Proximal Sensing Sensors for Monitoring Crop Growth

Hallik, Lea; Šarauskis, Egidijus; Kazlauskas, Marius; Bručienė, Indrė; Mozgeris, Gintautas; Steponavičius, Dainius; Tõrra, Toomas

doi:10.1007/978-3-030-84144-7_3

Cited by 4 publications

(6 citation statements)

References 72 publications

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“…Many agricultural sensors and tools are available to assess spatial crop, soil and weather data (Kassim, Mat, and Harun 2014;Kumar and Ilango 2018;Srikanth, Chakraborty, and Murthy 2021;Yin et al 2021;Hallik et al 2022). These in situ and on-the-go sensors are: LIDAR and RADAR sensors (Esch et al 2018); UAV drones (Inoue 2020;Awais et al 2022); electromagnetic induction (EMI) sensor; airborne imageries (Tack et al 2019); hyperspectral sensing systems (Jin et al 2019) and field sensors (Svotwa et al 2013).…”

Section: Components Of Site-specific Crop Managementmentioning

confidence: 99%

“…EC meter can be used to establish ECa zones based on soil chemical properties (De Assis Silva et al 2022). Proximal soil sensors monitoring crop growth and development used for spatial mapping (Hallik et al 2022). Soil spectrophotometer to measure soil properties such as moisture, organic matter, NO 3 -N, pH and ECa (Wijaya et al 2001).…”

Section: Field Management Zones Developmental Procedures and Referencesmentioning

confidence: 99%

“…For SSCM, monitoring spatial crop, soil and weather data is very crucial. This becomes feasible thanks to GNSS-based technologies, GPS mounted crop harvesters, crop and soil sensing systems and digital sensors (Long et al 2016;Jin et al 2019;Liu et al 2021;Perez-Ruiz, Martínez-Guanter, and Upadhyaya 2021;Srikanth, Chakraborty, and Murthy 2021;Yin et al 2021;Awais et al 2022;Hallik et al 2022).…”

mentioning

confidence: 99%

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Broad Scope of Site‐Specific Crop Management and Specific Role of Remote Sensing Technologies Within It—A Review

Ali,

Hassan,

Kaul

2024

J Agronomy Crop Science

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Precision agriculture (PA) has great potential to increase agricultural productivity and profitability while reducing input costs and environmental impacts. Within PA, site‐specific crop management (SSCM) is considered the main premise, in which tillage operations and precise crop inputs (such as seed, fertiliser, water, pesticide and agrochemical) are applied according to field variability. The main aim of this review was to highlight the methods and tools used for spatial crop monitoring, soil and weather data influencing crop productivity and to support the adoption of SSCM technology. To achieve this goal: we discussed the main five components of SSCM, methods for monitoring crop and soil data, delineating field management zones (FMZs) and variable rate technologies (VRT) such as precision planting and digital smart sensors used for SSCM application. The review summarised that recent advances in plant and soil sensing systems, artificial intelligence (AI) and machine learning should be used in retrieving and analysing GIS big data for optimised crop inputs supply. Within VRT, light‐bar systems, automatic controllers and sensors are user‐friendly technologies that should be employed in SSCM solution. The authors highlight that adoption of PA can be increased through proper training and education of the farmers, and developing simple, affordable and efficient PA technologies. The review suggests five criteria that should be strictly adopted to get maximum benefits from SSCM: (i) all factors influencing crop yields can be identified; (ii) their effects on crop yields can be determined by using appropriate digital tools and crop modelling; (iii) variable rate crop inputs (VRCIs) should be calculated based on accurate information obtained from plant, soil and environment; (iv) targeted crop inputs should be exercised through global positioning system (GPS) enabled automatic controllers or wireless sensors network (WSN); and (v) right doses of crop inputs (e.g., nitrogen and irrigation) must be applied at the right time and place.

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Section: Components Of Site-specific Crop Managementmentioning

confidence: 99%

Section: Field Management Zones Developmental Procedures and Referencesmentioning

confidence: 99%

mentioning

confidence: 99%

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Broad Scope of Site‐Specific Crop Management and Specific Role of Remote Sensing Technologies Within It—A Review

Ali,

Hassan,

Kaul

2024

J Agronomy Crop Science

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“…The current state of the art in agricultural robotics includes crop monitoring [7], weed control [8,9], harvesting [10,11], and post-harvesting [12]. Robots are utilized for a variety of agricultural tasks, including soil monitoring [13], seeding [14], seedling manipulation [15], fertilization [16], irrigation [17], and crop protection [18,19]. These technologies enable efficient and accurate crop monitoring, allowing for timely interventions to promote optimal growth.…”

Section: Introductionmentioning

confidence: 99%

Mobile Robot System for Selective Asparagus Harvesting

2023

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Asparagus harvesting presents unique challenges, due to the variability in spear growth, which makes large-scale automated harvesting difficult. This paper describes the development of an asparagus harvesting robot system. The system consists of a delta robot mounted on a mobile track-based platform. It employs a real-time asparagus detection algorithm and a sensory system to determine optimal harvesting points. Low-level control and high-level control are separated in the robot control. The performance of the system was evaluated in a laboratory field mock-up and in the open field, using asparagus spears of various shapes. The results demonstrate that the system detected and harvested 88% of the ready-to-harvest spears, with an average harvesting cycle cost of 3.44s±0.14s. In addition, outdoor testing in an open field demonstrated a 77% success rate in identifying and harvesting asparagus spears.

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“…Soil monitoring robots help assess soil quality, moisture levels, and nutrient content, providing essential data to optimize fertilization and irrigation strategies [40]. Seed planting and seedling manipulation robots guarantee precise and consistent planting, promoting strong and healthy plant growth [41,42]. Furthermore, robots are actively involved in the fertilization process, delivering nutrients in a targeted and efficient manner [43][44][45].…”

Section: Introductionmentioning

confidence: 99%

Designing and Implementing a Versatile Agricultural Robot: A Vehicle Manipulator System for Efficient Multitasking in Farming Operations

2023

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This paper presents a detailed design of a skid-steering mobile platform with four wheels, along with a Cartesian serial (PPP) manipulator. The aim of this design is to enable the platform to perform various tasks in the agricultural process. The parallel manipulator designed can handle heavy materials in the agricultural field. An experimental robotic harvesting scenario was conducted using parallel manipulator-based end-effectors to handle heavy fruits such as watermelon or muskmelon. The conceptual and component design of the different models was carried out using the Solidworks modeling package. Design specifications and parametric values were utilized during the manufacturing stage. The mobile manipulator was simulated on undulating terrain profiles using ADAMS software. The simulation was analyzed for a duration of 15 s, and graphs depicting the distance, velocity, and acceleration were evaluated over time. Proportional derivative control and proportional derivative-like conventional sliding surface control were applied to the model, and the results were analyzed to assess the error in relation to the input and desired variables. Additionally, a structural analysis was performed to ensure minimal deformation and the highest safety factor for the wheel shaft and L bracket thickness. Throughout the fabrication and prototype development, calibration tests were conducted at various X-, Y-, and Z-axis frame mounting stages. The objective was to minimize the lateral and longitudinal deviation between the parallel linear motion (LM) rails. Once the fabrication and prototype construction was completed, field testing was carried out. All mechanical movements in the lateral and longitudinal directions functioned according to the desired commands given by the Arduino Mega, controlled via a six-channel radio frequency (RF) controller. In the context of agriculture, the grippers utilizing parallel mechanisms were also subjected to testing, demonstrating their ability to handle sizable cylindrical and spherical fruits or vegetables, as well as other relevant objects.

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Proximal Sensing Sensors for Monitoring Crop Growth

Cited by 4 publications

References 72 publications

Broad Scope of Site‐Specific Crop Management and Specific Role of Remote Sensing Technologies Within It—A Review

Broad Scope of Site‐Specific Crop Management and Specific Role of Remote Sensing Technologies Within It—A Review

Mobile Robot System for Selective Asparagus Harvesting

Designing and Implementing a Versatile Agricultural Robot: A Vehicle Manipulator System for Efficient Multitasking in Farming Operations

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