Records of Agricultural and Food Chemistry Articles

The Apiaceae botanical family and the Pleurospermum genus have been recognized as valuable reservoirs of natural antioxidants, finding extensive applications in medicinal, pharmaceutical, nutraceutical, cosmeceutical, and culinary realms. This is attributed to their rich array of bioactive phytochemicals and their diverse range of biological activities. Essential oils are complex mixtures of hydrocarbons, and their oxygenated derivatives arise from two different isoprenoid pathways. Glandular trichomes and other secretory structures, specialized secretory tissues primarily distributed on the surface of plant organs, notably flowers and leaves, generate essential oils. Essential oils play a crucial ecological role within the plant. In addition, since ancient times, essential oils have been used in many different traditional healing systems worldwide because of their biological activities. Moreover, this review will attract the attention of scientists from aroma industries, nutritionists, and pharmaceutical industries to improve the use of essential oils for nutraceutical purposes with commercialization to aid and promote healthy lifestyles, wellness, and well-being.

Astragalus L. is the largest flowering genus of the Fabaceae family and is represented by approximately 3000 species worldwide. This study aims to determine the anti-aging and anti-diabetes effects of Astragalus leporinus, A. distinctissimus, and A. schizopterus, three endemic species in Anatolia. The anti-aging effects against elastase and collagenase enzymes and the anti-diabetic effects against α-glucosidase and α-amylase enzymes were determined. Some triterpene contents were also determined by GC-MS. Ursolic acid (85.86 mg/g extract) and oleanolic acid (49.11 mg/g extract) were detected in the acetone extract of A. schizopterus species, and only (2.10 mg/g extract) oleanolic acid was detected in the ethanol extract. α-Amyrin (5.46 mg/g extract), oleanolic acid (6.09 mg/g extract), and ursolic acid (8.95 mg/g extract) were identified in the acetone extract of A. distinctissimus species. In terms of anti-aging, A. leporinus var. hirsutus ethanol extract has shown the highest activity in elastase and collagenase inhibition activity methods (inhibition %: 17.26±0.18 and 11.47±0.15, respectively), standard reference substances (oleanolic acid and epicatechin gallate, inhibition %: 43.80±0.76, 84.08±0.49, respectively). When it is evaluated in terms of anti-diabetic, it was determined that acetone extracts of A. schizopterus and A. distinctissimus species inhibited α-glucosidase at a higher level than acorbose, which was used as the standard reference substance, at all concentrations. In addition, it has also been observed that both acetone and ethanol extracts of the three species studied showed moderate inhibitory activity against the α-amylase enzyme. When the results obtained were evaluated, it is possible to state that A. schizopterus and A. distinctissimus species used as animal feed should be subjected to more detailed studies to be used for the pharmaceutical industry, as they are rich in oleanolic and ursolic acids and show anti-diabetic.

Fruits contain vitamins and dietary fibers, a vital source of the human diet. According to fruit production statistics, millions of metric tons of fruits was produced worldwide, and the advanced agricultural fruit recognition system with a simple camera or sensor will play an excellent role for farmers and general people. For the classification of fruits and vegetables, the features that come to mind first are sizing, color, and smell. The other ones are physical, chemical, and biological properties, and their tastes are important for identification, too. Such features also provide a perfect environment for creating imbalanced and incomplete datasets under the open-set protocol. The traditional methods that include a physical inspection of each fruit are less efficient, resulting in the development of more efficient and effective classification algorithms. Data mining algorithms for classification is operated in some software without being directly coded, KNIME, or can be modeled in code-able software such as PYTHON. It is a widely used high-level, general-purpose, interpreted, dynamic programming language, and pandas, numpy, matplotlib, and scikit-learn packages is frequently used as the basis for programming with PYTHON. This work aims to distinguish between different types of fruits using a simple dataset for the task of training a classifier. In this study prepared using the data, 59 fruit samples with the species name, subspecies name, weight, width, height, and color properties were analyzed using Decision Tree (DTR), K-Nearest Neighbors (KNN), Linear Discriminant Analysis (LDA), Gaussian Navie Bayes (GNB) and Support Vector Machine (SVM) classifiers. Accuracy values for each classifier were defined and compared with each other, and then the classifier with the highest accuracy was examined in detail. In the decision tree of samples classified according to fruit names, it is understood that height is the most effective measure in classifying fruits, and they are in the Bin 1 class (15 pieces). The second effective one is in the Bin 1 class (15 units) with height. The third effective one is in the Bin 1 class with width (12 peaces).