Nutrient deficiency in alkaline calcareous soils under arid and semi-arid climates limits productivity. The current study evaluated the effectiveness of biofertilizers in a growth promotion assay under controlled environment, followed by their testing under a nutrient-deficient field for two consecutive years. The field experiment evaluated three formulations named BF-1 (IA6), BF-2 (IA16) and BF-3 (IA6 + IA16) in a randomized complete block design (RCBD) with three blocks/replications under factorial settings. After 3 days of sowing at 30 +/- 1 degrees C, BF-3 showed 83.3% germination, while under cool germination at 18 +/- 1 degrees C, germination was 78.7%. However, the formulations showed non-significant differences at 30 +/- 1 degrees C. Similarly, under field conditions BF-3 caused significant improvements in plant height, number of sympodial branches plant-1, number of monopodial branches plant-1, boll weight, seed cotton yield, SPAD value, superoxide dismutase (SOD) activity, peroxidase (POD) activity, catalase (CAT) activity and POX activity by 14%, 13%, 17%, 11%, 20%, 19%, 13%, 11%, 13% and 11%, respectively, compared with C1 (negative control) in first year. Similar results were also observed during the second year by BF-3. It is concluded that BF-3 can potentially enhance cotton productivity in nutrient-deficient soils; thus, it can help farmers in sustainable farming systems.

Maize is the most staple food crop produced in sub-Saharan Africa which its cultivation has been expanding with time however, the productivity remains low. Low productivity of maize in Africa is contributed by different challenges such as pests and diseases, drought, floodings which are associated with the effects of climate change. Drought is among the critical constraints in maize production causing yield loss up to 100% under extreme conditions. With these challenges researchers have come with some of the promising technologies that help to reduce the effect of climate changes for instance breeding new climate resilience maize varieties which using modern breeding tools like marker assisted backcrossing, quantitative trait loci, genomewide association studies, double haploid, gene editing, genomic selection and high throughput phenotyping. These tools map traits of target for introgression to recipient varieties thus reducing time of breeding cycles. Some of the climate of improvement for climate resilience include drought and heat tolerance, high stay green with low less leaf rolling, stemborer and fall armyworm tolerance, water-use efficiency and high grain yield. Effort have been done by CIMMYT in collaboration with National Agricultural Research Institutes have developed climate resilient crop varieties, however, with pace of climate change there is more effort to diversify varieties for sustainable climate resilience that will strengthen food security in sub-Saharan Africa which is the most vulnerable to climate change. There is a need to integrate approaches to cope with climate change such as use of next-generation genomic technologies, digital agriculture and data-driven approaches, strengthening seed systems, integration of farmer preferences and socioeconomic factors into the breeding process, and adaptive breeding programs based on climate scenarios. These will shorten breeding cycles and come up with new technologies that cope with variation of climate at certain intervals.

Calcareous soils pose significant constraints to plant nutrient uptake due to high pH and calcium carbonate content. This study evaluated the effects of biochar (BC), leonardite (L), and polyacrylamide (PAM), applied individually and in combination, on early maize (Zea mays L.) growth and selected soil properties in calcareous soil. A pot experiment was conducted under controlled conditions using calcareous soil amended with BC, L, and PAM. Soil pH, electrical conductivity (EC), organic carbon (OC), aggregate stability (AS), and penetration resistance (PR) were determined. Plant growth parameters included plant height, stem diameter, SPAD values, and total nitrogen (TN). Across treatments, SPAD values ranged from 35.20 to 43.90, TN from 0.79 to 1.62

Efficient use of water and energy resources is increasingly important for sustaining agricultural production under growing food demand and climate change pressures. This study evaluated the effects of irrigation technology on energy performance, input-related carbon footprint, and water scarcity footprint in irrigated silage maize production. Field-based data were collected over three consecutive growing seasons (2022-2024) from a large commercial farm in Ankara Province, Central Anatolia, T & uuml;rkiye, where silage maize was produced under sprinkler and center pivot irrigation systems. Energy performance was quantified using an input-output energy analysis framework, input-related carbon footprint was estimated using emission factors associated with agricultural inputs and field operations, and water scarcity footprint was assessed using the AWARE characterization factor for T & uuml;rkiye. Based on three-year mean values, center pivot irrigation increased dry matter yield by 1.48%, energy use efficiency by 16.89%, energy productivity by 16.88%, and net energy by 3.27%, while reducing specific energy by 14.38% compared with sprinkler irrigation. The input-related carbon footprint per unit of dry matter yield decreased by 22.22% under center pivot irrigation. In contrast, the mean water scarcity footprint was identical between the two systems, and its pattern varied by year: sprinkler irrigation showed lower values in 2022 and 2023, whereas center pivot irrigation showed a lower value in 2024. Overall, center pivot irrigation improved energy performance and reduced input-related carbon footprint under the evaluated commercial farm conditions, while water scarcity footprint was mainly governed by irrigation water volume and the regional AWARE factor rather than irrigation technology alone. These findings provide field-based evidence for irrigation planning and resource-use assessment in semi-arid silage maize production systems.

The concept of water footprint (WF) has become an important indicator of agricultural water use efficiency, especially in semi-arid regions where water scarcity threatens sustainable crop production. Sorghum × Sudangrass (SSG) hybrid is increasingly grown in these environments for its drought tolerance and high biomass yield. However, the influence of irrigation strategies on the balance between blue and green WF components remains insufficiently understood. This study aimed to assess the WF of SSG under different irrigation regimes by integrating field-based measurements with CROPWAT model simulations. Experiments conducted in Konya Province, Türkiye, during the 2021 and 2022 cropping seasons showed that CROPWAT predictions of crop evapotranspiration (ETc) generally agreed with observed values, though some discrepancies appeared under lower irrigation levels. Over the two-year period, measured blue WF values for irrigation treatments of 100

This study evaluated the impact of different irrigation levels on ethanol yield and water use efficiency (WUE) of sorghum × sudangrass hybrid (SSG) under semi-arid conditions. The aim was to optimize water use for sustainable bioethanol production in water-scarce environments. A two-year field experiment (2021–2022) was conducted using four drip irrigation treatments corresponding to 100

Sorghum is a crucial crop for sustainable agriculture due to its drought resistance, low carbon footprint, and diverse applications in food, feed, and bioenergy. However, understanding the impact of climate change on sorghum production is essential for ensuring its future sustainability. This study conducts a comprehensive bibliometric analysis of scientific publications related to sorghum and climate change using the Web of Science (WoS) database, covering the period from 1984 to 2024. A total of 1053 relevant papers were analyzed, revealing an average annual growth rate of 12.73% and an average citation count of 32.02 per document. Most of the publications (83.5%) were research articles, while 9.7% were review papers. Among the contributing researchers, Prasad PVV emerged as the most productive author based on an h ‐index of 13, whereas the United States was identified as the most influential country, contributing 235 documents and 13,750 citations. Keyword clustering analysis identified five major research themes, including sustainable energy and environmental impacts, climate resilience, socioeconomic effects of climate change, and key crops. The findings of this study offer valuable scientific insights to guide future research and policymaking on climate change and sorghum sustainability.

In this study, the effect of morphological traits on fresh herbage yield of sorghum x sudangrass hybrid plant grown in Konya province, which is the largest cereal production area in Turkey, was analyzed with some data mining methods. For this purpose, Artificial Neural Networks (ANN), Automatic Linear Model (ALM), Random Forest (RF) Algorithm and Multivariate Adaptive Regression Spline (MARS) Algorithm were used, and the prediction performances of these methods were compared. Plant height of 251.22 cm, stem diameter of 7.03 mm, fresh herbage yield of 8010.69 kg da-1, crude protein ratio of 9.09%, acid detergent fiber 33.23%, neutral detergent fiber 57.44%, acid detergent lignin 7.43%, dry matter digestibility of 63.01%, dry matter intake 2.11%, and relative feed value of 103.02 were the descriptive statistical values that were computed. Model fit statistics, including coefficient of determination (R2), adjusted R2, root of mean square error (RMSE), mean absolute percentage error (MAPE), standard deviation ratio (SD ratio), Mean Absolution Error (MAE) and Relative Absolution Error (RAE), were used to evaluate the prediction abilities of the fitted models. The MARS method was shown to be the best model for describing fresh herbage yield, with the lowest values of RMSE, MAPE, SD ratio, MAE and RAE (137.7, 1.488, 0.072, 109.718 and 0.017, respectively), as well as the highest R2 value (0.995) and adjusted R2 value (0.991). The experimental results show that the MARS algorithm is the most suitable model for predicting fresh herbage yield in sorghum x sudangrass hybrid, providing a good alternative to other data mining algorithms.

The aim of this research was to define the energy use and greenhouse gas (GHG) emissions associated with the production of sorghum x sudan grass (SSG) hybrids. Energy use efficiency (EUE) indicators and GHG ratios were computed for the 2021 and 2022 growth seasons. Energy inputs, including diesel, fertilizers, seeds, and agricultural machinery, were assessed based on their energy equivalents, while energy outputs were calculated based on the energy value of the biomass produced. The analysis differentiated between direct energy inputs (human labor, diesel, irrigation, and electricity) and indirect energy inputs (machinery, fertilizer, and seed). Energy inputs were further divided into renewable energy sources (human labor, water, seeds) and non-renewable energy sources (fertilizer, fuel, and electricity). GHG ratios were determined by calculating the carbon footprint of the inputs in the production process. The average energy input and output for SSG hybrid production were computed to be 20445.65 MJ ha-1 and 370040.77 MJ ha-1, respectively. The research defined an EUE of 18.10, with a specific energy of 1.02 MJ kg-1, an energy productivity of 0.98 kg MJ-1 and a net energy value of 349595.12 MJ ha-1. Direct and indirect energy inputs were computed to be 12901.65 MJ ha-1 (63.10%) and 7544 MJ ha-1 (36.90%), while renewable and non-renewable inputs were calculated to be 4718.30 MJ ha-1 (23.08%) and 15727.35 MJ ha-1 (76.92%), respectively. The total GHG emissions were 1324.55 kgCO2-eq ha-1 and the GHG ratio was 0.07 kgCO2-eq ha-1. The production profitability ratio was calculated as 3.35. SSG hybrid production proved to be highly profitable for the 2021 and 2022 production seasons in terms of EUE.

This research was carried out to determine the potential for using the pulp of 10 different sorghum x sudan grass hybrid varieties (Aneto, Greengo, Jumbo, Master BMR, Nutri Honey, Nutrima, Sugar Graze II, Supergraze 1000, Süper Su 22, Tonka) used to obtain ethanol in Bingöl, Eastern Anatolian ecological conditions as silage. Field trials were carried out in 3 replications in 2020 according to the randomized block design. The plants were harvested during the pulping period of the grains. The stems from which the sap was extracted were silaged and left for fermentation at room temperature for 45 days. Feed quality characteristics and organic acid contents were determined in silage materials. Depending on the varieties; silages have a physical score of 7-19, dry matter rate 37.58-50.94%, pH value 3.36-4.30, ADF rate 39.33-50.76%, NDF rate 53.40-66.86%, ADL rate 10.90-13.96%, CP rate 2.76-4.46%, DDM ratio 49.33-50.26%, DMI ratio 1.80-2.36%, RFV ratio 68.66-107.00, net energy value 1.176-1.337, AA ratio 0.11-0.66%, BA ratio 0.76-1.16%, LA ratio 0.07-1.05% and PA ratio was found to vary between 0.0013-0.0026%. As a result, it was concluded that silages made with pulp in cultivars of sorghum x sudan grass hybrid plant can be used more appropriately in cellulosic ethanol production than forage.

The purpose of this study was to ascertain the fresh herbage yield, fertilizer dosage, and plant characteristics of the Sorghum-Sudangrass hybrid grown in arid and semi-arid regions, as well as their interrelationships. For this reason, data from the Sorghum-Sudangrass hybrid were used to assess the predictive performance of several data mining techniques, including CHAID, CART, MARS, and Bagging MARS. Plant traits were measured in Konya and Sanliurfa during 2021 and 2022. The descriptive statistical values were calculated as follows: plant height 306.27 cm, stem diameter 9.47 mm, fresh herbage yield 10852.51 kg/da, crude protein ratio 9.66%, acid detergent fiber 33.39%, neutral detergent fiber 51.85%, acid detergent lignin 9.76%, dry matter digestibility 62.88%, dry matter intake 2.34%, and relative feed value 114.68 (average values). The predictive capacities of the fitted models were assessed using model fit statistics such as the coefficient of determination (R²), adjusted R², root mean square error (RMSE), mean absolute percentage error (MAPE), standard deviation ratio (SD ratio), and Akaike Information Criterion (AIC). With the lowest values for RMSE, MAPE, SD ratio, and AIC (246, 1.926, 0.085, and 845, respectively), and the highest R² value (0.993) and adjusted R² value (0.989), the MARS algorithm was determined to be the best model for characterizing fresh herbage yield. As a solid alternative to other data mining techniques, the MARS algorithm was shown to be the most appropriate model for forecasting fresh herbage production.

The sorghum plant, which is one of the most important plants of the world, was used as material. It was grown in Konya province of Türkiye, which has semi-arid climate conditions. Plant height, fresh weight and dry weight were determined for 11 weeks during the vegetation period. Some growth models were used and the parameters of the models were tried to be defined. The coefficient of determination (R2), Pseudo R2, Mean Squares of Error (MSE) and Akaike Information Criteria (AIC) statistics were taken into account in comparing the performances of the models. It was concluded that the most suitable model was the Gompertz model for plant height, the Von Bertalanffy model for wet weight, and the Log-Logistic model for dry weight. The R2, Pseudo R2, MSE and AIC values of the Gompertz model found suitable for plant height were found to be 0.998, 0.999, 23.162 and 21.013 respectively. The R2, Pseudo R2, MSE, and AIC values of the Von Bertalanffy model, which was found suitable for wet weight estimation, were obtained as 0.995, 0.998, 1817.141 and 41.993 respectively. The R2, Pseudo R2, MSE, and AIC values of the Log-logistic model, which were found suitable for estimating the dry weight of the plant, were calculated as 0.998, 0.9993, 51.007 and 24.784 respectively. It can be suggested that nonlinear mathematical growth models are useful methods in terms of describing important plant characteristics such as plant height, fresh and dry weight, calculating maximum plant height and weight and determining the average growth rate.

This research was conducted in the 2019 and 2020 growing seasons to determine the most suitable sorghum x sudan grass hybrid variety or varieties in terms of dry herbage yield and quality characteristics in Bingöl, which has a semi-humid climate. Dry herbage yield (DHY), crude protein ratio (CP), acid detergent fiber (ADF), neutral detergent fiber (NDF), acid detergent lignin (ADL), dry matter digestibility (DMD), dry matter intake (DMI) and relative feed value (RFV) were determined for ten sorghum x sudan grass hybrid varieties grown in Bingöl University Faculty of Agriculture, Agricultural Application and Research Center according to coincidence blocks experimental design with 3 replications. In the varieties examined in the research, DHY varied between 12216-16397 kg ha-1, CP 5.15-8.15 %, ADF 39.43-45.85 %, NDF 51.45-62.89 %, ADL 9.20-13.15 %, DMD 53.18-58.18 %, DMI 1.91-2.33 % and RFV 78.68-104.30. According to the two-year combined averages, the Master BMR variety produced a higher dry herbage yield than the other varieties. Among the varieties, the highest CP, DMI, RFV, and the lowest NDF were obtained in the Master BMR variety. It was concluded that the Master BMR variety gave high values in terms of dry herbage yield and quality characteristics in Bingöl province's ecological conditions.

The sorghum x sudangrass hybrid is significant as a biofuel crop due to its high biomass production, drought tolerance, adaption ability to various climatic conditions, and high sugar content in its stems. This study aimed to determine the effects of six different nitrogen dose treatments on ethanol yield, yield parameters, and fertilizer use relationships in sorghum x sudangrass hybrid plants in two locations in 2021 and 2022. The experiment was established according to the randomized block design with three replicates. Nitrogen treatments were applied as N0 (0 kg da-1), N5 (5 kg da-1), N 10 (10 kg da-1), N 15 (15 kg da-1), N 20 (20 kg da-1), and N 25 (25 kg da-1). Juice ethanol yield (JEY), lignocellulosic ethanol yield (LEY), and theoretical ethanol yield (TEY) values varied between 123.8-219.0 L da-1, 522.2-955.1 L da-1, and 646.0-1174.2 L da-1, respectively. JEY, LEY, and TEY values increased as the amount of nitrogen increased. The correlation analysis found a high positive relationship between all traits except acid detergent lignin. As a result of the orthogonal comparison, it was found that the nitrogen dose amount should be increased for JEY, LEY, and TEY. Principal components-biplot analyses explained 92.9% of the relationships between the studied parameters and the nitrogen dose levels. This study, conducted over two years and in two locations, determined that sorghum x sudangrass hybrid cultivation could be realized in terms of bioethanol yield under different nitrogen dose levels and that the ethanol yield potential is high.

Renewable energy sources are the most effective and cheapest method in combating climate change. Biomass, which is one of the renewable energy sources, is also one of the raw materials of biofuels. Sorghum x sudan grass hybrid, which is drought tolerant and has a short vegetation period, is one of the biomass sources. This study was carried out to determine the ethanol yield of sorghum x sudan grass hybrid plant grown in an area with a semi-humid climate and to determine the environmental impacts of biomass. Environmental impacts were assessed using the life cycle assessment method. Environmental impact categories are divided into 11 categories according to the CML-IA Baseline model. As a result, the biomass yield was 49888 kg ha-1 and the ethanol yield was 1674.1 l ha-1. According to the life cycle impact category of sorghum x sudan grass hybrid biomass production, it was determined that the highest environmental impact was 79.21%, causing the marine aquatic ecotoxicity. According to the life cycle interpretation, it was determined that it caused a global effect with a rate of 83.87%. In addition, the global warming value was calculated as 0.195 kg CO2-eq kgbiomass-1 (9728.16 kg CO2-eq ha-1). It has been determined that the agricultural phases that have the most negative impact on the environment are irrigation and fertilization.

Amaç: Bingöl ekolojik koşullarında yetiştirilen 10 farklı sorgum x sudan otu melezi çeşidinin (Aneto, Greengo, Jumbo, Master BMR, Nutri Honey, Nutrima, Sugar Graze II, Supergraze 1000, Süper Su 22 ve Tonka) silaj kalitesinin belirlenmesi amacıyla 3 tekerrürlü olarak yürütülmüştür. Materyal ve Yöntem: Bitkilerdeki daneler hamur olum döneminde iken hasat edilmiş, parçalanarak plastik bidonlara doldurulmuş ve oda sıcaklığında 45 gün süre ile fermantasyona bırakılmıştır. Silaj materyallerinde; fiziksel puan (FP), kuru madde (KM) oranı, asetik asit (AA), bütirik asit (BA), laktik asit (LA), propiyonik asit (PA) içerikleri, sindirilebilir kuru madde (SKM) oranı, kuru madde tüketimi (KMT) oranı, nispi yem değeri (NYD), ham protein (HP) oranı, pH, asit deterjanda çözünmeyen lif (ADF) oranı, nötral deterjanda çözünmeyen lif (NDF) oranı ve asit deterjan lignin (ADL) oranı belirlenmiştir. Araştırma Bulguları: Araştırma sonucuna göre; sorgum x sudan otu melezi çeşitleri arasında istatistiki olarak PA içeriği açısından p≤0,05, geriye kalan diğer özellikler açısından ise p≤0,01 düzeyinde önemli farklılıklar bulunmuştur. Sorgum x sudan otu melezi çeşitlerine ait silajların fiziksel puanı 11-20, KM, AA, BA, LA, PA oranları sırasıyla %26.07-36.49, %0.13-0.49, %0.33-1.16, %0.44-1.61, %0.0013-0.0026, SKM oranı %57.93-68.76, KMT oranı %2.40-3.20, NYD 117.26-171.53, HP, ADF, NDF, ADL oranları sırasıyla %5.13-8.16, %25.83-39.73, %37.30-50.33, %6.06-13.00, ve pH değerinin 3.45-4.09 arasında olduğu tespit edilmiştir. Sonuç: Elde edilen verilere göre, sorgum x sudan otu melezi çeşitleri arasında en kaliteli silajın Nutrima çeşidinden alınabileceği tespit edilmiştir.

Bu araştırma, Bingöl Üniversitesi Tarımsal Araştırma ve Uygulama Alanı’nda yetiştirilen 5 farklı dallı darı çeşidinin (Alamo, Cave in Rock, Cloud Nine, Kanlow ve Shawnee) silaj kalitesinin belirlenmesi amacıyla 2020 yılında yapılmıştır. Bitkiler çiçeklenme döneminden 10-15 gün sonra hasat edilmiş, parçalanan bitki örnekleri plastik bidonlara doldurulmuş ve oda sıcaklığında 45 gün süre ile fermantasyona bırakılmıştır. Silaj materyallerinde; fiziksel puan, kuru madde oranı, pH, asit deterjanda çözünmeyen lif (ADF), nötral deterjanda çözünmeyen lif (NDF), asit deterjan lignin (ADL), ham protein (HP), sindirilebilir kuru madde (SKM), kuru madde tüketimi (KMT) oranları, nispi yem değeri (NYD), asetik asit (AA), bütirik asit (BA), laktik asit (LA) ve propiyonik asit (PA) içerikleri incelenmiştir. Araştırma sonucuna göre; incelenen özelliklerin hepsinde dallı darı çeşitleri arasındaki farklılık istatistiki olarak p≤0.01 düzeyinde çok önemli bulunmuştur. Dallı darı çeşitlerine ait silajların fiziksel puanının 7-11 puan arasında, kuru madde oranının %40.21-47.21, pH değerinin 4.32-4.59, ADF oranının %40.72-49.67, NDF oranının %55.65-63.65, ADL oranının %12.50-15.07, HP oranının %4.82-8.42, SKM oranının %50.20-57.17, KMT oranının %1.90-2.17, NYD’nin 73.35-95.57, AA oranının %0.70-1.38, BA oranının %0.02-0.29, LA oranının %1.00-1.86 ve PA oranının %0.012-0.034 arasında olduğu tespit edilmiştir. Elde edilen verilere göre, dallı darı çeşitleri arasında en kaliteli silajın Cloud Nine çeşidinde olduğu tespit edilmiştir.

In this study on common vetch growing in Bingol, Turkey, based on the results of correlation analysis obtained: plant length (0.585) dry herbage yield (0.895), number of seeds per plant (0.100), seed weight (0.120), cut weight (0.212) and the weight of 1000 seeds (0.408) are affected green herbage yield positively, while the harvest index (-0.047) is affected negatively. Similarly, plant length (0.541), green herbage yield (0.895), number of seeds per plant (0.029), seed weight (0.027), cut weight (0.124) and weight of 1000 seeds (0.394) are affected dry herbage yield positively, while the harvest index (-0.169) is affected negatively. According to path analysis results; yield elements that affected respectively, green herbage yield at the highest rate, positively and directly, plant length (0.569), 1000 seeds weight (0.396) and number of seeds per plant (0.316). While green herbage yield (0.895) is affected dry herbage yield positively. For this reason, growing studies to increase the green herbage yield efficiency of common vetch; come to a conclusion that the plant height, the weight of 1000 seeds and the number of seeds in the plant could be used as important criteria.

Bu araştırma, Bingöl ili ekolojik koşullarında yetiştirilecek burçak genotiplerinin tohum verimi ve kalite özelliklerinin belirlenmesi amacıyla 2014 ve 2015 yıllarının yetiştirme sezonunda yürütülmüştür. Araştırmada, 14 adet burçak genotipi [ICARDA orjinli 6 adet, Diyarbakır ve Mardin popülasyonuna ait 3 adet ve Ankara Üniversitesi Ziraat Fakültesi’ne ait 5 adet hat] bitki materyali olarak kullanılmıştır. Araştırma tesadüf blokları deneme desenine göre üç tekrarlamalı olarak kurulmuştur. Araştırmada; tohum verimi, kes verimi, bin tane ağırlığı, ham kül oranı, ham protein oranı, ham protein verimi, ADF ve NDF ile ilgili veriler incelenmiştir. Araştırma sonucunda; genotiplerin tohum verimi 50.3-82.6 kg/da, kes verimi 354.3-535.9 kg/da, bin tane ağırlığı 32.4-46.6 g, ham protein oranı %5.8-9.5, ham protein verimi 20.6-39.5 kg/da, ham kül oranı %8.8-13.0, ADF oranı %35.7-39.8 ve NDF oranı %43.9-50.0 arasında değişim göstermiştir. Bu sonuçlara göre Bingöl ve benzeri ekolojik koşullarda tohum verimi için 6 ve 13 nolu genotip, kes verimi için 5 ve 6 nolu genotip, yüksek ham protein verimi için 6 ve 10 nolu genotip, düşük ADF ve NDF oranı için 1 nolu genotiplerin ekilmesi tavsiye edilmektedir.

The seed oils of twenty Sanguisorba minor (Leguminosae) genotypes were investigated for their oil contents and fatty acid compositions. The oil contents of the seeds were found to be between 8.85% and 15.66%. The fatty acid compositions of these twenty different genotypes were determined by the GC of the methyl esters of their fatty acids. The oilseeds of Sanguisorba minor genotypes contain palmitic acid as the major component of their fatty acids, among the saturated acids, with small amounts of steraric acid. The major unsaturated fatty acids found in the oilseeds of the genotypes were oleic, linoleic and linolenic acids. In this study, the total saturated fatty acids of Sanguisorba minor genotypes were between 6.40% and 15.84% while the total unsaturated fatty acids were between 84.16% and 93.60%.