Development and evaluation of a novel system for monitoring harvest labor efficiency

Ampatzidis, Yiannis; Whiting, Matthew; Scharf, Patrick A.; Zhang, Qin

doi:10.1016/j.compag.2012.06.009

Cited by 16 publications

(6 citation statements)

References 16 publications

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“…The collected data can be transmitted wirelessly to the server in real-time with an internet or GPRS connection. A detailed description of a LMS is given in Ampatzidis et al (2012b) and of a PLMS in (Ampatzidis and Whiting, 2014). A computational unit CU was developed to collect data from the sensors (RFID reader, GPS, weighing system), process and wirelessly transmit them to the cloud-based harvest management software.…”

Section: Portable Labor Monitoring Systems (Plms)mentioning

confidence: 99%

“…Regardless, paying piece-rate (pay pickers per full of fruit buckets or bins, assuming that their weights are similar; but might be under-or overfilled) is beset with inaccuracies that cause significant financial losses. Tests in commercial sweet cherry, apple and blueberry orchards revealed variability of 25 -30% of final weight among bins and buckets (Ampatzidis et. al, 2012;.…”

Section: Introductionmentioning

confidence: 99%

“…Real-time novel Labor Monitoring System (LMS) (CU= computational unit, RFID=radio frequency identification)(Ampatzidis et al, 2012b).…”

mentioning

confidence: 99%

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Cloud-based harvest management information system for hand-harvested specialty crops

Ampatzidis

Tan

Haley

et al. 2016

Computers and Electronics in Agriculture

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The harvest process for specialty crops is generally one of intensive activity because many people are required for harvest and packing, and the harvest window is brief due to the high perishability of the produce. Herein we present a cloud-based Harvest Management Information System (HMIS) that combines a novel real-time Portable Labor Monitoring System (PLMS) with a cloud-based harvest management software. The PLMS comprised of three key elements (1) a self-leveling scale, (2) electronic control box, and (3) a frame that supports all hardware. The electronic control box includes: (i) a RFID reader, (ii) a LCD display, (iii) a thermal printer, (iv) a GPS module, and (v) a communication system. RFID tags, containing unique ID numbers, embedded within rubber wrist bands, are worn by pickers. This system can read a picker's ID (RFID bracelet), measure the weight of fruit, and record the time and location (optional) of every fruit 'transaction' (i.e., every time a

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Section: Portable Labor Monitoring Systems (Plms)mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Cloud-based harvest management information system for hand-harvested specialty crops

Ampatzidis

Tan

Haley

et al. 2016

Computers and Electronics in Agriculture

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“…Ampatzidis et al [12,13] address the problem of the integration of technologies in fruit orchards, with the inclusion of radio frequency identification (RFID) technology and bar codes in harvest bins and orchard trees of cherries. With the help of an electronic scale and differential global positioning systems (DGPSs) in the tractors that transport the harvest bins, measurements of the weight associated with the harvested fruit are efficiently acquired.…”

Section: Introductionmentioning

confidence: 99%

Harvest Stage Recognition and Potential Fruit Damage Indicator for Berries Based on Hidden Markov Models and the Viterbi Algorithm

Orchard

Munoz-Poblete

Huircan

et al. 2019

Sensors

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This article proposes a monitoring system that allows to track transitions between different stages in the berry harvesting process (berry picking, waiting for transport, transport and arrival at the packing site) solely using information from temperature and vibration sensors located in the basket. The monitoring system assumes a characterization of the process based on hidden Markov models and uses the Viterbi algorithm to perform inferences and estimate the most likely state trajectory. The obtained state trajectory estimate is then used to compute a potential damage indicator in real time. The proposed methodology does not require information about the weight of the basket to identify each of the different stages, which makes it effective and more efficient than other alternatives available in the industry.

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“…Luxhoj and Giacomelli (1990) compared the time-study method and two tabular methods: Element Times for Agriculture tables and the Maynard Operation Sequence Technique tables (Zandin, 2003) for evaluating the operations in a tomato greenhouse. To increase the accuracy and reliability of measuring the processing time, several handheld devices have been developed (Ampatzidis et al, 2012(Ampatzidis et al, , 2013Bechar and Eben-Chaime, 2014;Riemer and Bechar, 2016). However, for PPSLs, there is little information based on a work analysis including the evaluation of labor productivity.…”

mentioning

confidence: 99%

Evaluating Labor Productivity in a Plant Production System with Sole-source Lighting: A Case Study

Ohyama

Yamaguchi

Enjoji

2018

hortte

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Labor productivity in terms of material value (weight of plants harvested per hour per person) was evaluated for 6 months from the start of operations in a research facility at Osaka Prefecture University (Osaka, Japan), serving as a model system for plant production with sole-source lighting (also referred to as a “vertical farm” or “plant factory”). The research facility is capable of producing lettuce plants (Lactuca sativa) at a maximum production rate of ≈5000 plants/day when the relative harvest rate (i.e., number of plants harvested/maximum potential number of plants harvested) is 100%. However, in the present study, the relative harvest rate at the research facility was in the range of 17% to 65% and labor productivity varied from 1.5 to 6.0 kg·h−1 per person. The evaluation results indicated that increasing the weight of plants harvested and increasing the relative harvest rate was necessary to maintain a high level of labor productivity. The processing time for harvesting was greatest among all plant operations, suggesting the need to reduce the time taken in this operation to increase the labor productivity in the research facility and in other plant production systems with sole-source lighting (PPSLs). This study demonstrates the importance of analyzing labor productivity for increasing the commercial feasibility of PPSLs. However, further long-term investigation with higher relative harvest rates is required for a more definitive conclusion.

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Development and evaluation of a novel system for monitoring harvest labor efficiency

Cited by 16 publications

References 16 publications

Cloud-based harvest management information system for hand-harvested specialty crops

Cloud-based harvest management information system for hand-harvested specialty crops

Harvest Stage Recognition and Potential Fruit Damage Indicator for Berries Based on Hidden Markov Models and the Viterbi Algorithm

Evaluating Labor Productivity in a Plant Production System with Sole-source Lighting: A Case Study

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