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This study investigates the input–output energy-flow patterns and CO2 emissions from the wheat–rice crop rotation system. In this regard, an arid region of Punjab, Pakistan was selected as the study area, comprising 4150 km2. Farmers were interviewed to collect data and information on input/output sources during the 2020 work season. The total energy from these sources was calculated using appropriate energy equivalents. Three energy indices, including energy use efficiency (ηe), energy productivity (ηp), and net energy (ρ), were defined and calculated to investigate overall energy efficiency. Moreover, the data envelopment analysis (DEA) technique was used to optimize the input energy in wheat and rice production. Finally, CO2 emissions was calculated using emissions equivalents from peer-reviewed published literature. Results showed that the average total energy consumption in rice production was twice the energy consumed in wheat production. However, the values of ηe, ηp, and ρ were higher in wheat production and calculated as 5.68, 202.3 kg/GJ, and 100.12 GJ/ha, respectively. The DEA showed the highest reduction potential in machinery energy for both crops, calculated as −42.97% in rice production and −17.48% in wheat production. The highest CO2 emissions were found in rice production and calculated as 1762.5 kg-CO2/ha. Our conclusion indicates that energy consumption and CO2 emissions from wheat–rice cropping systems can be minimized using optimized energy inputs.
Muhammad N. Ashraf; Muhammad H. Mahmood; Muhammad Sultan; Redmond R. Shamshiri; Sobhy M. Ibrahim. Investigation of Energy Consumption and Associated CO2 Emissions for Wheat–Rice Crop Rotation Farming. Energies 2021, 14, 5094 .
AMA StyleMuhammad N. Ashraf, Muhammad H. Mahmood, Muhammad Sultan, Redmond R. Shamshiri, Sobhy M. Ibrahim. Investigation of Energy Consumption and Associated CO2 Emissions for Wheat–Rice Crop Rotation Farming. Energies. 2021; 14 (16):5094.
Chicago/Turabian StyleMuhammad N. Ashraf; Muhammad H. Mahmood; Muhammad Sultan; Redmond R. Shamshiri; Sobhy M. Ibrahim. 2021. "Investigation of Energy Consumption and Associated CO2 Emissions for Wheat–Rice Crop Rotation Farming." Energies 14, no. 16: 5094.
The purpose of this study was to develop an in-vitro digestion protocol to evaluate the antioxidant potential of the peptides found in processed cheddar cheese using digestion enzymes. We first studied antioxidant and angiotensin-converting enzyme (ACE) inhibition and antioxidant activities of processed cheddar cheese with the addition of spices e.g., cumin, clove, and black pepper made from buffalo milk and ripened for 9 months. Then we conducted an in vitro digestion of processed cheddar cheese by gastric and duodenal enzymes. Freeze-dried water (WSE) and ethanol-soluble fractions (ESE) of processed cheddar cheese were also monitored for their ACE inhibition activity and antioxidant activities. In our preliminary experiments, different levels of spices (cumin, clove, and black pepper) were tested into a cheese matrix and only one level 0.2 g/100 g (0.2%) based on cheese weight was considered good after sensory evaluation. Findings of the present study revealed that ACE-inhibitory potential was the highest in processed cheese made from buffalo milk with the addition of 0.2% cumin, clove, and black pepper. A significant increase in ACE-inhibition (%) of processed cheddar cheese, as well as its WSE and ESE, was obtained. Lower IC50 values were found after duodenal phase digestion compared to oral phase digestion.
Amal Shaukat; Muhammad Nadeem; Tahir Qureshi; Rabia Kanwal; Muhammad Sultan; Olivier Kashongwe; Redmond Shamshiri; Mian Murtaza. Effect of In Vitro Digestion on the Antioxidant and Angiotensin-Converting Enzyme Inhibitory Potential of Buffalo Milk Processed Cheddar Cheese. Foods 2021, 10, 1661 .
AMA StyleAmal Shaukat, Muhammad Nadeem, Tahir Qureshi, Rabia Kanwal, Muhammad Sultan, Olivier Kashongwe, Redmond Shamshiri, Mian Murtaza. Effect of In Vitro Digestion on the Antioxidant and Angiotensin-Converting Enzyme Inhibitory Potential of Buffalo Milk Processed Cheddar Cheese. Foods. 2021; 10 (7):1661.
Chicago/Turabian StyleAmal Shaukat; Muhammad Nadeem; Tahir Qureshi; Rabia Kanwal; Muhammad Sultan; Olivier Kashongwe; Redmond Shamshiri; Mian Murtaza. 2021. "Effect of In Vitro Digestion on the Antioxidant and Angiotensin-Converting Enzyme Inhibitory Potential of Buffalo Milk Processed Cheddar Cheese." Foods 10, no. 7: 1661.
The present study reports the development of a deep learning artificial intelligence (AI) model for predicting the thermal performance of evaporative cooling systems, which are widely used for thermal comfort in different applications. The existing, conventional methods for the analysis of evaporation-assisted cooling systems rely on experimental, mathematical, and empirical approaches in order to determine their thermal performance, which limits their applications in diverse and ambient spatiotemporal conditions. The objective of this research was to predict the thermal performance of three evaporation-assisted air-conditioning systems—direct, indirect, and Maisotsenko evaporative cooling systems—by using an AI approach. For this purpose, a deep learning algorithm was developed and lumped hyperparameters were initially chosen. A correlation analysis was performed prior to the development of the AI model in order to identify the input features that could be the most influential for the prediction efficiency. The deep learning algorithm was then optimized to increase the learning rate and predictive accuracy with respect to experimental data by tuning the hyperparameters, such as by manipulating the activation functions, the number of hidden layers, and the neurons in each layer by incorporating optimizers, including Adam and RMsprop. The results confirmed the applicability of the method with an overall value of R2 = 0.987 between the input data and ground-truth data, showing that the most competent model could predict the designated output features (
Hafiz Asfahan; Uzair Sajjad; Muhammad Sultan; Imtiyaz Hussain; Khalid Hamid; Mubasher Ali; Chi-Chuan Wang; Redmond Shamshiri; Muhammad Khan. Artificial Intelligence for the Prediction of the Thermal Performance of Evaporative Cooling Systems. Energies 2021, 14, 3946 .
AMA StyleHafiz Asfahan, Uzair Sajjad, Muhammad Sultan, Imtiyaz Hussain, Khalid Hamid, Mubasher Ali, Chi-Chuan Wang, Redmond Shamshiri, Muhammad Khan. Artificial Intelligence for the Prediction of the Thermal Performance of Evaporative Cooling Systems. Energies. 2021; 14 (13):3946.
Chicago/Turabian StyleHafiz Asfahan; Uzair Sajjad; Muhammad Sultan; Imtiyaz Hussain; Khalid Hamid; Mubasher Ali; Chi-Chuan Wang; Redmond Shamshiri; Muhammad Khan. 2021. "Artificial Intelligence for the Prediction of the Thermal Performance of Evaporative Cooling Systems." Energies 14, no. 13: 3946.
The purpose of this study was to develop an in-vitro digestion protocol to evaluate the antioxidant potential of the peptides found in processed cheddar cheese using digestion enzymes. We studied first antioxidant and angiotensin converting enzyme (ACE) inhibition and antioxidant activities of processed cheddar cheese with the addition of spices e.g. cumin, clove and black pepper made from buffalo milk and ripened for 9 months. Then we conducted an in vitro digestion of processed cheddar cheese by gastric and duodenal enzymes. Freeze dried water (WSE) and ethanol soluble fractions (ESE) of processed cheddar cheese were also monitored for their ACE inhibition activity and antioxidant activities. In our preliminary experiments, different levels of spices (cumin, clove and black pepper) were tested into cheese matrix and only one level 0.2g/100g (0.2%) on the basis of cheese weight was considered good concerning sensory evaluation. Significant increase in ACE-inhibition (%) of processed Cheddar cheese as well as its WSE and ESE was obtained. Lower IC50 values were found after duodenal phase digestion compared to oral phase digestion.
Amal Shaukat; Muhammad Nadeem; Tahir Mahmood Qureshi; Rabiak Kanwal; Muhammad Sultan; Olivier Basole Kashongwe; Redmond R. Shamshiri; Mian Anjum Murtaza. Effect of In Vitro Digestion on the Antioxidant and Angiotensin Converting Enzyme (ACE)-Inhibitory Potential of Buffalo Milk Processed Cheddar Cheese. 2021, 1 .
AMA StyleAmal Shaukat, Muhammad Nadeem, Tahir Mahmood Qureshi, Rabiak Kanwal, Muhammad Sultan, Olivier Basole Kashongwe, Redmond R. Shamshiri, Mian Anjum Murtaza. Effect of In Vitro Digestion on the Antioxidant and Angiotensin Converting Enzyme (ACE)-Inhibitory Potential of Buffalo Milk Processed Cheddar Cheese. . 2021; ():1.
Chicago/Turabian StyleAmal Shaukat; Muhammad Nadeem; Tahir Mahmood Qureshi; Rabiak Kanwal; Muhammad Sultan; Olivier Basole Kashongwe; Redmond R. Shamshiri; Mian Anjum Murtaza. 2021. "Effect of In Vitro Digestion on the Antioxidant and Angiotensin Converting Enzyme (ACE)-Inhibitory Potential of Buffalo Milk Processed Cheddar Cheese." , no. : 1.
Estimation of plant canopy using low-altitude imagery can help monitor the normal growth status of crops and is highly beneficial for various digital farming applications such as precision crop protection. However, extracting 3D canopy information from raw images requires studying the effect of sensor viewing angle by taking into accounts the limitations of the mobile platform routes inside the field. The main objective of this research was to estimate wheat (Triticum aestivum L.) leaf parameters, including leaf length and width, from the 3D model representation of the plants. For this purpose, experiments with different camera viewing angles were conducted to find the optimum setup of a mono-camera system that would result in the best 3D point clouds. The angle-control analytical study was conducted on a four-row wheat plot with a row spacing of 0.17 m and with two seeding densities and growth stages as factors. Nadir and six oblique view image datasets were acquired from the plot with 88% overlapping and were then reconstructed to point clouds using Structure from Motion (SfM) and Multi-View Stereo (MVS) methods. Point clouds were first categorized into three classes as wheat canopy, soil background, and experimental plot. The wheat canopy class was then used to extract leaf parameters, which were then compared with those values from manual measurements. The comparison between results showed that (i) multiple-view dataset provided the best estimation for leaf length and leaf width, (ii) among the single-view dataset, canopy, and leaf parameters were best modeled with angles vertically at −45° and horizontally at 0° (VA −45, HA 0), while (iii) in nadir view, fewer underlying 3D points were obtained with a missing leaf rate of 70%. It was concluded that oblique imagery is a promising approach to effectively estimate wheat canopy 3D representation with SfM-MVS using a single camera platform for crop monitoring. This study contributes to the improvement of the proximal sensing platform for crop health assessment.
Minhui Li; Redmond Shamshiri; Michael Schirrmann; Cornelia Weltzien. Impact of Camera Viewing Angle for Estimating Leaf Parameters of Wheat Plants from 3D Point Clouds. Agriculture 2021, 11, 563 .
AMA StyleMinhui Li, Redmond Shamshiri, Michael Schirrmann, Cornelia Weltzien. Impact of Camera Viewing Angle for Estimating Leaf Parameters of Wheat Plants from 3D Point Clouds. Agriculture. 2021; 11 (6):563.
Chicago/Turabian StyleMinhui Li; Redmond Shamshiri; Michael Schirrmann; Cornelia Weltzien. 2021. "Impact of Camera Viewing Angle for Estimating Leaf Parameters of Wheat Plants from 3D Point Clouds." Agriculture 11, no. 6: 563.
A greenhouse is a complex environment in which various biological and non-biological phenomena occur. For simulation and prediction of the climate and plant growth changes in the greenhouse are necessary to provide mathematical models. The dynamic greenhouse climate models are classified in mechanistic and black-box models (ARX). Climatic models are mainly obtained using energy balance or computational fluid dynamics. In the energy balance models, the greenhouse climatic variables are considered uniformity and homogeneity, but in the computational fluid dynamics, the heterogeneity of the greenhouse environment can be shown by 3D simulation. Crop growth simulation models are quantitative tools based on scientific principles and mathematical relationships that can evaluate the different effects of climate, soil, water, and crop management factors on crop growth and development. In this chapter, with a review of the basics of climate models in greenhouses, the results and application of some climate dynamics models based on the energy balance as well as simulations performed with computational fluid dynamics are reviewed. A review of greenhouse growth models and functional–structural plant models (FSPM) was also conducted.
Seyed Moin-E-Ddin Rezvani; Redmond R. Shamshiri; Ibrahim A. Hameed; Hamid Zare Abyane; Mohsen Godarzi; Davood Momeni; Siva K. Balasundram. Greenhouse Crop Simulation Models and Microclimate Control Systems, A Review. Next-Generation Greenhouses for Food Security 2021, 1 .
AMA StyleSeyed Moin-E-Ddin Rezvani, Redmond R. Shamshiri, Ibrahim A. Hameed, Hamid Zare Abyane, Mohsen Godarzi, Davood Momeni, Siva K. Balasundram. Greenhouse Crop Simulation Models and Microclimate Control Systems, A Review. Next-Generation Greenhouses for Food Security. 2021; ():1.
Chicago/Turabian StyleSeyed Moin-E-Ddin Rezvani; Redmond R. Shamshiri; Ibrahim A. Hameed; Hamid Zare Abyane; Mohsen Godarzi; Davood Momeni; Siva K. Balasundram. 2021. "Greenhouse Crop Simulation Models and Microclimate Control Systems, A Review." Next-Generation Greenhouses for Food Security , no. : 1.
In Pakistan, many subsurface (SS) drainage projects were launched by the Salinity Control and Reclamation Project (SCARP) to deal with twin problems (waterlogging and salinity). In some cases, sump pumps were installed for the disposal of SS effluent into surface drainage channels. Presently, sump pumps have become dysfunctional due to social and financial constraints. This study evaluates the alternate design of the Paharang drainage system that could permit the discharge of the SS drainage system in the response of gravity. The proposed design was completed after many successive trials in terms of lowering the bed level and decreasing the channel bed slope. Interconnected MS-Excel worksheets were developed to design the L-section and X-section. Design continuity of the drainage system was achieved by ensuring the bed and water levels of the receiving drain were lower than the outfalling drain. The drain cross-section was set within the present row with a few changes on the service roadside. The channel side slope was taken as 1:1.5 and the spoil bank inner and outer slopes were kept as 1:2 for the entire design. The earthwork was calculated in terms of excavation for lowering the bed level and increasing the drain section to place the excavated materials in a specific manner. The study showed that modification in the design of the Paharang drainage system is technically admissible and allows for the continuous discharge of SS drainage effluent from the area.
Muhammad Imran; Jinlan Xu; Muhammad Sultan; Redmond Shamshiri; Naveed Ahmed; Qaiser Javed; Hafiz Asfahan; Yasir Latif; Muhammad Usman; Riaz Ahmad. Free Discharge of Subsurface Drainage Effluent: An Alternate Design of the Surface Drain System in Pakistan. Sustainability 2021, 13, 4080 .
AMA StyleMuhammad Imran, Jinlan Xu, Muhammad Sultan, Redmond Shamshiri, Naveed Ahmed, Qaiser Javed, Hafiz Asfahan, Yasir Latif, Muhammad Usman, Riaz Ahmad. Free Discharge of Subsurface Drainage Effluent: An Alternate Design of the Surface Drain System in Pakistan. Sustainability. 2021; 13 (7):4080.
Chicago/Turabian StyleMuhammad Imran; Jinlan Xu; Muhammad Sultan; Redmond Shamshiri; Naveed Ahmed; Qaiser Javed; Hafiz Asfahan; Yasir Latif; Muhammad Usman; Riaz Ahmad. 2021. "Free Discharge of Subsurface Drainage Effluent: An Alternate Design of the Surface Drain System in Pakistan." Sustainability 13, no. 7: 4080.
The greenhouse industry is an energy-intensive sector with a heavy reliance on fossil fuels, contributing to substantial greenhouse gas (GHG) emissions. Addressing this issue, the employment of energy-saving strategies along with the replacement of conventional energy sources with renewable energies are among the most feasible solutions. Over the last few years, solar energy has demonstrated great potential for integration with agricultural greenhouses. The present study reviews the progress of solar greenhouses by investigating their integration with solar energy technologies including photovoltaic (PV), photovoltaic-thermal (PVT), and solar thermal collectors. From the literature, PV modules mounted on roofs or walls of greenhouses cause shading which can adversely affect the growing trend of cultivated crops inside. This issue can be addressed by using bifacial PV modules or employing sun trackers to create dynamic shades. PVT modules are more efficient in producing both heat and electricity, and less shading occurs when concentrating modules are employed. In terms of using solar thermal collectors, higher performance values have been reported for greenhouses installed in moderate climate conditions. Further, in this review, the employment of thermal energy storage (TES) units as crucial components for secure energy supply in solar greenhouses is studied. The usage of TES systems can increase the thermal performance of solar greenhouses by 29%. Additionally, the most common mathematical models utilized to describe the thermal behavior of solar greenhouses are presented and discussed. From the literature, machine learning algorithms have shown a better capability to describe the complex environment of greenhouses, but their main drawback is less reliability. Notwithstanding the progress which has been made, further improvements in technology and more reductions in costs are required to make the solar greenhouse technology a solution to achieve sustainable development.
Shiva Gorjian; Francesco Calise; Karunesh Kant; Shamim Ahamed; Benedetta Copertaro; Gholamhassan Najafi; Xingxing Zhang; Mohammadreza Aghaei; Redmond R. Shamshiri. A review on opportunities for implementation of solar energy technologies in agricultural greenhouses. Journal of Cleaner Production 2021, 285, 124807 .
AMA StyleShiva Gorjian, Francesco Calise, Karunesh Kant, Shamim Ahamed, Benedetta Copertaro, Gholamhassan Najafi, Xingxing Zhang, Mohammadreza Aghaei, Redmond R. Shamshiri. A review on opportunities for implementation of solar energy technologies in agricultural greenhouses. Journal of Cleaner Production. 2021; 285 ():124807.
Chicago/Turabian StyleShiva Gorjian; Francesco Calise; Karunesh Kant; Shamim Ahamed; Benedetta Copertaro; Gholamhassan Najafi; Xingxing Zhang; Mohammadreza Aghaei; Redmond R. Shamshiri. 2021. "A review on opportunities for implementation of solar energy technologies in agricultural greenhouses." Journal of Cleaner Production 285, no. : 124807.
This study provides insights into the feasibility of a desiccant dehumidification-based Maisotsenko cycle evaporative cooling (M-DAC) system for greenhouse air-conditioning application. Conventional cooling techniques include direct evaporative cooling, refrigeration systems, and passive/active ventilation. which are commonly used in Pakistan; however, they are either not feasible due to their energy cost, or they cannot efficiently provide an optimum microclimate depending on the regions, the growing seasons, and the crop being cultivated. The M-DAC system was therefore proposed and evaluated as an alternative solution for air conditioning to achieve optimum levels of vapor pressure deficit (VPD) for greenhouse crop production. The objective of this study was to investigate the thermodynamic performance of the proposed system from the viewpoints of the temperature gradient, relative humidity level, VPD, and dehumidification gradient. Results showed that the standalone desiccant air-conditioning (DAC) system created maximum dehumidification gradient (i.e., 16.8 g/kg) and maximum temperature gradient (i.e., 8.4 °C) at 24.3 g/kg and 38.6 °C ambient air conditions, respectively. The DAC coupled with a heat exchanger (DAC+HX) created a temperature gradient nearly equal to ambient air conditions, which is not in the optimal range for greenhouse growing conditions. Analysis of the M-DAC system showed that a maximum air temperature gradient, i.e., 21.9 °C at 39.2 °C ambient air condition, can be achieved, and is considered optimal for most greenhouse crops. Results were validated with two microclimate models (OptDeg and Cft) by taking into account the optimality of VPD at different growth stages of tomato plants. This study suggests that the M-DAC system is a feasible method to be considered as an efficient solution for greenhouse air-conditioning under the climate conditions of Multan (Pakistan).
Hadeed Ashraf; Muhammad Sultan; Redmond Shamshiri; Farrukh Abbas; Muhammad Farooq; Uzair Sajjad; Hafiz Md-Tahir; Muhammad Mahmood; Fiaz Ahmad; Yousaf Taseer; Aamir Shahzad; Badar Niazi. Dynamic Evaluation of Desiccant Dehumidification Evaporative Cooling Options for Greenhouse Air-Conditioning Application in Multan (Pakistan). Energies 2021, 14, 1097 .
AMA StyleHadeed Ashraf, Muhammad Sultan, Redmond Shamshiri, Farrukh Abbas, Muhammad Farooq, Uzair Sajjad, Hafiz Md-Tahir, Muhammad Mahmood, Fiaz Ahmad, Yousaf Taseer, Aamir Shahzad, Badar Niazi. Dynamic Evaluation of Desiccant Dehumidification Evaporative Cooling Options for Greenhouse Air-Conditioning Application in Multan (Pakistan). Energies. 2021; 14 (4):1097.
Chicago/Turabian StyleHadeed Ashraf; Muhammad Sultan; Redmond Shamshiri; Farrukh Abbas; Muhammad Farooq; Uzair Sajjad; Hafiz Md-Tahir; Muhammad Mahmood; Fiaz Ahmad; Yousaf Taseer; Aamir Shahzad; Badar Niazi. 2021. "Dynamic Evaluation of Desiccant Dehumidification Evaporative Cooling Options for Greenhouse Air-Conditioning Application in Multan (Pakistan)." Energies 14, no. 4: 1097.
This study reports on the investigation of the performance of single and two-stage liquid and solid desiccant dehumidification systems and two-stage combined liquid and solid desiccant dehumidification systems with reference to humid climates. The research focus is on a dehumidification system capacity of 25 kW designed for room air conditioning application using the thermal models reported in the literature. RD-type silica gel and LiCl are used as solid and liquid desiccant materials, respectively. In this study, the application of proposed system for deep drying application is also explored. Condensation rate and moisture removal efficiency are chosen as performance parameters for room air conditioning application, whereas air outlet temperature is chosen as performance parameter for deep drying application. Further, for a given range of operating parameters, influences of air inlet humidity ratio, flow rate, and inlet temperature on performance parameters of the systems are investigated. In humid climatic conditions, it has been observed that a two-stage liquid desiccant dehumidification system is more effective for room air conditioning application, and two-stage solid desiccant dehumidification system is more suitable for deep drying application in the temperature range of 50 to 70 °C, while single-stage solid desiccant and two-stage combined liquid and solid desiccant dehumidification systems are more effective for low temperature, i.e., 30 to 50 °C deep drying application.
B. Naik; Mullapudi Joshi; P. Muthukumar; Muhammad Sultan; Takahiko Miyazaki; Redmond Shamshiri; Hadeed Ashraf. Investigating Solid and Liquid Desiccant Dehumidification Options for Room Air-Conditioning and Drying Applications. Sustainability 2020, 12, 10582 .
AMA StyleB. Naik, Mullapudi Joshi, P. Muthukumar, Muhammad Sultan, Takahiko Miyazaki, Redmond Shamshiri, Hadeed Ashraf. Investigating Solid and Liquid Desiccant Dehumidification Options for Room Air-Conditioning and Drying Applications. Sustainability. 2020; 12 (24):10582.
Chicago/Turabian StyleB. Naik; Mullapudi Joshi; P. Muthukumar; Muhammad Sultan; Takahiko Miyazaki; Redmond Shamshiri; Hadeed Ashraf. 2020. "Investigating Solid and Liquid Desiccant Dehumidification Options for Room Air-Conditioning and Drying Applications." Sustainability 12, no. 24: 10582.
The future megacity of Faisalabad is of prime interest when considering environmental health because of its bulky population and abundant industrial and anthropogenic sources of coarse particles (PM10) and fine airborne particulate matter (PM2.5). The current study was aimed to investigate the concentration level of PM2.5 and PM10, also the characterization of carbonaceous aerosols including organic carbon (OC), elemental carbon (EC) and total carbon (TC) in PM2.5 and PM10 samples collected from five different sectors (residential, health, commercial, industrial, and vehicular zone). The data presented here are the first of their kind in this sprawling city having industries and agricultural activities side by side. Results of the study revealed that the mass concentration of PM2.5 and PM10 is at an elevated level throughout Faisalabad, with ambient PM2.5 and PM10 points that constantly exceeded the 24-h standards of US-EPA, and National Environment Quality Standards (NEQS) which poses harmful effects on the quality of air and health. The total carbon concentration varied between 21.33 and 206.84 μg/m3, and 26.08 and 211.15 μg/m3 with an average of 119.16 ± 64.91 μg/m3 and 124.71 ± 64.38 μg/m3 for PM2.5 in summer and winter seasons, respectively. For PM10, the concentration of TC varied from 34.52 to 289.21 μg/m3 with an average of 181.50 ± 87.38 μg/m3 (for summer season) and it ranged between 44.04 and 300.02 μg/m3 with an average of 191.04 ± 87.98 μg/m3 (winter season), respectively. No significant difference between particulate concentration and weather parameters was observed. Similarly, results of air quality index (AQI) and pollution index (PI) stated that the air quality of Faisalabad ranges from poor to severely pollute. In terms of AQI, moderate pollution was recorded on sampling sites in the following order; Ittehad Welfare Dispensary > Saleemi Chowk > Kashmir Road > Pepsi Factory, while at Nazria Pakistan Square and Allied Hospital, higher AQI values were recorded. The analysis and results presented in this study can be used by policy-makers to apply rigorous strategies that decrease air pollution and the associated health effects in Faisalabad.
Afifa Aslam; Muhammad Ibrahim; Imran Shahid; Abid Mahmood; Muhammad Kashif Irshad; Muhammad Yamin; Ghazala; Muhammad Tariq; Redmond R. Shamshiri. Pollution Characteristics of Particulate Matter (PM2.5 and PM10) and Constituent Carbonaceous Aerosols in a South Asian Future Megacity. Applied Sciences 2020, 10, 8864 .
AMA StyleAfifa Aslam, Muhammad Ibrahim, Imran Shahid, Abid Mahmood, Muhammad Kashif Irshad, Muhammad Yamin, Ghazala, Muhammad Tariq, Redmond R. Shamshiri. Pollution Characteristics of Particulate Matter (PM2.5 and PM10) and Constituent Carbonaceous Aerosols in a South Asian Future Megacity. Applied Sciences. 2020; 10 (24):8864.
Chicago/Turabian StyleAfifa Aslam; Muhammad Ibrahim; Imran Shahid; Abid Mahmood; Muhammad Kashif Irshad; Muhammad Yamin; Ghazala; Muhammad Tariq; Redmond R. Shamshiri. 2020. "Pollution Characteristics of Particulate Matter (PM2.5 and PM10) and Constituent Carbonaceous Aerosols in a South Asian Future Megacity." Applied Sciences 10, no. 24: 8864.
Optimum microclimate parameters, including air temperature (T), relative humidity (RH) and vapor pressure deficit (VPD) that are uniformly distributed inside greenhouse crop production systems are essential to prevent yield loss and fruit quality. The objective of this research was to determine the spatial and temporal variations in the microclimate data of a commercial greenhouse with tomato plants located in the mid-west of Iran. For this purpose, wireless sensor data fusion was incorporated with a membership function model called Optimality Degree (OptDeg) for real-time monitoring and dynamic assessment of T, RH and VPD in different light conditions and growth stages of tomato. This approach allows growers to have a simultaneous projection of raw data into a normalized index between 0 and 1. Custom-built hardware and software based on the concept of the Internet-of-Things, including Low-Power Wide-Area Network (LoRaWAN) transmitter nodes, a multi-channel LoRaWAN gateway and a web-based data monitoring dashboard were used for data collection, data processing and monitoring. The experimental approach consisted of the collection of meteorological data from the external environment by means of a weather station and via a grid of 20 wireless sensor nodes distributed in two horizontal planes at two different heights inside the greenhouse. Offline data processing for sensors calibration and model validation was carried in multiple MATLAB Simulink blocks. Preliminary results revealed a significant deviation of the microclimate parameters from optimal growth conditions for tomato cultivation due to the inaccurate timer-based heating and cooling control systems used in the greenhouse. The mean OptDeg of T, RH and VPD were 0.67, 0.94, 0.94 in January, 0.45, 0.36, 0.42 in June and 0.44, 0.0, 0.12 in July, respectively. An in-depth analysis of data revealed that averaged OptDeg values, as well as their spatial variations in the horizontal profile were closer to the plants’ comfort zone in the cold season as compared with those in the warm season. This was attributed to the use of heating systems in the cold season and the lack of automated cooling devices in the warm season. This study confirmed the applicability of using IoT sensors for real-time model-based assessment of greenhouse microclimate on a commercial scale. The presented IoT sensor node and the Simulink model provide growers with a better insight into interpreting crop growth environment. The outcome of this research contributes to the improvement of closed-field cultivation of tomato by providing an integrated decision-making framework that explores microclimate variation at different growth stages in the production season.
Sayed Moin-Eddin Rezvani; Hamid Zare Abyaneh; Redmond R. Shamshiri; Siva K. Balasundram; Volker Dworak; Mohsen Goodarzi; Muhammad Sultan; Benjamin Mahns. IoT-Based Sensor Data Fusion for Determining Optimality Degrees of Microclimate Parameters in Commercial Greenhouse Production of Tomato. Sensors 2020, 20, 6474 .
AMA StyleSayed Moin-Eddin Rezvani, Hamid Zare Abyaneh, Redmond R. Shamshiri, Siva K. Balasundram, Volker Dworak, Mohsen Goodarzi, Muhammad Sultan, Benjamin Mahns. IoT-Based Sensor Data Fusion for Determining Optimality Degrees of Microclimate Parameters in Commercial Greenhouse Production of Tomato. Sensors. 2020; 20 (22):6474.
Chicago/Turabian StyleSayed Moin-Eddin Rezvani; Hamid Zare Abyaneh; Redmond R. Shamshiri; Siva K. Balasundram; Volker Dworak; Mohsen Goodarzi; Muhammad Sultan; Benjamin Mahns. 2020. "IoT-Based Sensor Data Fusion for Determining Optimality Degrees of Microclimate Parameters in Commercial Greenhouse Production of Tomato." Sensors 20, no. 22: 6474.
Okra possesses a short shelf-life which limits its marketability, thereby, the present study investigates the individual and combined effect of 1-methylcyclopropene (1-MCP) and modified atmosphere packaging (MAP) on the postharvest storage life of okra. The treated/ untreated okra samples were stored at ambient (i.e., 27 °C) and low (i.e., 7 °C) temperatures for eight and 20 days, respectively. Results revealed that the 1-MCP and/or MAP treatment successfully inhibited fruit softening, reduction in mucilage viscosity, and color degradation (hue angle, ∆E, and BI) in the product resulting in a longer period of shelf-life. However, MAP with or without 1-MCP was more effective to reduce weight loss in okra stored at both ambient and cold storage conditions. Additionally, ascorbic acid and total antioxidants were also retained in 1-MCP with MAP during cold storage. The 1-MCP in combination with MAP effectively suppressed respiration rate and ethylene production for four days and eight days at 27 °C and 7 °C temperature conditions, respectively. According to the results, relatively less chilling injury stress also resulted when 1-MCP combined with MAP. The combined treatment of okra pods with 1-MCP and MAP maintained the visual quality of the product in terms of overall acceptability for four days at 20 °C and 20 days at 7 °C.
Rabia Kanwal; Hadeed Ashraf; Muhammad Sultan; Irrum Babu; Zarina Yasmin; Muhammad Nadeem; Muhammad Asghar; Redmond R. Shamshiri; Sobhy M. Ibrahim; Nisar Ahmad; Muhammad A. Imran; Yuguang Zhou; Riaz Ahmad. Effect of 1-Methyl Cyclopropane and Modified Atmosphere Packaging on the Storage of Okra (Abelmoschus esculentus L.): Theory and Experiments. Sustainability 2020, 12, 7547 .
AMA StyleRabia Kanwal, Hadeed Ashraf, Muhammad Sultan, Irrum Babu, Zarina Yasmin, Muhammad Nadeem, Muhammad Asghar, Redmond R. Shamshiri, Sobhy M. Ibrahim, Nisar Ahmad, Muhammad A. Imran, Yuguang Zhou, Riaz Ahmad. Effect of 1-Methyl Cyclopropane and Modified Atmosphere Packaging on the Storage of Okra (Abelmoschus esculentus L.): Theory and Experiments. Sustainability. 2020; 12 (18):7547.
Chicago/Turabian StyleRabia Kanwal; Hadeed Ashraf; Muhammad Sultan; Irrum Babu; Zarina Yasmin; Muhammad Nadeem; Muhammad Asghar; Redmond R. Shamshiri; Sobhy M. Ibrahim; Nisar Ahmad; Muhammad A. Imran; Yuguang Zhou; Riaz Ahmad. 2020. "Effect of 1-Methyl Cyclopropane and Modified Atmosphere Packaging on the Storage of Okra (Abelmoschus esculentus L.): Theory and Experiments." Sustainability 12, no. 18: 7547.
In the 21st century, the poultry sector is a vital concern for the developing economies including Pakistan. The summer conditions of the city of Multan (Pakistan) are not comfortable for poultry birds. Conventionally, swamp coolers are used in the poultry sheds/houses of the city, which are not efficient enough, whereas compressor-based systems are not economical. Therefore, this study is aimed to explore a low-cost air-conditioning (AC) option from the viewpoint of heat stress in poultry birds. In this regard, the study investigates the applicability of three evaporative cooling (EC) options, i.e., direct EC (DEC), indirect EC (IEC), and Maisotsenko-cycle EC (MEC). Performance of the EC systems is investigated using wet-bulb effectiveness (WBE) for the climatic conditions of Multan. Heat stress is investigated as a function of poultry weight. Thermal comfort of the poultry birds is calculated in terms of temperature-humidity index (THI) corresponding to the ambient and output conditions. The heat production from the poultry birds is calculated using the Pederson model (available in the literature) at various temperatures. The results indicate a maximum temperature gradient of 10.2 °C (MEC system), 9 °C (DEC system), and 6.5 °C (IEC systems) is achieved. However, in the monsoon/rainfall season, the performance of the EC systems is significantly reduced due to higher relative humidity in ambient air.
Hafiz Raza; Hadeed Ashraf; Khawar Shahzad; Muhammad Sultan; Takahiko Miyazaki; Muhammad Usman; Redmond Shamshiri; Yuguang Zhou; Riaz Ahmad. Investigating Applicability of Evaporative Cooling Systems for Thermal Comfort of Poultry Birds in Pakistan. Applied Sciences 2020, 10, 4445 .
AMA StyleHafiz Raza, Hadeed Ashraf, Khawar Shahzad, Muhammad Sultan, Takahiko Miyazaki, Muhammad Usman, Redmond Shamshiri, Yuguang Zhou, Riaz Ahmad. Investigating Applicability of Evaporative Cooling Systems for Thermal Comfort of Poultry Birds in Pakistan. Applied Sciences. 2020; 10 (13):4445.
Chicago/Turabian StyleHafiz Raza; Hadeed Ashraf; Khawar Shahzad; Muhammad Sultan; Takahiko Miyazaki; Muhammad Usman; Redmond Shamshiri; Yuguang Zhou; Riaz Ahmad. 2020. "Investigating Applicability of Evaporative Cooling Systems for Thermal Comfort of Poultry Birds in Pakistan." Applied Sciences 10, no. 13: 4445.
Environmental concerns are growing about excessive applying nitrogen (N) fertilizers, especially in oil palm. Some conventional methods which are used to assess the amount of nutrient in oil palm are time-consuming, expensive, and involve frond destruction. Remote sensing as a non-destructive, affordable, and efficient method is widely used to detect the concentration of chlorophyll (Chl) from canopy plants using several vegetation indices (VIs) because there is an influential relation between the concentration of N in the leaves and canopy Chl content. The objectives of this research are to (i) evaluate and compare the performance of various vegetation indices (VIs) for measuring N status in oil palm canopy using SPOT-7 imagery (AIRBUS Defence & Space, Ottobrunn, Germany) to (ii) develop a regression formula that can predict the N content using satellite data to (iii) assess the regression formula performance on testing datasets by testing the coefficient of determination between the predicted and measured N contents. SPOT-7 was acquired in a 6-ha oil palm planted area in Pahang, Malaysia. To predict N content, 28 VIs based on the spectral range of SPOT-7 satellite images were evaluated. Several regression models were applied to determine the highest coefficient of determination between VIs and actual N content from leaf sampling. The modified soil-adjusted vegetation index (MSAVI) generated the highest coefficient of determination (R2 = 0.93). MTVI1 and triangular VI had the highest second and third coefficient of determination with N content (R2 = 0.926 and 0.923, respectively). The classification accuracy assessment of the developed model was evaluated using several statistical parameters such as the independent t-test, and p-value. The accuracy assessment of the developed model was more than 77%.
Mohammad Yadegari; Redmond R. Shamshiri; Abdul Rashid Mohamed Shariff; Siva K. Balasundram; Benjamin Mahns. Using SPOT-7 for Nitrogen Fertilizer Management in Oil Palm. Agriculture 2020, 10, 133 .
AMA StyleMohammad Yadegari, Redmond R. Shamshiri, Abdul Rashid Mohamed Shariff, Siva K. Balasundram, Benjamin Mahns. Using SPOT-7 for Nitrogen Fertilizer Management in Oil Palm. Agriculture. 2020; 10 (4):133.
Chicago/Turabian StyleMohammad Yadegari; Redmond R. Shamshiri; Abdul Rashid Mohamed Shariff; Siva K. Balasundram; Benjamin Mahns. 2020. "Using SPOT-7 for Nitrogen Fertilizer Management in Oil Palm." Agriculture 10, no. 4: 133.
Emission-free closed-field crop cultivation at a commercial scale necessitates microclimate evaluation for embracing the production uncertainties and maximizing the returns. This paper presents an application of the Internet-of-Things for model-based evaluation of microclimate parameters inside two greenhouse crop production systems. The objectives thus were to develop (i) a comfort ratio model, and (ii) a custom-built wireless sensor for data fusion in order to evaluate and compare microclimate parameters inside two different tropical greenhouses prior to the actual cultivation of tomato. The model was implemented in MATLAB Simulink with a flexible architecture and self-tuning reference inputs to work with different crops and cultural practices within which various growth stages can be modeled and analyzed. The accuracy and functional reliability of the sensor, as well as the performance of the model were validated by collecting and analyzing microclimate data from a naturally ventilated net-covered Screenhouse and a Polycarbonate Panel greenhouse under tropical lowland climate conditions of Malaysia. Raw data including air temperature, relative humidity, vapor pressure deficit and solar radiation were processed by the model for simulating comfort ratio values associated with different growth stages. Preliminary results showed that the mean and maximum vapor pressure deficit were respectively 1.19 and 5.1 kPa in the Polycarbonate Panel greenhouse and 0.97 and 3.81 kPa in the Screenhouse. Analyses based on comfort ratio values were validated with the results from raw data, showing that when temperature, relative humidity, and vapor pressure deficit were in the range of 25 ± 5 °C, 80 ± 20%, and 1.1±1 kPa in the Screenhouse, the comfort ratio values associated with the optimum reference borders were higher than those in the Polycarbonate Panel greenhouse. This study thus suggests that comfort ratio index is a more revealing indicator for comparing two or more greenhouses based on the dynamic assessment of microclimate parameters. The proposed method takes into an account the variation in each parameter, not only with the respect to different reference borders, but also by considering different time frames, light conditions and growth stages. The presented IoT sensor node and the Simulink model provide growers with a better insight into interpreting crop growth environment. The results of this study can contribute to optimal control strategies for a more efficient greenhouse crop production.
Redmond R. Shamshiri; Iva Bojic; Eldert van Henten; Siva K. Balasundram; Volker Dworak; Muhammad Sultan; Cornelia Weltzien. Model-based evaluation of greenhouse microclimate using IoT-Sensor data fusion for energy efficient crop production. Journal of Cleaner Production 2020, 263, 121303 .
AMA StyleRedmond R. Shamshiri, Iva Bojic, Eldert van Henten, Siva K. Balasundram, Volker Dworak, Muhammad Sultan, Cornelia Weltzien. Model-based evaluation of greenhouse microclimate using IoT-Sensor data fusion for energy efficient crop production. Journal of Cleaner Production. 2020; 263 ():121303.
Chicago/Turabian StyleRedmond R. Shamshiri; Iva Bojic; Eldert van Henten; Siva K. Balasundram; Volker Dworak; Muhammad Sultan; Cornelia Weltzien. 2020. "Model-based evaluation of greenhouse microclimate using IoT-Sensor data fusion for energy efficient crop production." Journal of Cleaner Production 263, no. : 121303.
Iran holds 10% of the global oil reserves and 15% of the natural gas. It is the second largest producer and exporter of oil and gas in Organization of the Petroleum Exporting Countries (OPEC). The consumption of energy in Iran is 4.4 times higher than the global average, placing it among the world's top ten greenhouse gas (GHG) emitters. According to the published statistics, renewable energy (RE) has faced a considerable growth in Iran due to the strategies of the sixth development plan, which aims at generating 5000 MW from REs by 2021, and an additional 2500 MW by 2030. The other reason is that under the “Paris Agreement” terms, Iran obliged to reduce its GHG emissions by at least 4% and at most 12% by 2030. Among RE resources, Iran has the remarkable potential for solar energy with the average annual rate of 4.5–5.5 kWh/m2. Under these conditions, solar photovoltaic (PV) power plants can play a crucial role in supplying a significant portion of the country's electricity demand. Although there is a high tendency of the government and policy makers for deployment of PV technology in Iran, there are still some impediments to turn potential into reality in this sector due to insufficient industry growth, financing problems, deficient of governing rules, and lack of a sustainable development roadmap. Solving these issues requires long-term and persisting policies to gain technical and industrial development to achieve mass progress in this sector during the next decades.
Shiva Gorjian; Babak Nemat Zadeh; Ludger Eltrop; Redmond R. Shamshiri; Yasaman Amanlou. Solar photovoltaic power generation in Iran: Development, policies, and barriers. Renewable and Sustainable Energy Reviews 2019, 106, 110 -123.
AMA StyleShiva Gorjian, Babak Nemat Zadeh, Ludger Eltrop, Redmond R. Shamshiri, Yasaman Amanlou. Solar photovoltaic power generation in Iran: Development, policies, and barriers. Renewable and Sustainable Energy Reviews. 2019; 106 ():110-123.
Chicago/Turabian StyleShiva Gorjian; Babak Nemat Zadeh; Ludger Eltrop; Redmond R. Shamshiri; Yasaman Amanlou. 2019. "Solar photovoltaic power generation in Iran: Development, policies, and barriers." Renewable and Sustainable Energy Reviews 106, no. : 110-123.
Unmanned aerial vehicles carrying multimodal sensors for precision agriculture (PA) applications face adaptation challenges to satisfy reliability, accuracy, and timeliness. Unlike ground platforms, UAV/drones are subjected to additional considerations such as payload, flight time, stabilization, autonomous missions, and external disturbances. For instance, in oil palm plantations (OPP), accruing high resolution images to generate multidimensional maps necessitates lower altitude mission flights with greater stability. This chapter addresses various UAV-based smart farming and PA solutions for OPP including health assessment and disease detection, pest monitoring, yield estimation, creation of virtual plantations, and dynamic Web-mapping. Stabilization of UAVs was discussed as one of the key factors for acquiring high quality aerial images. For this purpose, a case study was presented on stabilizing a fixed-wing Osprey drone crop surveillance that can be adapted as a remote sensing research platform. The objective was to design three controllers (including PID, LQR with full state feedback, and LQR plus observer) to improve the automatic flight mission. Dynamic equations were decoupled into lateral and longitudinal directions, where the longitudinal dynamics were modeled as a fourth order two-inputs-two-outputs system. State variables were defined as velocity, angle of attack, pitch rate, and pitch angle, all assumed to be available to the controller. A special case was considered in which only velocity and pitch rate were measurable. The control objective was to stabilize the system for a velocity step input of 10m/s. The performance of noise effects, model error, and complementary sensitivity was analyzed.
Redmond Ramin Shamshiri; Ibrahim A. Hameed; Siva K. Balasundram; Desa Ahmad; Cornelia Weltzien; Muhammad Yamin. Fundamental Research on Unmanned Aerial Vehicles to Support Precision Agriculture in Oil Palm Plantations. Agricultural Robots - Fundamentals and Applications 2019, 1 .
AMA StyleRedmond Ramin Shamshiri, Ibrahim A. Hameed, Siva K. Balasundram, Desa Ahmad, Cornelia Weltzien, Muhammad Yamin. Fundamental Research on Unmanned Aerial Vehicles to Support Precision Agriculture in Oil Palm Plantations. Agricultural Robots - Fundamentals and Applications. 2019; ():1.
Chicago/Turabian StyleRedmond Ramin Shamshiri; Ibrahim A. Hameed; Siva K. Balasundram; Desa Ahmad; Cornelia Weltzien; Muhammad Yamin. 2019. "Fundamental Research on Unmanned Aerial Vehicles to Support Precision Agriculture in Oil Palm Plantations." Agricultural Robots - Fundamentals and Applications , no. : 1.
A prototype robot that moves on a monorail along the greenhouse for weed elimination between cucumber plants was designed and developed. The robot benefits from three arrays of ultrasonic sensors for weed detection and a PIC18 F4550-E/P microcontroller board for processing. The feedback from the sensors activates a robotic arm, which moves inside the rows of the cucumber plants for cutting the weeds using rotating blades. Several experiments were carried out inside a greenhouse to find the best combination of arm motor (AM) speed, blade rotation (BR) speed, and blade design. We assigned three BR speeds of 3500, 2500, and 1500 rpm, and two AM speed of 10 and 30 rpm to three blade designs of S-shape, triangular shape, and circular shape. Results indicated that different types of blades, different BR speed, and different AM speed had significant effects (P < 0.05) on the percentage of weeds cut (PWC); however, no significant interaction effects were observed. The comparison between the interaction effect of the factors (three blade designs, three BR speeds, and two AM speeds) showed that maximum mean PWC was equal to 78.2% with standard deviation of 3.9% and was achieved with the S-shape blade when the BR speed was 3500 rpm, and the AM speed was 10 rpm. Using this setting, the maximum PWC that the robot achieved in a random experiment was 95%. The lowest mean PWC was observed with the triangular-shaped blade (mean of 50.39% and SD = 1.86), which resulted from BR speed of 1500 rpm and AM speed of 30 rpm. This study can contribute to the commercialization of a reliable and affordable robot for automated weed control in greenhouse cultivation of cucumber.
Amid Heravi; Desa Ahmad; Ibrahim A. Hameed; Redmond Ramin Shamshiri; Siva K. Balasundram; Muhammad Yamin. Development of a Field Robot Platform for Mechanical Weed Control in Greenhouse Cultivation of Cucumber. Agricultural Robots - Fundamentals and Applications 2019, 1 .
AMA StyleAmid Heravi, Desa Ahmad, Ibrahim A. Hameed, Redmond Ramin Shamshiri, Siva K. Balasundram, Muhammad Yamin. Development of a Field Robot Platform for Mechanical Weed Control in Greenhouse Cultivation of Cucumber. Agricultural Robots - Fundamentals and Applications. 2019; ():1.
Chicago/Turabian StyleAmid Heravi; Desa Ahmad; Ibrahim A. Hameed; Redmond Ramin Shamshiri; Siva K. Balasundram; Muhammad Yamin. 2019. "Development of a Field Robot Platform for Mechanical Weed Control in Greenhouse Cultivation of Cucumber." Agricultural Robots - Fundamentals and Applications , no. : 1.
This paper presents the study reports on evaluating a new transplanting operation by taking into accounts the interactions between soil, plant, and machine in line with the System of Rice Intensification (SRI) practices. The objective was to modify planting claw (kuku-kambing) of a paddy transplanter in compliance with SRI guidelines to determine the best planting spacing (S), seed rate (G) and planting pattern that results in a maximum number of seedling, tillers per hill, and yield. Two separate experiments were carried out in two different paddy fields, one to determine the best planting spacing (S=4 levels: s1=0.16 m×0.3 m, s2= 0.18 m×0.3 m, s3=0.21 m×0.3 m, and s4=0.24 m×0.3 m) for a specific planting pattern (row mat or scattered planting pattern), and the other to determine the best combination of spacing with seed rate treatments (G=2 levels: g1=75 g/tray, and g2= 240 g/tray). Main SRI management practices such as soil characteristics of the sites, planting depth, missing hill, hill population, the number of seedling per hill, and yield components were evaluated. Results of two-way analysis of variance with three replications showed that spacing, planting pattern and seed rate affected the number of one-seedling in all experiment. It was also observed that the increase in spacing resulted in more tillers and more panicle per plant, however hill population and sterility ratio increased with the decrease in spacing. While the maximum number of panicles were resulted from scattered planting at s4=0.24 m×0.3 m spacing with the seed rate of g1=75 g/tray, the maximum number of one seedling were observed at s4=0.16 m×0.3 m. The highest and lowest yields were obtained from 75 g seeds per tray scattered and 70 g seeds per tray scattered treatment respectively. For all treatments, the result clearly indicates an increase in yield with an increase in spacing. Keywords: system of rice intensification, sustainable cultivation, smart farming, modified transplanter, paddy fields, Malaysia DOI: 10.25165/j.ijabe.20191202.2999 Citation: Shamshiri R R, Ibrahim B, Balasundram S K, Taheri S, Weltzien C. Evaluating system of rice intensification using a modified transplanter: A smart farming solution toward sustainability of paddy fields in Malaysia. Int J Agric & Biol Eng, 2019; 12(2): 54–67.
Redmond Ramin Shamshiri; Bala Ibrahim; Siva K. Balasundram; Sima Taheri; Cornelia Weltzien. Evaluating system of rice intensification using a modified transplanter: A smart farming solution toward sustainability of paddy fields in Malaysia. International Journal of Agricultural and Biological Engineering 2019, 12, 54 -67.
AMA StyleRedmond Ramin Shamshiri, Bala Ibrahim, Siva K. Balasundram, Sima Taheri, Cornelia Weltzien. Evaluating system of rice intensification using a modified transplanter: A smart farming solution toward sustainability of paddy fields in Malaysia. International Journal of Agricultural and Biological Engineering. 2019; 12 (2):54-67.
Chicago/Turabian StyleRedmond Ramin Shamshiri; Bala Ibrahim; Siva K. Balasundram; Sima Taheri; Cornelia Weltzien. 2019. "Evaluating system of rice intensification using a modified transplanter: A smart farming solution toward sustainability of paddy fields in Malaysia." International Journal of Agricultural and Biological Engineering 12, no. 2: 54-67.