Effects of sample pretreatment and particle size on the determination of nitrogen in soil by portable LIBS and potential use on robotic-borne remote Martian and agricultural soil analysis systems

Yan, Xiaohui; Donaldson, K. M.; Davidson, Christine M.; Gao, Yichun; Wu, Hanling; Houston, Andrew M.; Kisdi, Áron

doi:10.1039/c8ra07065b

Cited by 23 publications

(4 citation statements)

References 49 publications

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“…Many studies have applied LIBS to measure soil carbon content, and these are summarized in the review article by Senesi and Senesi [40]. For soil nitrogen, Yan et al employed a portable LIBS to measure nitrogen in five soils collected from central Scotland, and a good correlation (R 2 = 0.82) between LIBS-predicted and microanalytical content was achieved [41]. Moreover, other nutrient elements in soil, such as K, Ca, Mg, Mn, and Fe, also have been detected using the LIBS technique [42][43][44][45].…”

Section: Introductionmentioning

confidence: 99%

Fast and Simultaneous Determination of Soil Properties Using Laser-Induced Breakdown Spectroscopy (LIBS): A Case Study of Typical Farmland Soils in China

et al. 2019

Soil Syst.

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Accurate management of soil nutrients and fast and simultaneous acquisition of soil properties are crucial in the development of sustainable agriculture. However, the conventional methods of soil analysis are generally labor-intensive, environmentally unfriendly, as well as time- and cost-consuming. Laser-induced breakdown spectroscopy (LIBS) is a “superstar” technique that has yielded outstanding results in the elemental analysis of a wide range of materials. However, its application for analysis of farmland soil faces the challenges of matrix effects, lack of large-scale soil samples with distinct origin and nature, and problems with simultaneous determination of multiple soil properties. Therefore, LIBS technique, in combination with partial least squares regression (PLSR), was applied to simultaneously determinate soil pH, cation exchange capacity (CEC), soil organic matter (SOM), total nitrogen (TN), total phosphorus (TP), total potassium (TK), available phosphorus (AP), and available potassium (AK) in 200 soils from different farmlands in China. The prediction performances of full spectra and characteristic lines were evaluated and compared. Based on full spectra, the estimates of pH, CEC, SOM, TN, and TK achieved excellent prediction abilities with the residual prediction deviation (RPDV) values > 2.0 and the estimate of TP featured good performance with RPDV value of 1.993. However, using characteristic lines only improved the predicted accuracy of SOM, but reduced the prediction accuracies of TN, TP, and TK. In addition, soil AP and AK were predicted poorly with RPDV values of < 1.4 based on both full spectra and characteristic lines. The weak correlations between conventionally analyzed soil AP and AK and soil LIBS spectra are responsible for the poor prediction abilities of AP and AK contents. Findings from this study demonstrated that the LIBS technique combined with multivariate methods is a promising alternative for fast and simultaneous detection of some properties (i.e., pH and CEC) and nutrient contents (i.e., SOM, TN, TP, and TK) in farmland soils because of the extraordinary prediction performances achieved for these attributes.

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Section: Introductionmentioning

confidence: 99%

Fast and Simultaneous Determination of Soil Properties Using Laser-Induced Breakdown Spectroscopy (LIBS): A Case Study of Typical Farmland Soils in China

et al. 2019

Soil Syst.

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“…The AgriRover-Sensing is equipped with a laser induced breakdown spectrometer (LIBS) system for soil sensing and detection of nitrogen. The design and operation of the LIBS system in analysing a soil sample can be found in Yan et al [15]. This paper focuses on the mechatronic aspect of the AgriRover system, i.e.…”

Section: Soil Sample Collection Mechanismmentioning

confidence: 99%

The AgriRover: A Reinvented Mechatronic Platform from Space Robotics for Precision Farming

Yan

Bianco

Niu

et al. 2020

Reinventing Mechatronics

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This paper presents an investigation of a novel development of a multifunctional mobile platform for agriculture applications. This is achieved through a reinvention process of a mechatronic design by spinning off space robotic technologies in terrestrial applications in the AgriRover project. The AgriRover prototype is the first of its kind in exploiting and applying space robotic technologies in precision farming. To optimize energy consumption of the mobile platform, a new dynamic total cost of transport algorithm is proposed and validated. An autonomous navigation system has been developed to enable the AgriRover to operate safely in unstructured farming environments. An object recognition algorithm specific to agriculture-has been investigated and implemented. A novel soil sample collecting mechanism has been designed and prototyped for on-board and in-situ soil quality measurement. The design of the whole system has benefited from the use of a mechatronic design process known as the Tiv model through which a planetary exploration rover is reinvented into the AgriRover for agricultural applications. The Agri-Rover system has gone through three sets of field trials in the UK and some of these results are reported.

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“…In addition to agricultural environments, research focus has been directed and stimulated by extraterrestrial robotic platforms that explore soils on planets such as Mars [28]. Robotically mapped terrestrial agricultural environment parameters that impact net zero include soil nutrition (including N) using advanced laser-induced breakdown spectroscopy (LIBS) sensors [29], moisture using cosmic neutron detectors [30], compaction using penetrometers [27], and more recently spatial carbon dioxide emissions across fields using robot actuated infra-red gas analysers (see Fig. 1A).…”

Section: Introductionmentioning

confidence: 99%

Robotics and Autonomous Systems for Net Zero Agriculture

et al. 2022

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Purpose of Review The paper discusses how robotics and autonomous systems (RAS) are being deployed to decarbonise agricultural production. The climate emergency cannot be ameliorated without dramatic reductions in greenhouse gas emissions across the agri-food sector. This review outlines the transformational role for robotics in the agri-food system and considers where research and focus might be prioritised. Recent Findings Agri-robotic systems provide multiple emerging opportunities that facilitate the transition towards net zero agriculture. Five focus themes were identified where robotics could impact sustainable food production systems to (1) increase nitrogen use efficiency, (2) accelerate plant breeding, (3) deliver regenerative agriculture, (4) electrify robotic vehicles, (5) reduce food waste. Summary RAS technologies create opportunities to (i) optimise the use of inputs such as fertiliser, seeds, and fuel/energy; (ii) reduce the environmental impact on soil and other natural resources; (iii) improve the efficiency and precision of agricultural processes and equipment; (iv) enhance farmers’ decisions to improve crop care and reduce farm waste. Further and scaled research and technology development are needed to exploit these opportunities.

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Effects of sample pretreatment and particle size on the determination of nitrogen in soil by portable LIBS and potential use on robotic-borne remote Martian and agricultural soil analysis systems

Abstract: Measurement of nitrogen in soil using a portable LIBS for potential use on robotic-borne remote Martian and agricultural soil analysis systems.

Cited by 23 publications

References 49 publications

Fast and Simultaneous Determination of Soil Properties Using Laser-Induced Breakdown Spectroscopy (LIBS): A Case Study of Typical Farmland Soils in China

Fast and Simultaneous Determination of Soil Properties Using Laser-Induced Breakdown Spectroscopy (LIBS): A Case Study of Typical Farmland Soils in China

The AgriRover: A Reinvented Mechatronic Platform from Space Robotics for Precision Farming

Robotics and Autonomous Systems for Net Zero Agriculture

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