نشریه تحقیقات سامانه ها و مکانیزاسیون کشاورزی
پیاپی 85 (بهار 1402)

This study was conducted in order to investigate the factors of sugarcane production (inputs: physical-consumption) and optimization of energy consumption for sugarcane production using a data envelopment analysis in Khuzestan province, Amirkabir Agro-industrial Company Unit. The necessary information to conduct this study was collected from Agro-industrial of sugarcane Amirkabir experts through face-to-face interviews and questionnaire completion. According to the results, of the total energy consumed in production, the energy of cuttings and chemical fertilizers had the largest share among the consumed inputs with 59 and 16 (%), respectively. Biocides 3.15 (%), agricultural machines 1.09 (%) and human labor 0.06 (%) were the least energy-consuming inputs among other sugarcane production inputs. According to the results obtained from this research, it was found that two inputs sugarcane cuttings and chemical fertilizer have the highest amount of consumption among all the inputs for production. Also, the results of data coverage analysis showed that nitrogen fertilizer and human labor had the largest share of stored energy with 42 and 60.31 (%). The lowest share of energy stored in production belonged to chemical pesticides and phosphorus fertilizer, respectively. The results showed that reducing the consumption of chemical fertilizers and diesel fuel is important for energy storage and reducing the problem of environmental risk in the region. Saving in diesel fuel is possible by improving the performance of the irrigation pump and using new tractors and soil analysis to improve the use of chemical fertilizers.

In order to choose the optimal solution for the management of residual by products from the olive oil industry in Roudbar city of Guilan province, a systematic literature review and expert consultation were conducted to select the criteria. Four criteria, including economic, technical, social and environmental aspects were identified for choosing the solution which they divided into 12 sub-criteria. A paired comparison questionnaire was designed and completed through face-to-face interviews with 20 skilled experts in this field, using a purposeful sampling method. The Analytical Hierarchy Process (AHP) method was employed to analyze the data and perform calculations. The findings revealed that the economic criterion was the most important criterion with a weight of 0.478 in selecting the waste management approach for the olive oil industry. Afterward, respectively, technical criteria with a weight of 0.248, environmental with a weight of 0.183, and social with a weight of 0.091 were placed in the next ranks of importance by the experts. In the ranking of the alternatives, compost production was identified as the best option for managing olive oil waste in Guilan province. The results of the alternatives ranking indicated that compost production with a weight of 0.245 was considered the best option for olive oil waste in Guilan province. Followed by, renewable energy production (0.243) ranked second, animal feed production (0.236) ranked third, extraction of valuable materials (0.194) ranked fourth and finally dump in landfills (0.082) ranked last.

In this research, effects of water sprayed over the upper layer of the mowed and rowed alfalfa (before baling) on quantitative and qualitative losses of alfalfa during baling process were evaluated. The study was conducted in the form of split plot experiment with 12 treatments and three replications from 2020 to 2022. Main plots were the amount of water sprayed on the alfalfa with four levels of water (0, 250, 350, and 450 liters per hectare). Subplots were the time interval between spraying water on alfalfa and baling operation (0, 30, and 60 minutes after spraying water). Alfalfa losses at the baler pickup and compression chamber, during transportation, and total losses were measured. Alfalfa dry matter, crude protein, fat, organic matter, ash, acid detergent fiber, neutral detergent fiber was measured, and amount of aflatoxin were also detected after six months of storage. Results showed that spraying 450 L water per hectare decreased alfalfa losses at baler pickup and compression chamber, transportation, and total losses by 20.4, 34.3, 4.7, and 21.1% respectively, compared to the control treatment. Time interval between spraying water on alfalfa and baling time had no significant effect on alfalfa losses during baling operation and transportation. Results also indicated that spraying water on alfalfa before baling operation had no significant negative effects on alfalfa quality after six months storing and did not reduce alfalfa quality during storing time.

Hot air drying is the most common method used to dry agricultural products; this method is time consuming and has high energy consumption. Also, due to the rapid drying of the product surface in this method, the distribution and transferring of heat and moisture inside the product is relatively uneven. In fruits, such as apricots, skin of the fruit has a controlling and inhibitory effect on the drying process. Therefore, using some combination methods to dry fruits such as apricots, can reduce drying time and energy consumption. In the present study, a convection dryer was equipped with an infrared radiation system. The effect of hot air and infrared combination in different strategies on apricot drying was evaluated and compared. Experiments were conducted with hot air and infrared treatments alone, simultaneously and in a combination of two-stage and intermittent infrared in a combined dryer on a laboratory scale. The hot air temperature was 65 ° C, the velocity of hot air was 1.5 m/s and the power of infrared lamps was 400 watts. The results showed that the drying time, energy consumption and effective moisture penetration coefficient were significantly affected by the treatments. Midili et al.'s model was able to describe well the drying behavior of apricots for all the different combination states under investigation.

Iran is the largest saffron producer in the world. Saffron is of great economic importance and due to increasing activities of export competitors, it requires support, expansion, and development of exports. The growing trend of saffron export share on one hand and income generation and entrepreneurship for rural residents on the other hand double the necessity of attention to this product. Competition in this supply chain, despite powerful competitors, will be possible through mechanizing processes from cultivation to harvesting and grading to packaging. Therefore, evaluating the physical characteristics of saffron for proper grading is considered essential. In this study, the physical characteristics for the purpose of saffron grading using various artificial intelligence methods including Multilayer Perceptron Neural Networks (MLP), Learning Vector Quantization (LVQ), Self-Organizing Maps (SOM), Fuzzy Neural Networks (FNN), and Adaptive Neuro-Fuzzy Inference System (ANFIS) have been investigated. The database under study relates to 113 saffron samples categorized into 4 classes of Saffron Negin (top quality), Grade 2 Saffron (good), Grade 3 Saffron (normal), and Grade 4 Saffron (poor) collected by the researchers. The analysis results show that saffron grading considering uncertainties in the ANFIS model is superior to other methods, with a classification accuracy of 97.5% and a test sample detection error rate of 0.3484.

Tomato fruitworm (Heliotis) is the most destructive pests of the crops of Solanaceae family. In favorable environmental conditions, Heliotis spread quickly. In recent years, drone prayers have been used to control pests but the performance of these sprayers has not been evaluated in tomato fields yet. This research was carried out in a tomato field infected by the the Heliotis pest and the drone sprayer performance was compared with the performance of tractor lancer sprayer and back knapsack sprayer (atomizer) in the form of Randomized Complete Block Design (RCBD) and in three replications. The results showed that in tractor lancer, atomizer and drone sprayers the solution consumption was 1200, 211 and 32 liters per hectare, drift was 45.6, 13.06, 20.68 percent and field efficiency was 60.66, 69 and 90.2 percent respectively. In 14 days after spraying, the effectiveness was calculated 59.75%, 40.06% and 41.75% in drone method, atomizer and lancer methods respectively. In terms of effectiveness coefficient, the spraying with the drone was found better than that with atomizer and lancer methods on the 4th and 8th days after spraying. The spraying quality coefficient in atomizer and drone sprayer was 2.92 and 1.22, respectively. Economically, profit to cost ratio was calculated 4.15, 4.88 and 2.33 in lancer, atomizer and drone method respectively. Finally, according to the results, the use of drone sprayer to control tomato pests is recommended technically but in terms of economical aspects more studies should be done.