Introduction: Sunflower planting is mostly carried out for two particular purposes; oil production and as nut. HARVESTING is one of the biggest problems in both types of sunflower. The difficulty of HARVESTING and less scientific research have led us to study the mechanized HARVESTING of this kind of crops. In this research, head LOSSES and grain LOSSES for the inner section of combine were investigated during mechanized HARVESTING of oily sunflower and a regression model was used based on the experimental tests for head LOSSES and grain LOSSES in the inner section of the combine. Materials and Methods: After preparing an especial head for HARVESTING sunflower, the head was set up on the combine for measuring the harvest LOSSES. The cutting, threshing and clearing process for sunflower seeds were done during the tests. The design of the head is the same as the sunflower bushes are firstly bent by the bar and then sequentially the cutting, and transferring processes are done. The tests were implemented in an oily sunflower farm by a combine harvester (1055 john deer) in 3 replications. The farm performance was 2170 kg ha-1 and was located in Kermanshah province in Iran. A pre-test was done to define the best combine forward speed and finally 2. 5 km h-1 was adjusted for combine forward speed. The bar height (BH) in two levels (20 and 70 cm) and head height (HH) in two levels (60 and 120 cm) were independent parameters to evaluate the head. The dependent parameters were the combine LOSSES and head LOSSES. For the analysis of variance of the variable parameters, a 2×2 factorial plot with 3 replications was used. A regression model was defined based on experimental tests. Results and Discussion: Having done the experimental tests, data were analyzed and the effect of independent parameters on the head and combine grain LOSSES were investigated. The effect of the bar height on the head grain LOSSES was significant at 1% level and the effect of the head height and interaction between bar height and head height on the head grain LOSSES was also significant at 5% level. Results showed that with increasing in bar height, the head grain LOSSES increased. With a change in the bar height, the location of the cutting point is changed and this led to a change in the head grain LOSSES. The effect of the bar height on the combine grain LOSSES was significant at 5% level but the effect of the head height and interaction between bar height and head height was not significant on the combine grain LOSSES. Increasing in the bar height led to increase in material other grain (MOG) which enters to the combine, and also resulted in increasing in combine grain LOSSES. The coefficient of determination of head grain LOSSES in the regression model was 0. 97. The model was able to explain the relationship between the bar and head height with head grain LOSSES due to the relationship between independent and dependent parameters. The amount of R-squared for the combine grain LOSSES in the regression model was 0. 53. Because of the effect of other parameters in the inner section of the combine, the output of the model predicted that increasing in the bar height and head height, resulted in increasing in head grain LOSSES, and also increasing in the bar height and decreasing in head height let to increasing in combine grain LOSSES. The output of model showed that regulating the bar height and cutting height could reduce the harvest LOSSES by less than 3%. This R-squared is obviously less than R-squared of head grain LOSSES model. The output of the regression model predicted that the increase in the bar height and head height was associated with increase in the head grain LOSSES, and increasing in the bar height and decreasing in head height, resulted in increasing in combine grain LOSSES. The output of the regression model showed that the harvest LOSSES can be reduced less than 5% by regulating the bar height and cutting height. Conclusions: One of the most important parameters for mechanized HARVESTING is the head mechanism which cuts the crops and transfers them to the threshing unit. The cutting height in the sunflower head was defined by the bar height and head height. According to the linear relationship between the head and combine LOSSES with the bar height and head height, and the interaction between them, the regression model was able to predict the result successfully. This model of grain LOSSES in the head and combine model can be used in the intelligent combine to minimize the harvest LOSSES. The optimization of the bar height and head height for minimizing the harvest LOSSES can be the subject of next researches.

Mechanical HARVESTING of sugarcane is done in two ways: green and burnt, and usually burnt harvest has between 25-50% less LOSSES. When HARVESTING sugarcane, the sound of sugarcane pieces hitting the wall of the primary extractor hood can clearly be heard. Accordingly, it was decided to use the audio system to determine the relationship between these sounds and the LOSSES of the primary extractor. To record sounds in the basic extractor, two models of full-directional and one-way capacitive microphone (cardioid) and Cool Record Edit Deluxe and Audacity software were used. To detect the wavelength of the sounds caused by the collision of different parts of sugarcane with the hood cap and extractor blades by throwing a large volume of straw along with 25 cm pieces of sugarcane billets, a sound record was set. A camera was also installed there to record the video of what was happening under the extractor compartment. The results showed that the one-way capacitive microphone installed in the upper part of the primary extractor housing received clearer sounds. Analyzing the recorded sounds and comparing them with the images obtained from the camera under the primary extractor revealed that the audio loss detection system detects the LOSSES in the primary extractor with an accuracy of about 75 to 80%. The loss rate at 1200 rpm was about 1. 5 times higher than the loss rate at 1100 rpm.

Timely HARVESTING of paddy is very important in minimizing field LOSSES. Since this operation is labour consuming and expensive, steps have been taken to evaluate and develope an appropriate HARVESTING method for Guilan. In this study, a locally -manufactured power tiller-operated reaper and self-propelled reaper were field tested and compared to manual HARVESTING method. The results shown that, Grain LOSSES significantly differed in reaping and conveying stages. The grain LOSSES for manual HARVESTING was minimum (2.09%). The average field loss for mechanical HARVESTING was 2.8%. The actual field capacity of the self-propelled reaper was highest (0.294 ha/h) compared to 0.238 ha/h for power tiller-operated reaper and 0.0078 ha/h for manual HARVESTING. Labour input in mechanical reaping was 6.6 man-h/ha compared to 118.4 man-h/ha in manual operation. The cost of mechanical HARVESTING was 53% lower than manual HARVESTING. The average HARVESTING costs per ha are Rls. 1041875, Rls.481133 and Rls.483462 for manual HARVESTING, self-propelled and power tiller-operated reapers, respectively.

The most important agricultural products in our country is wheat that plays an important and distinct role in preparing food for people.Like other products of agriculture, we see many LOSSES in this product from producing to consuming. According to the results in HARVESTING irregular or old combines can affect the products by breaking grains or not separating the wheat from chaff. Doing this study, some parts of Varamin which have most wheat farming land have been chosen such as Javad Abad, Ghaleh Sin and Khaveh. The average of LOSSES in Varimin has been estimated 7 percent for one hectare. Amount of LOSSES was like this damage LOSSES 4.2 percent, quantitative LOSSES.1.6 percent, cylinder LOSSES 0.6 and sieve LOSSES 0.6 percent. It can be said that the main reasons for these LOSSES were: age of combine, speed of machine, cuter bar height, planting method, lack of adaptation between reel speed and combine speed, the farmer’s lack of fumiliarity with the combine, incongruity speed of fans, weed pollution, unsuitable of grain wheat during HARVESTING and irregularity of sieve. Accordingly, there are some suggestions: Land leveling, determination of useful age of combines and the best time for replacing, farmer’s and operators training, arrangement of combine device parts and using suitable ways for planting and irrigation.

Wheat is one of the important food staff in consumption pattern of each country. More than 50% of human energy is supplied from bread in the developing country. Combine LOSSES is less than 2-3% in developed countries, while in developing country is about 15-20% in different regions and circumstances of HARVESTING seasons and field conditions. In this research project that effect of combine type and wheat variety to grain LOSSES and waists were investigated. Experimental design was split plot in a completely randomized block design with three replications. Wheat variety in two levels of Sardari and Omid as a main plot and combines type in two levels of John Deere (JD) 1055 and JD 955 as a sub plot. Field experiments were carried out in the farmers field with 5 ha area. The results showed that higher amount of LOSSES were in the Omid variety and JD 955 with totally 5.97% (306.3 kg ha-1) that 14.75% of them attributed on the combine back, 41.6% on Header, 5.4% on Drum and 24.45% on impurity and 13.8% on grain breakage. The lowest LOSSES related to JD 1055 and Sardari variety with 3.12 % (160.05 kg ha-1) that 14.65% of them attributed on the combine back, 35.7% on Header, 4.5% on Drum, 26.15% on impurity and 19% on grain breakage.

Multistage and semi-mechanized HARVESTING of rice in Khouzestan province, Iran, causes much loss. Depending on available facilities and conditions, either spike-tooth or rasp-bar cylinders are employed with either direct or indirect combine HARVESTING methods. The present research studied the effect of these different HARVESTING methods on the amount of LOSSES in two rice varieties in 2001-2002 at Shavour Agricultural Research Station in Khouzestan province. The experiment was devised as a strip-plot with a randomized complete block design with two variables (HARVESTING method, variety) and three replications. The vertical axis variable HARVESTING methods were: indirect HARVESTING (manual) plus threshing by rasp-bar cylinder combine; indirect HARVESTING plus with threshing by spike-tooth cylinder combine; direct HARVESTING with threshing by rasp-bar cylinder combine, direct HARVESTING with threshing by spike-tooth cylinder combine. The horizontal axis variables were: high yield LD183 rice variety; qualitative local Red Anboury rice variety. Analysis of the LOSSES for the two years showed a significant difference between years for HARVESTING methods and their interactions but no significant difference between varieties. A comparison of averages showed that LOSSES for the first year were greater at 3.34% than for the second year at 2.08%. However, average LOSSES for the Red Anboury variety were 2.71% and 2.74% for the LD183 variety. For both direct and indirect HARVESTING methods, average LOSSES for HARVESTING by spike-tooth cylinder combine were 1.73%, which was less than the 3.68% for the rasp-bar cylinder combine. The spike-tooth cylinder combine produced the least amount of loss over the two varieties. Indirect HARVESTING of LD183 with threshing by rasp-bar cylinder combined in the first year produced the greatest average loss at 5.42%. Indirect HARVESTING of Red Anboury with threshing by spike-tooth cylinder combine in second year produced the lowest average loss at 1.48%. There was no significant difference between HARVESTING methods for quality of loss (broken rice rate) but there was a large significant difference by year with 45.6% for the second year and only 18.9% for the first year. This loss was also significant by variety with LD183 averaging 34.2% broken rice and Red Anboury averaging 27.6%. Over all HARVESTING methods, LD183 had greater broken rice rates.

Wheat is the most important staple crop in Iran. By reducing LOSSES of wheat at harvest stage, a significant increase of wheat fields production is possible. In view of increasing acceptance and the demand for straw walker combine, especially for HARVESTING the wheat, under present present investigation, the HARVESTING LOSSES rate of the conventional combine and the straw walker combine of John Deere 955 and Class 76 were compared. The straw walker and the conventional combines were tested under quite the same field conditions with 14% moisture content. Further LOSSES at different parts of combine such as cutting unit, threshing and separation, tank, MOG and seed germination percentage were also measured. The tested straw walker and the conventional combines were selected from Jandier (Hepko) and class companies. The results showed that the total harvest LOSSES of the straw walker combine and the conventional combine in both Claas and John Deere, had a significant difference. The LOSSES of John Deere straw walker combine mostly occurred at combine wheat storage tank at the value of 4. 16%, whereas the LOSSES in straw walker Class combine was mostly occurred at threshing and cleaning units which was about 8. 13%. It should be noted that LOSSES of both of tested combine had a significant difference as copared with LOSSES in conventional combine. Finally, it was observed that fuel consumption in case of straw walker Class combine was 55 litres per hectare and 69. 44 litres per hectare for straw walker John Deere combine.

Very few studies have investigated the effects of crop morphological characteristics on soil loss due to crop harvest (SLCH). The present study investigates the soil, nutrient (nitrogen, N, phosphorus, P, and potassium, K), and organic carbon LOSSES during the harvest of different potato cultivars with different morphological characteristics. The experiment is conducted at different soil water contents (SWC) controlled by different irrigation schemes, with the last irrigation 5, 10, and 15 days before harvest. At harvest time (early fall), in addition to measuring tuber yield (which was harvested manually) and SLCH, disturbed and undisturbed soil samples were collected in the field to measure various soil physicochemical properties and soil nutrient contents exported from the field. On average, 0.79 ± 0.36 Mg ha-1 soil, 580 g ha-1 nitrogen, 3 g ha-1 extractable phosphorus, 350 g ha-1 potassium, and 4.2 Kg ha-1 organic carbon were lost from the experimental fields at each harvest. The SLCH of the farms with Fontane, Challenger, and Agria cultivars was 1.21 ± 0.03 Mg ha-1 harvest-1, which was about three times higher than the SLCH of the farms with Innovator, Banba, Red Scarlet, Sifra, and Arinda cultivars with an average SLCH of 0.46 ± 0.06 Mg ha-1 harvest-1. The highest SLCH (2.57 Mg ha-1) occurred when SWC was highest compared to the other SWC values (i.e., 0.42 Mg ha-1). For a given soil stickiness, tuber length and specific surface area (SSA) generally explained the variation in SLCH values, with elongated tubers having lower SSA resulting in lower SLCH values.

Introduction: Corn harvest LOSSES are imposed by several factors, the most important of which is HARVESTING-time. Since the HARVESTING-time is coincident with the rainy season, it is necessary to appropriately estimate the corn harvest time to avoid HARVESTING LOSSES and losing the next cultivation. Accordingly, in the current research, the effect of HARVESTING-time on corn LOSSES during the month and the day has been into consideration. An expert fuzzy system was designed to predict the best harvest time as it operates based on the LOSSES amounts which are measured in processing and collection units into the combine, and LOSSES due to the humidity percentage. Materials and Methods: In this paper, corn harvest LOSSES in a John Deere Combine, Model 1165, was studied in a different climatic circumstance in Moghan region. Moreover, a split plot experiment in a completely randomized block design was conducted with three replications. The LOSSES data were collected from the processing and collection units of the combine harvester on the November 5th, 8th and 11th, 2017, in three different daily times of 8-10, 11-13 and 14-16 with three replications. The Mamdani fuzzy inference system with singleton fuzzifire and center average defuzzifire was used to develop a fuzzy expert system. In the designed expert system, the LOSSES percentage in the processing and collection units and the humidity percentage were considered as system inputs and optimal HARVESTING time was used as the system output. "Low, Very low, high and very high" and " Best, Suitable, Unfit, and Worst" were four groups of linguistic variables for input and output parameters, respectively. These variables follow the triangular and trapezoidal membership functions. The number of 64 fuzzy rules were considered and introduced into the fuzzy system by experts, experienced farmers, and combiners. Furthermore, the same field data (measured data) were applied to evaluate the designed system, so that the predicted value was accounted as the system output. Results and Discussion: Analysis of variance showed that there was a significant difference between the HARVESTING dates at the 0. 05 probability level and significant difference between the HARVESTING times of a day at the 0. 01 probability level. It can be concluded that the harvest dates and harvest times of a day were very effective in the number of corn LOSSES, but the interaction effects were not significant. The results appeared that the lowest LOSSES were 10. 05% on November 8th, 2017, at 14-16 p. m., and the highest LOSSES were 12. 88% on November 11th, 2017, at 8-10 a. m. The amount of LOSSES was increased due to the higher air humidity and lower temperature. In the fuzzy simulation model, the suitable HARVESTING-time can be predicted based on the LOSSES quantities in the processing and collection units and the humidity percentage. The results showed that the predicted values for HARVESTING-times, by a designed fuzzy system, were completely matched with measured values in this study. The coefficient of determination (R2) was 0. 980 between measured and predicted HARVESTING times. This coefficient demonstrated that the developed fuzzy logic system was suitable for prediction of HARVESTING time in the studied area. Conclusions: The experimental observations in the field and data analysis showed that in the corn HARVESTING in the Moghan region, the humidity level, date, and HARVESTING-time were the most effective factors in the HARVESTING LOSSES. In this paper, based on measured data from a small farm and implementation of the expert fuzzy system, the most suitable harvest date was set on November 8th at 14-16 p. m, at 21-24° C and relative humidity of 44%-53% to have 10. 5% LOSSES which has been confirmed by the lowest LOSSES observed in the corn plan (10%). Moreover, the high value of the determination coefficient demonstrates a high correlation between measured and predicted data.

In order to eliminate the overlapping time of rapeseed HARVESTING and rice transplantation in Guilan province, and to provide appropriate solutions to reduce yield LOSSES through seed loss, the present experiment was conducted as a factorial plots in a completely randomized blocks design with three replications at the Rice Research Institute of Iran in Rasht. The main plots in the present experiment consisted of the interaction of two ethephon foliar application factors at two levels (non-consuming and consuming 280 gram per hectare) and foliar application time at three levels ( podding, early grain filling, grain filling completion) and subplot including HARVESTING time in three phases, physiological maturation, 10 and 20 days after the physiological maturity. The results showed that ethephon foliar application with a mean time of 192 days reduced 8 days growth period compared to control treatment with an average time of 200 days. Also, erosion time (194. 6 days) was higher than early grain filling (196. 3 days) and seed filling completion with 197. 1 days for early maturity traits. The effect of harvest time on number of pods per plant, one-thousand grain weight, grain yield, oil percentage was significant. According to the results, ethephon foliar application caused 12 percent increase in grain yield and 0. 7 percent increase in oil in later HARVESTINGs. The interaction effect of foliar application, foliar application time and harvest time on seed yield was significant. Ethethenol soluble foliar application at the time of podding, with the lowest grain loss, was 202. 8 kilogram per hectare as the best experimental treatment.