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AgriEngineering, Volume 7, Issue 8

2025 August - 28 articles

Cover Story: Monitoring nitrogen fertilization using field spectroscopy presents several advantages: the technique is non-destructive and offers rapid analysis, cost-effectiveness, and environmental sustainability, among other benefits. An analysis of the reflectance data of maize leaves revealed the wavelengths most sensitive to the nitrogen availability: 555 nm and 720 nm during the vegetative stage and 680 nm during the reproductive stage. Furthermore, this study demonstrated the feasibility of estimating cornstalk nitrate content based on direct reflectance measurements. However, the model’s performance was dependent on the specific dataset and required validation. These results will support the development of drone-mounted multispectral sensors for large-scale monitoring and the design of low-cost sensors for early nitrogen deficiency detection. View this paper
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Articles (28)

  • Article
  • Open Access
2 Citations
2,175 Views
15 Pages

Long-Term Blueberry Storage by Ozonation or UV Irradiation Using Excimer Lamp

  • Yujiro Takano,
  • Daichi Hojo,
  • Kosuke Sato,
  • Noe Inubushi,
  • Chieto Miyashita,
  • Eiichi Inoue and
  • Yuya Mochizuki

Blueberries are in high demand worldwide because of their taste and functional components. However, the shelf life of blueberries is short owing to their perishability and rapid quality deterioration. Therefore, a sterilization technology must be dev...

  • Article
  • Open Access
8 Citations
2,466 Views
31 Pages

A Robust Lightweight Vision Transformer for Classification of Crop Diseases

  • Karthick Mookkandi,
  • Malaya Kumar Nath,
  • Sanghamitra Subhadarsini Dash,
  • Madhusudhan Mishra and
  • Radak Blange

Rice, wheat, and maize are important food grains consumed by most of the population in Asian countries (like India, Japan, Singapore, Malaysia, China, and Thailand). These crops’ production is affected by biotic and abiotic factors that cause d...

  • Article
  • Open Access
3 Citations
2,038 Views
18 Pages

An IoT-Based System for Measuring Diurnal Gas Emissions of Laying Hens in Smart Poultry Farms

  • Sejal Bhattad,
  • Ahmed Abdelmoamen Ahmed,
  • Ahmed A. A. Abdel-Wareth and
  • Jayant Lohakare

It is critical to provide proper environmental conditions in poultry houses to maintain birds’ health, boost productivity, and improve the overall economic viability of the poultry industry. Among the myriad of environmental elements, indoor ai...

  • Article
  • Open Access
1,723 Views
16 Pages

Ear Back Surface Temperature of Pigs as an Indicator of Comfort: Spatial Variability and Its Thermal Implications

  • Taize Calvacante Santana,
  • Cristiane Guiselini,
  • Héliton Pandorfi,
  • Ricardo Brauer Vigoderis,
  • José Antônio Delfino Barbosa Filho,
  • Rodrigo Gabriel Ferreira Soares,
  • Maria de Fátima Araújo Alves,
  • Marco Antonio Silva,
  • Leandro Dias de Lima and
  • João José de Mesquita Sales

This study applied geostatistics to analyze thermal images of the back surface of pigs’ ears (TSO) to understand how spatial temperature variability influences thermoregulation. The objective was to assess TSO variability in pigs housed under t...

  • Article
  • Open Access
1 Citations
1,006 Views
15 Pages

Relationship Between Hyperspectral Data and Amino Acid Composition in Soybean Genotypes

  • Ana Carina da Silva Cândido Seron,
  • Dthenifer Cordeiro Santana,
  • Izadora Araujo Oliveira,
  • Cid Naudi Silva Campos,
  • Larissa Pereira Ribeiro Teodoro,
  • Elber Vinicius Martins Silva,
  • Rafael Felippe Ratke,
  • Fábio Henrique Rojo Baio,
  • Carlos Antonio da Silva Junior and
  • Paulo Eduardo Teodoro

Spectral reflectance of plants can be readily associated with physiological and biochemical parameters. Thus, relating spectral data to amino acid contents in different genetic materials provides an innovative and efficient approach for understanding...

  • Article
  • Open Access
1 Citations
977 Views
20 Pages

Field Spectroscopy for Monitoring Nitrogen Fertilization and Estimating Cornstalk Nitrate Content in Maize

  • Jesús Val,
  • Iván González-Pérez,
  • Enoc Sanz-Ablanedo,
  • Ángel Maresma and
  • José Ramón Rodríguez-Pérez

Evaluating the response of maize crops to different nitrogen fertilization rates is essential to ensure their agronomic, environmental, and economic efficiency. In this study, the spectral information of maize plants subjected to five distinct nitrog...

  • Article
  • Open Access
2 Citations
1,108 Views
17 Pages

Straw Cover and Tire Model Effect on Soil Stress

  • Aldir Carpes Marques Filho,
  • Lucas Santos Santana,
  • Murilo Battistuzzi Martins,
  • Wellingthon da Silva Guimarães Júnnyor,
  • Simone Daniela Sartório de Medeiros and
  • Kléber Pereira Lanças

Heavy machinery degrades agricultural soils, with severity influenced by wheel type, contact area, and soil moisture. Tropical agriculture is characterized by the constant maintenance of straw on the ground. This permanent cover, among other benefits...

  • Technical Note
  • Open Access
1 Citations
988 Views
13 Pages

Design and Testing of Air-Separation-Type Tillage Layer Residual Film Recovery Machines

  • Zechen Xu,
  • Aiping Shi,
  • Mingquan Zhang,
  • Lei Liu,
  • Zhi Zhou and
  • Lijun Ding

Existing residual film recovery machines for the cultivated layer struggle to achieve an efficient separation of plastic film from impurities during operation. To address this challenge, a wind-separation-type residual film recovery machine equipped...

  • Article
  • Open Access
1 Citations
1,755 Views
16 Pages

Cloud-Enabled Multi-Axis Soilless Clinostat for Earth-Based Simulation of Partial Gravity and Light Interaction in Seedling Tropisms

  • Christian Rae Cacayurin,
  • Juan Carlos De Chavez,
  • Mariah Christa Lansangan,
  • Chrischell Lucas,
  • Justine Joseph Villanueva,
  • R-Jay Relano,
  • Leone Ermes Romano and
  • Ronnie Concepcion

Understanding the combined gravi-phototropic behavior of plants is essential for space agriculture. Existing single-axis clinostats and gel-based grow media provide limited simulation fidelity. This study developed a Cloud-enabled triple-axis clinost...

  • Article
  • Open Access
5 Citations
3,597 Views
18 Pages

Hybrid LSTM Method for Multistep Soil Moisture Prediction Using Historical Soil Moisture and Weather Data

  • Deus F. Kandamali,
  • Erin Porter,
  • Wesley M. Porter,
  • Alex McLemore,
  • Denis O. Kiobia,
  • Ali P. Tavandashti and
  • Glen C. Rains

Soil moisture prediction is a key parameter for effective irrigation scheduling and water use efficiency. However, accurate long-term prediction remains challenging, as most existing models excel in short- to medium-term prediction but struggle to ca...

  • Article
  • Open Access
1,580 Views
25 Pages

Crop Identification with Monte Carlo Simulations and Rotation Models from Sentinel-2 Data

  • Andrei Racoviteanu,
  • Andreea Nițu,
  • Corneliu Florea and
  • Mihai Ivanovici

Crop rotation is a well-established practice that helps reduce nutrient depletion and pressure from pests and weeds. At the same time, the use of artificial intelligence tools to recognize crops from satellite multispectral imagery is gaining momentu...

  • Article
  • Open Access
1,919 Views
22 Pages

Different crop production scenarios and crop rotation systems should be investigated with lower greenhouse gas (GHG) intensity levels, with it being possible to reach net-zero GHG emissions from grain production farms. This study was divided into thr...

  • Article
  • Open Access
2 Citations
2,225 Views
18 Pages

Drones have been widely used in precision agriculture to capture high-resolution images of crops, providing farmers with advanced insights into crop health, growth patterns, nutrient deficiencies, and pest infestations. Although several machine and d...

  • Article
  • Open Access
2 Citations
1,641 Views
14 Pages

Systematic Evaluation and Experimental Validation of Discrete Element Method Contact Models for Soil Tillage Simulation

  • Salavat Mudarisov,
  • Ildar Gabitov,
  • Yakov Lobachevsky,
  • Ildar Farkhutdinov and
  • Lyudmila Kravchenko

The discrete element method (DEM), based on particle dynamics, is used to simulate the technological process of soil tillage using agricultural machinery. A key aspect of the DEM for obtaining accurate agrotechnical and energy indicators of soil cult...

  • Article
  • Open Access
1 Citations
1,174 Views
25 Pages

This study proposes CEL-DL-Bagging (Cross-Entropy Loss-optimized Deep Learning Bagging), a multi-model fusion framework that integrates cross-entropy loss-weighted voting with Bootstrap Aggregating (Bagging). First, we develop a lightweight recogniti...

  • Article
  • Open Access
1 Citations
1,974 Views
18 Pages

Waste activated sludge (WAS), a byproduct of livestock wastewater treatment, poses significant disposal challenges due to its low biodegradability and potential environmental impact. Anaerobic digestion (AD) offers a sustainable approach for methane...

  • Article
  • Open Access
3,063 Views
11 Pages

This study investigated the maturity and optimal harvest interval of the ‘Kalinjot’ olive cultivar in the Vlora region. Fruit samples were collected from six randomly selected trees over nine harvest dates at 10-day intervals from Septemb...

  • Article
  • Open Access
1 Citations
1,587 Views
14 Pages

Prediction of Subcutaneous Fat Thickness (SFT) in Pantaneiro Lambs: A Model Based on Adipometer and Body Measurements for Android Application

  • Adrielly Lais Alves da Silva,
  • Marcus Vinicius Porto dos Santos,
  • Marcelo Corrêa da Silva,
  • Hélio Almeida Ricardo,
  • Marcio Rodrigues de Souza,
  • Núbia Michelle Vieira da Silva and
  • Fernando Miranda de Vargas Junior

The increasing adoption of digital technologies in the agriculture sector has significantly contributed to optimizing on-farm routines, especially in data-driven decision-making. This study aimed to develop an application to determine the slaughter p...

  • Article
  • Open Access
5 Citations
2,672 Views
27 Pages

Nitrous oxide (N2O) emissions from agriculture are rising due to increased fertilizer use and intensive farming, posing a major challenge for climate mitigation. This study introduces a novel reinforcement learning (RL) framework to optimize farm man...

  • Article
  • Open Access
1 Citations
1,404 Views
12 Pages

Optimizing Gear Selection and Engine Speed to Reduce CO2 Emissions in Agricultural Tractors

  • Murilo Battistuzzi Martins,
  • Jessé Santarém Conceição,
  • Aldir Carpes Marques Filho,
  • Bruno Lucas Alves,
  • Diego Miguel Blanco Bertolo,
  • Cássio de Castro Seron,
  • João Flávio Floriano Borges Gomides and
  • Eduardo Pradi Vendruscolo

In modern agriculture, tractors play a crucial role in powering tools and implements. Proper operation of agricultural tractors in mechanized field operations can support sustainable agriculture and reduce emissions of pollutants such as carbon dioxi...

  • Article
  • Open Access
1,721 Views
27 Pages

The integration of a real-time image processing system using multiple webcams with a variable rate spraying system mounted on the back of an unmanned tractor presents an effective solution to the labor shortage in agriculture. This research aims to d...

  • Article
  • Open Access
2 Citations
1,606 Views
17 Pages

TOM-SSL: Tomato Disease Recognition Using Pseudo-Labelling-Based Semi-Supervised Learning

  • Sathiyamohan Nishankar,
  • Thurairatnam Mithuran,
  • Selvarajah Thuseethan,
  • Yakub Sebastian,
  • Kheng Cher Yeo and
  • Bharanidharan Shanmugam

In the agricultural domain, the availability of labelled data for disease recognition tasks is often limited due to the cost and expertise required for annotation. In this paper, a novel semi-supervised learning framework named TOM-SSL is proposed fo...

  • Article
  • Open Access
2 Citations
1,543 Views
29 Pages

AIM-Net: A Resource-Efficient Self-Supervised Learning Model for Automated Red Spider Mite Severity Classification in Tea Cultivation

  • Malathi Kanagarajan,
  • Mohanasundaram Natarajan,
  • Santhosh Rajendran,
  • Parthasarathy Velusamy,
  • Saravana Kumar Ganesan,
  • Manikandan Bose,
  • Ranjithkumar Sakthivel and
  • Baskaran Stephen Inbaraj

Tea cultivation faces significant threats from red spider mite (RSM: Oligonychus coffeae) infestations, which reduce yields and economic viability in major tea-producing regions. Current automated detection methods rely on supervised deep learning mo...

  • Article
  • Open Access
1 Citations
2,297 Views
20 Pages

Smart Postharvest Management of Strawberries: YOLOv8-Driven Detection of Defects, Diseases, and Maturity

  • Luana dos Santos Cordeiro,
  • Irenilza de Alencar Nääs and
  • Marcelo Tsuguio Okano

Strawberries are highly perishable fruits prone to postharvest losses due to defects, diseases, and uneven ripening. This study proposes a deep learning-based approach for automated quality assessment using the YOLOv8n object detection model. A custo...

  • Article
  • Open Access
1 Citations
1,282 Views
22 Pages

Spatial Variability in the Deposition of Herbicide Droplets Sprayed Using a Remotely Piloted Aircraft

  • Edney Leandro da Vitória,
  • Luis Felipe Oliveira Ribeiro,
  • Ivoney Gontijo,
  • Fábio Ribeiro Pires,
  • Aloisio José Bueno Cotta,
  • Francisco de Assis Ferreira,
  • Marconi Ribeiro Furtado Júnior,
  • Maria Eduarda da Silva Barbosa,
  • João Victor Oliveira Ribeiro and
  • Josué Wan Der Maas Moreira

In this study, we evaluated the spatial variability in droplet deposition in herbicide applications using a remotely piloted aircraft (RPA) in pasture areas. The investigation was conducted in a square grid (50.0 m × 50.0 m), with 121 sampling...

  • Article
  • Open Access
1,052 Views
25 Pages

In response to the need for separation and utilization of residual film mixtures after transformation of protaetia brevitarsis larvae, a pneumatic drum-sieve-type separator for transforming mixtures of protaetia brevitarsis larvae was designed. First...

  • Article
  • Open Access
2 Citations
2,702 Views
26 Pages

In the era of smart agriculture, accurate identification of plant species is critical for effective crop management, biodiversity monitoring, and the sustainable use of medicinal resources. However, existing deep learning approaches often underperfor...

  • Article
  • Open Access
2 Citations
1,833 Views
20 Pages

Examination of Interrupted Lighting Schedule in Indoor Vertical Farms

  • Dafni D. Avgoustaki,
  • Vasilis Vevelakis,
  • Katerina Akrivopoulou,
  • Stavros Kalogeropoulos and
  • Thomas Bartzanas

Indoor horticulture requires a substantial quantity of electricity to meet crops extended photoperiodic requirements for optimal photosynthetic rate. Simultaneously, global electricity costs have grown dramatically in recent years, endangering the su...

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AgriEngineering - ISSN 2624-7402