جستجوی مقالات مرتبط با کلیدواژه "آنالیز خط مرزی" در نشریات گروه "زراعت"

Food security is one of the most important challenges facing humankind. Therefore improving crop yields are essential to meet the increasing pressure of global food demands. The Decreasing the area of high-quality land, increasing fertilizer use, and its effect on the environment indicate that we need to develop new strategies to increase grain yields with less impact on the environment. One strategy that could help address this concern is by narrowing the yield gaps using improved management. Therefore, the present study was conducted in Khorramshahr region for recognition of best management practices, percentage of the affected fields, estimation of wheat and rapeseed yield potential and gaps using boundary line analysis.

To quantify the production and estimation of wheat and rapeseed yield gap in Khoramshahr, Farm management information of 60 wheat fields and 57 rapeseed fields in the years 2018-2019 were collected. The information was collected through continuous farm monitoring during the growing season as along with face to face interviews with the farmers. Farms were selected by consulting with agricultural service centers expert in Khorramshahr districts. Based on the available information at the agricultural service centers, only farms, which is different in terms of acreage, cultural practices and harvesting operations were selected. In this study, by plotting the distribution of the yield obtained in each field as the dependent variable against the independent variables (crop management activities), using SAS software and an appropriate function was fitted on the upper edge of the data distribution.

Using this boundary line analysis method, the average yield, attainable yield and yield gap of wheat were obtained as 3740, 5455 and 1715 kg per hectare respectively. The yield gap percentage in wheat was 31.5% and rapeseed was 48%, which indicates the high effectiveness of wheat and rapeseed in relation to the use of appropriate management methods. The analysis of the investigated data in wheat fields showed that in order to achieve the achievable yield, 258 kg per hectare of seeds, the use of Mehrgan variety, the planting date until October 24, the amount of 280 kg per hectare of nitrogen fertilizer, the consumption of at least 100 Phosphorus fertilizer per hectare was at least 6 kg with irrigation and consumption of at least 70 kg of potassium fertilizer. Also, according to the frontier line analysis, the average yield of rapeseed farmers is 1663 kg, they can achieve a yield of 3197 kg per hectare by improving crop management, and for this purpose, the following measures should be taken into account: 1) consuming a maximum of seven kilograms of seeds per hectare 2) Planting date up to 17 November 3) Use of at least 300 kg of nitrogen fertilizer 4) At least 42 kg of phosphorus fertilizer 5) Use of Hyola 50 variety.

In this study by examining several important management factors in growing wheat and rapeseed, optimal requirements of each factor to achieve the highest yield was determined by borderline analysis. In addition, the percentage of farms that had poor management as well as wheat and rapeseed yield potential and gaps in Khorramshahr. Yield responses to management practices were evaluated and studied by means of borderline analysis. Best management practices could be devised using study findings to realize the highest yield potential.

One of the main problems for rice production is the large difference between farmers' actual yields and attainable yields. Therefore, it is important to identify the limiting factors on yield and yield gap. In this research, all performed management practices from seedbed preparation to harvesting in 228 paddy fields of local rice cultivars in the east, central and west parts of Mazandaran province, Iran were surveyed through field monitoring in 2015 and 2016. The results showed that the variables of certified seed, seedling age, and potassium application, nitrogen application after flowering, harvest time and pest problem were introduced into the comparative performance analysis (CPA) equation. The actual yield of the field and the calculated yield potential were estimated 4456 and 6642 kg.ha-1, respectively, hence the yield gap was estimated 2186 kg.ha-1. In the boundary line analysis (BLA), by fitting one line on the upper edge of the data, it was determined that the response function as a dependent variable to independent variables on seed rate, transplanting date, planting density, nitrogen application. Moreover, basal nitrogen application, nitrogen application in vegetative and after flowering stages had a positive piecewise function. The seedling age variable, phosphorus and potassium application and the number of seedling per hill followed a negative piecewise function. However,, four variables including the lodging, pests, diseases and weeds problems followed a linear function. According to BLA, the average yield was 5755 kg.ha-1 with a yield gap of 1207 kg.ha-1. An average relative yield and relative yield gap were estimated 79.8% and 20.90%, respectively. Given that the calculated yield potential in this analysis in three regions was obtained from the actual data of each field, it can be concluded that the yield potential is dependent on the region and is attainable.

In the recent year, due to increasing concerns about the future food security, researches in this field are growing globally and it requires to use proper statistic methods for estimation the amount of yield gap and determination of it’s causes. In dryland management, optimization of vegetative growth before flowering in order to maximize the utilization of available water in the soil is a fundamental principle and consequently management factors such as planting date, seeding rate and amount of fertilizer nitrogen (N) use can determine the amount of vegetative growth before flowering. Boundary line analysis is a statistical method that can quantify the response of yield to an environmental or management factor in a situation in which other parameters are variable. The objectives of this study were to introduce, use and comparison of two methods for fitting boundary line to determine the best managements and simultaneously estimate potentials and calculate wheat yield gap in three county of the Golestan province include Aghala, Gomishan and Kalaleh. One, the common method based on the least squares (LS) method and another method based on linear programming (LP) so that no point is fall above the drawn line. For this study, the required information were collected from 332 wheat field during two growing season of 2014 and 2015 in Aghala, Gomishan and Kalaleh. The investigated management factors included planting date, seeding rate and amount of nitrogen fertilizer (N) use (at the base and the road). To fit a boundary line using LS method, a curve was fitted through the maximum yield points based on the least squares method. However in LP method, a curve was fitted on the top edge of the data so that any point is not fall above the drawn line. For this purpose, the parameters of the function were changed so that the total remaining was at the lowest level, in the condition that no single negative remaining was left. Then, the optimum of each specific management factor was recognized and finally with estimating potential yield and minus the average yield in each county, yield gap was calculated for each factor and in whole. The results show the optimum of each specific management factor to reach the potential yield and optimum planting date, seeding rate and optimum nitrogen (N) use in each county were determined. The average wheat yield in drylands of Aghala, Gomishan and Kalaleh was about 2600 kg ha-1 and also potential yield was about 4700 kg ha-1 according to LS method and 4800 kg ha-1 according to LP method. So there is a yield gap about 2000-2100 kg ha-1 (44-45%). It should be noted that these results are not conclusive and it would be required to several years of testing to achieve the optimal range of each region. LP method doesn’t require dividing independent factor and determining the boundary point, and also the fitted curve done with participate of all the data. In other words, all points have their impacts on the drawn curve and this is the advantage of this method. However the lack of involvement of user experience to choice the ideal points for fitting the curve would be the weakness of this method, it seems that each of these methods in certain situations -depend on the type and distribution of data- can be useful. So user after drawing the scatter plot of data should choice the best method to fit line to the data.

To investigate the factors affecting soybean yield loss in comparison to the attainable yield, an experiment was conducted in 50 fields in the township of Kalaleh in summer of 2016. Sampling of weeds were taken in early growing season of soybean based on W pattern. In this study all agronomic management information including land area, farmers experience, seed bed preparation, sowing date, cultivar and provided seed source, sowing methods, seed rate, weeds control methods, amount and time of applied herbicide and wheat harvest time were collected during growing season by preparing questionnaire and complete them with farmers. In evaluated fields, 13 weed species belonged to 11 families were observed. Among the various parameters, field area, seed rate, certified seed application, planting date, Asian spider flower (Cleome viscosa L.) and Johnson grass (Sorghum halepense L.) had the significant effects on soybean yield. The minimum and optimum predicted yields with model were 1039 and 2036 kg/ha-1, respectively. Thus there was 996 kg/ha-1 gap between minimum and optimum predicted yield in this township. Results showed certified seed (23.07 percent), delay planting date(15.04 percent), low seed rate (11.54 percent), low field area(7.62 percent), present of Johnson grass(12.47 percent) and asian spider flower(30.25 percent) weeds were the most effective factors on this yield gap. With optimizing mentioned agronomic managements could reduce yield gap and increased yield to double.

In this study, collecting of management information from about 700 wheat farms in Golestan province was conducted during two growing season of 2013-2014 and 2014-2015. In each of region, potential yields, the optimum crop management and simultaneously the percentage of wheat farms out of the optimal range were identify in both irrigated and rainfed conditions using boundary line analysis. So, the information were analyzed in three part of irrigated, high- and low-yield rainfed conditions. By plotting farm’s yield data scatter, against management factors, highest yields in different levels of input or management factors were selected and a boundary function was fitted to the upper boundary of data points. According to the results, potential yield for irrigated, high- and low-yield rainfed wheat were estimated equal to 6816, 5791 and 3932 kg ha-1 with a yield gap of 42, 31 and 50%, respectively. The optimum ranges of sowing date, seeding rate, plant density, frequency and the amount of nitrogen fertilizer applied, the amount of nitrogen applied after sowing, the amount of phosphorus (P2O5) and potassium fertilizers (K2O) applied and irrigation frequency were determined according to the results. Consider the optimum managements, farmers in each region can shrink the yield gap and reach potential yield result in increasing the amount of wheat production in Golestan province.