'-triphosphate and adenosine 5'-diphosphate multiply and singly charged anions

Multiply charged anions (MCAs) represent highly energetic species in the gas phase but can be stabilized through formation of molecular clusters with solvent molecules or counterions. We explore the intramolecular stabilization of excess negative charge in gas-phase MCAs by probing the intrinsic stability of the [adenosine 5‘-triphosphate-2H]2- ([ATP-2H]2-), [adenosine 5‘-diphosphate-2H]2- ([ADP-2H]2-), and H3P3O102- dianions and their protonated monoanionic analogues. The relative activation barriers for decay of the dianions via electron detachment or ionic fragmentation are investigated using resonance excitation of ions isolated within a quadrupole trap. All of the dianions decayed via ionic fragmentation demonstrating that the repulsive Coulomb barriers (RCB) for ionic fragmentation lie below the RCBs for electron detachment. Both the electrospray ionization mass spectra (ESI-MS) and total fragmentation energies for [ATP-2H]2-, [ADP-2H]2-, and H3P3O102- indicate that the multiply charged H3P3O102- phosphate moiety is stabilized by the presence of the adenosine group and the stability of the dianions increases in the order H3P3O102- < [ADP-2H]2- < [ATP-2H]2-. Fully optimized, B3LYP/6-31+G* minimum energy structures illustrate that the excess charges in all of the phosphate anions are stabilized by intramolecular hydrogen bonding either within the phosphate chain or between the phosphate and the adenosine. We develop a model to illustrate that the relative magnitudes of the RCBs and hence the stability of these ions is dominated by the extent of intramolecular hydrogen bonding

Research, Innovation and Extension to the service to society, in the framework of the Sixth Conference on Social Appropriation of Knowledge (SAK)

Annually, the Technological University of Pereira has been carrying out some events in the line of Social Appropriation of Knowledge. This has been done through the research, innovation, and extension Vice Rectory, moreover, these sessions are framed within the institutional objective: “Define and direct the guidelines for the institutional research that strengthen the research groups and the Seedbeds, through the formation of researchers, the development of science, technology, and innovation projects or programs, as well as the generation of networks and strategic partnerships that contribute to the creation and appropriation of knowledge for the society”. Therefore, the 6th Social Appropriation of Knowledge event took place under the title of “The research, Innovation, and Extension at the service of society” which was constituted as an academic and institutional opportunity where the results of the research projects from the last 5 years were published. The results of this event revealed, once again, the high academic level in investigation development at the university. There were 11 articles divided into 6 fields: Health, Engineering, Technology, Education, Industrial Technology, and Art, in which the results obtained by the research projects from the investigation groups were shown, promoting a knowledge exchange from their authors whose intellectual formation is diverse. With this publication, as part of a permanent effort to socialize the knowledge, the university promotes the circulation of its professors, students, and general community voices, having in mind that knowledge must be transferred through different channels, strengthening the academy and society in general, according to the institutional mission that invites us to incentivize a research culture in the university community.Presentation........................................................................................................... 5 Chapter 1. Health Teaching during the pandemic: what changes did professors implement? Results of a survey in a Colombian medical program. ........................................... 9 Germán Alberto Moreno Gómez ,Rodolfo Adrián Cabrales Vega, Jairo Franco Londoño, Samuel Eduardo Trujillo Henao, Víctor Manuel Patiño Suárez Evaluation of the effectiveness of a rat, rabbit and human intestine decellularization protocol...................................................................................... 19 Julio César Sánchez Naranjo, Laura Victoria Muñoz Rincón, Andrés Felipe Quiroz Ma zuera, Andrés Mauricio García Cuevas, Cristhian David Arroyave Durán, Fabián David Giraldo Castaño, Álvaro Guerra Solarte, Juliana Buitrago Jaramillo Exploration of the filtering functions of the intestine through a filtering loop model: an experimental approach towards a feasible renal replacement.............. 31 Julio César Sánchez Naranjo, Laura Victoria Muñoz Rincón, Andrés Mauricio García Cuevas, Álvaro Guerra Solarte y Juliana Buitrago Jaramillo Chapter 2. Engineering Identification of sociodemographic factors using multivariate analysis related to the dropout of Universidad Tecnológica de Pereira undergraduate students.... 47 Nelcy N Atehortua-Sanchez, Paula Marcela Herrera, Julian D Echeverry Correa Design and Construction of an HVDC-MMC Terminal on a Low Scale to Interconnection of Windfarms to the Electrical Grid........................................ 61 Diego Alberto Montoya Acevedo, Andrés Escobar Mejía Chapter 3. Technologies Preliminary study of cytototoxic and bactericidal activities of nonpolar extracts from seeds and peel of Persea americana cv Lorena ............................................ 85 Gloria Edith Guerrero Alvarez, Daniel Steven Fernández, Daniela Londoño Ramirez Cytototoxic and bactericidal activities of nonpolar extracts from seeds and peel of Persea americana cv Hass..................................................................................... 95 Gloria Edith Guerrero Alvarez, Gustavo Alfonso Cifuentes Colorado, Paula Daniela Sandoval Mossos Chapter 4. Education Pedro Henríquez Ureña traveler and Cosmopolitan ........................................... 107 William Marín Osorio Reading and writing in the training of our teachers: a commitment of all ......... 133 María Gladis Agudelo Gil, Gloria Inés Correa Aristizábal Chapter 5. Industrial engineering Tasks design to promote metacognitive regulation in discrete event simulation ......................................................................................................... 151 María Elena Bernal Loaiza, Manuela Gómez Suta, Rosario Iodice CONTENIDO Chapter 6. Arts The media feuilleton, between fiction and reality............................................... 169 Teresita Vásquez Ramíre