Ergonomic problems in agricultural farms: Explainable relationship between awkward postures and body discomforts in Iranian leafy vegetable cultivation.

BACKGROUND: Many agricultural activities excessively need human power and are associated with musculoskeletal disorders (MSDs). Leafy vegetable cultivation (LVC) is one of these. OBJECTIVE: The postural workload, body discomfort, and explainable linkage between these among Iranian wintry LVC workers were investigated. METHODS: Postures and body discomfort were evaluated using Ovako working posture analyzing system (OWAS) and a body map, respectively. The explainable body discomforts by working postures for each body region were descriptively discussed using some of the literature. RESULTS: Considering the maximum MSD risk value of 400%, irrigation and manual harvesting had the highest MSD risks with index risks of 313% and 305% respectively. Low back discomfort was the most common body discomfort in LVC which was reported for the operations of moldboard plowing, disking, manure application, chemical broadcasting, spraying, and manual harvesting. LVC operations seemed to rely heavily on the use of low back and shoulders. Bent and/or twist postures were the most common postures for the back. CONCLUSIONS: Almost all the body discomforts were explained by awkward postures shown by postural workload analysis. Therefore, the working posture analysis results may be reliable and utilized in future decisions around ergonomic interventions. Future studies may be conducted to investigate the simple and inexpensive ergonomic interventions to mitigate MSD risks.

Application of classic and soft computing for modeling yield and environmental final impact in vegetable production (a case study: transplanting onion in Isfahan province, Iran).

This study aimed to develop a precision model between inputs and yield, and also between inputs (indirect emissions) and environmental final index (EFI) in onion farms through regression models (classic computing) and artificial intelligence models (soft computing). Required data were collected through direct measurement and questionnaire. To this end, 85 and 70 questionnaires were distributed among onion farmers in Fereydan and Falavarjan regions (Isfahan province, center of Iran), respectively. In the Fereydan region, the total energy input, onion yield, and water use efficiency (WUE) were obtained as 239496 MJ.ha-1, 97658 kg.ha-1, and 9.08 kg.m-3, respectively, while for Falavarjan region, these were obtained as 232221 MJ.ha-1, 94485 kg.ha-1, and 10.8 kg m-3, respectively. Electricity and diesel fuel were the most widely used inputs in the study areas. Based on the results related to the environmental indices, EFI was obtained as 547.38 and 363.54 pPt.t-1 for Fereydan and Falavarjan regions, respectively. The contribution of direct (such as CO2 and NH3) and indirect emissions (especially electricity) to the total EFI was 74 and 26% in Fereydan and 63 and 37% in Falavarjan region, respectively. Results related to the Cobb-Douglas regression model (CDR) showed that the effects of seed, manure, and labor on the onion yield were significant at 1% level of confidence. However, despite meeting the regression assumptions, the CDR model has predicted the yield and EFI with lower accuracy and higher error compared to artificial neural network models (ANNs), multi-layer perceptron (MLP), and adaptive neuro-fuzzy inference system (ANFIS). Soft computing (artificial intelligence) modeling showed that the ANFIS model (Grid Partitioning (GP)) has higher computational speed an lower error compared to multi-layer perceptron (MLP) models. Therefore, the comparison of the best GP and MLP models showed that the root-mean-square-error (RMSE) was obtained as 10.649 and 52.321 kg.ha-1 for yield and 25.08 and 40.94 pPt.ha-1 for EFI, respectively.

Occupational safety and health in traditional date palm works.

OBJECTIVE: Date palm is mostly cultivated in Western Asia and North Africa and is the main wealth for the people of these regions. Traditional date palm crown access via manual climbing, as the main activity in date fruit production, suffers from occupational hazards. Mitigation of these problems through interventions or new designs initially needs to complete knowledge of safety and health aspects and relationships between them and characters of date palm climbers. This study provided detailed information about this concern. METHODS: A questionnaire consisting of personal, operational, safety, satisfaction, financial and ergonomic demographics was used for data collection. 117 climbers participated in the study. Nonparametric correlations using Spearman's coefficient and logistic regressions investigated the linkage between characters obtained by the questionnaire. RESULTS: The annual mortality rate of falls from height was calculated by 3.4 per one thousand men. Fall was a major challenge in traditional date palm crown access and its rate was highly greater in comparison with the estimation of International Labor Office (ILO) about fatal agricultural injuries. Safety and health condition was the main contributing factor in the status of date palm climbing and was significantly linked to job satisfaction. Safety risk-taking and non-awareness of technology had a significant linkage with together (r = - 0.195, p = 0.035). Safety risk-taking, also, had significant correlations with discomfort in back (r = - 0.201, p = 0.030). Regressions showed heavier climbers (> 75 kg) were expected about 4.3 (1/0.230) times than more lightweight ones to have an upper leg discomfort with high severity relative to low severity (p = 0.018). CONCLUSION: Obesity, senescence, and awareness of technology as three personal characteristics of climbers need to be addressed. Future strategies are required to improve the safety condition of climbing and manage the workforces as well as governmental decision making to address the financial aspects of climbers for sustainable date production and reduction in reasons causing unemployment. Considering current status and modification of the present tool and equipment is recommended.

Integration of life cycle assessment (LCA) and modeling methods in investigating the yield and environmental emissions final score (EEFS) of carp fish (Cyprinus carpio) farms.

This study was conducted to investigate and predict the yield and environmental emissions final score (EEFS) of common carp fish farms in Shushtar county of Khuzestan province. The required data was collected from 115 carp fish farms selected by random sampling using face-to-face questionnaire and interview. The total input energy, the yield, and energy ratio were obtained as 293,127.95 MJ ha-1, 3389.28 kg ha-1, and 0.30, respectively. Electricity and feed consumption had the highest contributions to total input energy and environmental emissions. The normalization results showed that the marine aquatic ecotoxicity (MAET) and freshwater aquatic ecotoxicity (FAET) had the highest values among all impact categories with 671.50×10-9 and 152.60×10-9, respectively. Also, the EEFS was calculated per tons of carp fish as 7793.09 pPt. The comparison of results between the regression model and adaptive neuro-fuzzy inference system (ANFIS) indicated that in prediction of the yield, the accuracy values (R2) of regression and ANFIS models were 0.87 and 0.99, respectively, while in prediction of EEFS, R2 of regression and ANFIS models were 0.98 and 0.99, respectively. In total, it was concluded that ANFIS model can predict the yield better than regression model.

Linkage between machine power utilization and ergonomics, with reference to reducing exertions at work.

BACKGROUND: Despite mechanization development, leafy vegetable cultivation (LVC), as a labor-intensive activity in both developed and developing countries, still suffers from heavy physical activities. OBJECTIVE: The present study evaluated the human physiological strains of LVC's workers to identify relationships among contributing factors affecting human physiological strains. METHODS: Thirty male workers were included in this study. Working heart rate (HR) was measured using a heart rate sensor during various operations. The time taken to treat a known area was measured using a stopwatch to calculate work speed (or field capacity (FC)) for each operation. Pearson correlation coefficient and linear regression were used to investigate the relationships among HR, heart rate ratio, FC and mechanization status (MS), and human energy expenditure rate and total energy expenditure per unit area. RESULTS: The highest HR was at seedbed preparing (120.1 beats/min) and lowest at manual harvesting (87.8 beats/min). Manual hoe-used operations (seedbed preparing, manure application and irrigating) were demonstrated as the critical operations concerning physiological strains. The operations performed by machine power corresponded to a high FC. CONCLUSIONS: Variables influencing the area treating speed (i.e. MS and FC) are negatively linked to the human energy consumed per unit area and variable changed in time unit (i.e. HR) was positively linked to the human energy expenditure speed.

Chemical footprint of pesticides used in citrus orchards based on canopy deposition and off-target losses.

The application of chemical pesticides is one of the main practices in citrus orchards. But during this operation, a considerable amount of sprayed volume is emitted to off-target areas using air-blast sprayers. The present study aimed to investigate pesticides' toxicological impacts in citrus orchards through determining the proportion of pesticides in different areas (air, soil, and canopy), which facilitate toxicity assessment of pesticides in citrus orchards. In this study, human toxicity and freshwater ecotoxicity impacts were assessed using USEtox 2.1 modeling approach for five active ingredients used in citrus orchards in the south of Iran. Different spraying scenarios were defined based on two types of nozzles (Hallow-cone and Teejet full-cone) and three levels of pressure (30, 40, and 50 bar) in two orchards with different row spacing. Results showed that only 26-37% of spray solution is deposited on the target with much loss to areas between tree canopies on the row. Scenario 1 (Hallow-cone nozzle with spraying pressure as 30 bar) shows the highest spraying efficiency in the both orchards (37% and 34% for Tangerine and Lemon orchards, respectively). Air emissions were obtained around 17 and 18% for hollow-cone and Teejet full-cone nozzles, respectively. The final inventory was obtained considering evaporation rate of active ingredients from soil surface and leaves. Based on the results obtained from toxicological impact assessment, Thiacloprid and Carbendazim had the highest negative environmental impacts on human health and freshwater aquatic ecosystem, respectively. Based on the results, soil emissions were identified as more critical than air emissions in terms of environmental consequences. It can be attributed to the higher characterization factor and deposition on the soil in comparison to the air. The present study provided well-founded information on the environmental performance of production systems by estimating the relevant emissions of pesticides to different compartments and determined the human and freshwater toxicity impact profiles, which assist decision-makers and LCA-practitioners to have a better perspective about pesticides behavior in receiving compartment.