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Sunflower, one of the most important crops, is produced in many countries to meet especially for edible oil demand. Since the sunflower plant is affected by many factors, such as the amount of rain and air temperature, the yield changes from year to year, which has adverse effects on the balance between demand and supply. Because of the product produced in many countries is not enough; it has to be imported. Turkey is one of the world's leading sunflower importers. The yield must be accurately estimated for the imported quantity to be correct. Importing in large quantities causes inventories, while small quantities cause the sunflower oil demand to not be met. It is used methods such as the direct method, simulation, and remote sensing to estimate sunflower yield. However, these methods have some shortcomings. In this article, machine learning methods, such as decision tree (DT), support vector machine (SVM) and random forest (RF), are used for production prediction. In order to increase the effectiveness of the methods, the values of the hyperparameters are determined by Halving Grid Search (HGS) method that is tuning method. The methods were implemented in Edirne, which is among the province with the highest sunflower yield in Turkey. The results were evaluated with ANOVA method and performance evaluation criteria, MAE, MAPE, RMSE, and R2. The R2 values obtained for the test data were determined as 0.92, 0.68 and 0.80 for the DT, SVM and RF methods, respectively. In addition, the number of combinations and execution times were compared using the grid search method and the HGS method for the DT method that gave the best results. While 644204 combinations were solved in 4608 seconds with grid search, 5324 combinations were solved in 23 seconds with HGS. Thus, DT method, providing the prediction with the lowest error, is determined a suitable method for sunflower yield prediction and then accurate buying decision making. [ABSTRACT FROM AUTHOR]

The paper analysed the input costs on the sunflower production at Mkalama district in Singida region using variables prices of fertilizer, plough, pesticide, land hired per acre, labour hired, hoe, improved seed (50kg) and Local seed (50kg). For this aim, descriptive statistics and an econometric analysis was conducted in 120 randomly selected sunflower farmers in Mkalama district. Descriptive statistics and OLS regression model were used to analyze the extent of input costs on the sunflower production by respondents. The results revealed that fertilizer, plough, labour hired and Local seed (50kg) inputs had the highest average total cost of inputs. The results of econometric model showed that fertilizers, ploughs, pesticides, land hired per acre, hoes and improved seed (50kg) were the most important inputs, significantly contributed to total production of sunflower seeds; While, the use of labour hired and Local seed (50kg) has negative relationship with output of sunflower. The paper found out that price per bag of fertilizer, price per plough, price per pesticide and price per acre of land hired are positive and statistically significant influence on the sunflower production (Beta= 0.535, 0.302, 0.502, 0.197, P>0.001). The paper concluded that major problems confronting sunflower production were found to be inputs cost which always affects the yield of sunflower. This paper recommended that the Government of Tanzania should enhance the productivity of the agricultural sector through the subsidies provision of the required inputs, which would minimize the total cost of production and speed up the productivity process of sunflower in Tanzania. [ABSTRACT FROM AUTHOR]

Sunflowers have emerged as a significant global crop with extensive economic, agricultural, and nutritional significance. This article presents a comprehensive analysis of sunflower production in the Autonomous Province of Vojvodina, Serbia, delving into key trends, challenges, and opportunities within the industry. Serbia, being a prominent player in the European sunflower market, has been influenced by its diverse agricultural landscape and its commitment to sustainable practices, shaping the dynamics of sunflower cultivation and oil production. The study thoroughly investigates production statistics, regional disparities, and the influence of external factors on sunflower farming and market dynamics in Vojvodina. Data from reputable sources such as the FAO, USDA, and COCERAL at the European level are utilized, along with information on sunflower production and oil prices obtained from the Statistical Yearbooks of the Statistical Office of the Republic of Serbia. The findings of the study revealed a notable rise in harvested areas, yield, and overall production during the observed period, concurrent with shifts in the global market. Additionally, the price of sunflower oil demonstrated an upward trend, reflecting these market dynamics.

Considering the growing pressure of the edible oil imports bill on Pakistan’s national accounts, the significance of sunflower cultivation is gaining more attention to meet the domestic edible oil demand. Given the declining area for sunflower production, this study explored the factors of economic and environmental inefficiencies affecting sunflower growers in Pakistan. The study adopted the epsilon-based measure (EBM) model at the first stage and the Tobit truncated regression model at the second stage to precisely estimate the economic and environmental inefficiencies in the data collected from 240 sunflower growers. Results found that out of 240, 69.9% of the sunflower growers are economically inefficient, while the average environmental inefficiency of sunflower growers is 56.3%. The findings further revealed that farmers’ age, cultivated land, and market distance are the driving factors of farmers’ economic and environmental inefficiencies. However, formal education, farming experience, and access to agricultural extension services decreased the farmer’s inefficiencies. Based on the present study’s findings, diverse policy options are presented to address the problem of contraction of the area under sunflower production.

In this study, sunflower's cultivation area, production quantity, average yield and foreign trade in Turkey and World have been studied dividing the time from 1980 to 2000 into five-year terms. The main countries growing sunflower are Russia, Ukraine, and Argentina. Turkey accounts for the 13% of the total sunflower production of the World. The quantity of sunflower production in the World has increased as the cultivation areas increased during the terms mentioned above. However, our Country has become an importer country in recent years as the area of cultivation decreased. The cultivation area and the quantity of production of sunflower may increase if the market price of sunflower becomes high enough to encourage the cultivation of sunflower and if the markets in which farmers can sell their products easily can be established. [ABSTRACT FROM AUTHOR]

The aim of the study is to analyse the efficiency of input use in sunflower production in Karatay district. Turkey ranks 10th in sunflower production in the world and Konya province has 13.39% capacity of sunflower production in Turkey, placing the 2nd place in terms of production. 97% of sunflower produced in Konya province is sunflower for oil. Data used in this study was determined as 51 enterprises manufacturing sunflower according to the Stratified Sampling Method. The economic efficiency results of sunflower production were calculated with Data Envelopment Analysis (DEAP) method. The total Gross Production Values (GPV) obtained from the enterprises is 50,221.43 $, the GPV acquired from the sunflower production is 23,844.70 $, the total gross profit is 36,927.29 $ and the sunflower gross profit is 18,285.16 $. According to the efficiency results, economic efficiency was found to be 0.604, resource efficiency was 0.604, technical efficiency was 0.868, and pure efficiency was 0.922 while scale efficiency was 0.942. It should be ensured that enterprises use their resources effectively. Information meetings should be held for enterprises on resource use.

The paper analyzes the trends in the development of industrial crop production in the case of sugar beet and sunflower in Serbia from 1976 to 2013. Grouping of regions (4 regions without Autonomous Province of Kosovo and Metohija) and districts (25 districts) in Serbia in 2013, according to the characteristics of land capacity, production of sugar beet and sunflower and level of development, was carried out by cluster analysis. Based on the median value of the important characteristics of available land capacity, production volume and economic development in municipalities, I-distance method were ranked districts in Serbia from 1 to 25. Similarities between the sugar beet and sunflower production regions in Serbia were determined by the method of complete-linkage clustering, and the results were presented in the dendrogram. According to data for 2013 it was found that 99.8% of sugar beet production and 93.9% of sunflower production in Serbia comes from the Vojvodina region. The average yields per hectare for analyzed crops in the areas of the Vojvodina region, on average, were by up to 10% higher compared to the yields in Serbia. According to the characteristics of land capacity and production, areas of the Vojvodina region belong to the highest rank 1-7, while according to the characteristics of the development level, these areas belong to rank 2-13.

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The paper presents the developed software for statistical analysis of time series on crop production, extracted from multidimensional database. The software can be used by statisticians, economists and agricultural specialists to facilitate their access to statistical data and analytical methods. The created algorithm updates automatically the database using public online sources. The sunflower yields by regions and their sustainability have been studied. Hierarchical clustering of Bulgarian regions is presented graphically. [ABSTRACT FROM AUTHOR]

This study applies a Data Envelopment Analysis (DEA) approach to analyze the technical and scale efficiencies of farmers with respect to energy use for oilseed sunflower production in Golestan province, Iran. This study also helps to segregate the efficient and inefficient farmers, identify the wasteful usage of energy by inefficient farmers and to suggest reasonable saving of energy. The results revealed that total operational energy of 6771.1 MJ ha-1 was consumed for sunflower production and the irrigation operations had the highest share. About 64% of farmers were technically efficient and the mean efficiency of farmers was found to be 0.85 and 0.94 under constant and variable returns to scale assumptions, respectively. The results also revealed that, by raising the performance of inefficient farmers to the highest level, on average, about 9.3% of total operational input energy could be saved. Moreover, energy saving from irrigation operation had the highest share (76.9%). From this study improvement of timing, amount, and reliability of water applications and utilization of new irrigation systems with high efficiency is suggested to improve the energy use efficiency and to reduce the environmental impacts. [ABSTRACT FROM AUTHOR]

About 65% of sunflower production in Turkey, which is the world's 11th largest producer of sunflower based on the FAO data, occurs in the Thrace region. The biggest problem in sunflower areas in the Thrace region is broomrape ( Orobanche cernua L.). Three types of sunflower cultivars are planted in the region, namely hybrids genetically resistant to broomrape (GRH), nonresistant ones (NRH) and IMI (Imidazolinone) herbicide resistant ones (IMIH), which control both broomrape and key weeds in sunflower production. The adoption situation and the performances of these three sunflower hybrid types were studied in the research. The research data was obtained from 571 agricultural enterprises, which were determined based on the Stratified Random Sampling Method in the Thrace region. Sunflower is grown on 42% of the total cultivated land surveyed in the research and accounts for 23% of the total agricultural revenue. The adoption rate and degree of IMIH and GRH sunflower hybrids were calculated to be over 90%. The highest yield (1,915.10 kg ha-1) was obtained from GRH hybrids in the research areas. A high yielding potential and easier weed control are seen by the farmers as being among the most important factors for choosing a particular type of sunflower seed. Statistical differences were observed among the sunflower hybrid types based on seed yield, revenue, and seed amounts. The highest net profit was obtained from GRH hybrids in the study. Additionally, based on the results, NRH hybrids were found to be more profitable than IMI hybrids. [ABSTRACT FROM AUTHOR]