A method for the validation of measurements collected by different monitoring systems applied to aquaculture processing plants

Barbaresi, Alberto; Agrusti, Miki; Ceccarelli, Mattia; Bovo, Marco; Tassinari, Patrizia; Torreggiani, Daniele

doi:10.1016/j.biosystemseng.2021.07.011

Cited by 6 publications

(5 citation statements)

References 27 publications

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“…One of the most important metric to monitor is the dissolved oxygen (DO) in the fish tanks. While some probes simply underwent to a validation test [9], the DO failed the validation test and needed a calibrations procedure as explained later.…”

Section: A Simtap Project and Ismacs Systemmentioning

confidence: 99%

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Methodology for sensor calibration in agro-industrial facilities

Barbaresi

Ceccarelli

Agrusti

et al. 2021

2021 IEEE International Workshop on Metrology for Agriculture and Forestry (MetroAgriFor)

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The rising need of precision in several sectors, agriculture included, brings to the development of new monitoring systems customised for the specific application. These systems often take advantages of probes offered by the market, however, the integration between market probes and home-built systems, requires tests to validate the recorded measurements.This paper provides a methodology to perform a calibration procedure when the probes fail the validation test.The results show the comparison of the measurements collected by investigated sensors and reference sensor coupled with the application of simple correlation methods can bring to an improvement of the sensor precision as far as to pass the validation test.

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Section: A Simtap Project and Ismacs Systemmentioning

confidence: 99%

“…A few works proposed methodologies to validate the measurements, [9]- [12] suggesting to compare the measurements recorded by the investigated sensor with a more accurate reference sensor and then calculate an indicator based on the difference between the two measurements [13].…”

Section: Introductionmentioning

confidence: 99%

Methodology for sensor calibration in agro-industrial facilities

Barbaresi

Ceccarelli

Agrusti

et al. 2021

2021 IEEE International Workshop on Metrology for Agriculture and Forestry (MetroAgriFor)

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“…Recently, specific developments proposed solutions to check and monitor several metrics from crop and animal conditions to food quality. Moreover, the possibility to send, receive and store data in real time and the potentialities of big data analysis, allow the precision and efficacy of the monitoring to be enhanced [35][36][37][38]. These systems also determine a dramatic improvement in the accuracy of plant experiments in controlled environments (such as greenhouses), based on the analysis of the spatial and temporal variability/homogeneity of environmental conditions affecting crop development, growth, quantitative and qualitative characteristics.…”

Section: Introductionmentioning

confidence: 99%

Effects of LED supplemental lighting on the growth and metabolomic profile of Taxus baccata cultivated in a smart greenhouse

et al. 2022

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Light emitting diode (LED) lamps are increasingly being studied in cultivation of horticultural, ornamental and medicinal plants as means to increase yield, quality, stress resistance, and bioactive compounds content. Enhancing the production of metabolites for medicinal or pharmaceutical use by regulating LED intensity and spectra is a challenging subject, where promising results have been achieved. Nevertheless, some species have been poorly investigated, despite their interest as a source of medicinally active substances, with particular reference to LED effects at the plant cultivation level. This study evaluates the effects of supplementary top-light LED treatments on Taxus baccata, one of the main sources of taxane precursors. Blue, red and mixed red–and-blue spectra were tested at 100 μM m-2 s-1. Moreover, 50 and 150 μM m-2 s-1 intensities were tested for the mixed spectrum. All treatments were set for 14 hours a day and were tested against natural light as control treatment, in a controlled environment, from 19 August to 9 December 2019, this latter date representing 112 days after treatment (DAT) began. A smart monitoring and control system powered by environmental and proximal sensors was implemented to assure homogeneity of temperature, humidity, and base natural light for all the treatments. It resulted in negligible deviations from expected values and reliable exclusion of confusing factors. Biometric measurements and 1H-NMR based metabolomic analysis were performed to investigate growth and phytochemical profile throughout the trial. One-way ANOVA showed that supplemental LED lighting increased plant height and number of sprouts. Considering the mixed red–and-blue spectrum, plant height increased almost proportionally from control to 100 μM m-2 s-1 (+20% at 112 DAT), with no further increase at higher intensity. The number of sprouts was strongly enhanced by LED treatments only in the early phase (48.9 vs. 7.5 sprouts in the averaged 50, 100 and 150 μM m-2 s-1 vs. the control at 28 DAT), with no differences related to intensity in the very early stage, and more persisting effects (up to 56 DAT) for higher intensities. After the very early growth stages (28 DAT), plant vigor showed a modest although significant increase over time compared to the control, with no differences related to light intensity (0.81 vs. 0.74 of NDVI in the averaged 50, 100 and 150 μM m-2 s-1 vs. the control, across 56, 84 and 112 DAT). The different spectra tested at 100 μM m-2 s-1 showed no significant differences in growth parameters, except for a slight beneficial influence of blue (alone or with red) compared to only red for sprouting. According to the metabolomic analysis, treated plants at 28 DAT were characterized by the highest content of sucrose and aromatic compounds. Signals of a putative taxane were detected in the 1H NMR profiles of plants, which were compared to the spectrum of baccatin III standard. However, the intensity of these spectral signals was not affected by the treatment, while they increased only slightly during time. Light at 150 μM m-2 s-1 induced the strongest variation in the metabolome. Conversely, light composition did not induce significant differences in the metabolome.

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“…For instance, great results have been achieved in water monitoring through the implementation of Internet of Things (IoT) principles [2]. The application of technological innovations in aquaculture, could also improve resources utilization and reduce waste discharge during routine farm operations [3], [4]. Commercial aquafarms goals are to feed fish to maintain desired growth rates and keep feed loss to the environment at a minimum, especially in offshore farms.…”

Section: Introductionmentioning

confidence: 99%

“…Commercial aquafarms goals are to feed fish to maintain desired growth rates and keep feed loss to the environment at a minimum, especially in offshore farms. Moreover, feed cost accounts for about 40-50 percent of running costs and is thus the most significant expense in carnivorous fish production [4]. Since fish are commonly fed with a ratio of feed to fish biomass, aquaculture farmers should precisely quantify the fish biomass and thus the daily dose of feed to be supplied to avoid a reduced fish growth due to underfeeding or an environmental pollution and economic loss due to overfeeding [5], [6].…”

Section: Introductionmentioning

confidence: 99%

Application of a smart dynamic scale for measuring live-fish biomass in aquaculture

Rossi

Bibbiani

Fronte

et al. 2021

2021 IEEE International Workshop on Metrology for Agriculture and Forestry (MetroAgriFor)

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The need of measuring the fish biomass, either for in-land facilities or offshore cages, drove recently to develop a cheap dynamic scale (by MEGA Materials srl), based on a board of the Arduino family, suitable to measure live-fish weights. Via a Bluetooth transmitter and a specific app the communication with smartphones is allowed. The estimation of live-fish biomass is extremely relevant to precisely quantify the daily dose of feed to be supplied and to avoid a reduction of fish growth. We present the comparison between 'static' and 'dynamic' weight measures of seabream juveniles reared in tanks.

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A method for the validation of measurements collected by different monitoring systems applied to aquaculture processing plants

Cited by 6 publications

References 27 publications

Methodology for sensor calibration in agro-industrial facilities

Methodology for sensor calibration in agro-industrial facilities

Effects of LED supplemental lighting on the growth and metabolomic profile of Taxus baccata cultivated in a smart greenhouse

Application of a smart dynamic scale for measuring live-fish biomass in aquaculture

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