To deal with increasing salinization, plants show an array of responses such as root system architecture remodelling, thereby enhancing stress tolerance. Although various chemical, molecular and genetic techniques such that generally expensive and difficult applications are used to enhance stress tolerance, out of them, seed priming with suitable substrates is an easy-applicable and cost-effective treatment. The experiment aimed to evaluate the effects of salicylic acid (SA), silicon (Si), and sodium chloride (NaCl) priming on lentil seed germination parameters, seedling development, and root system architecture. In 2022, the experiment was carried out in the Field Crops Department laboratory at Siirt University in Turkey. Petri and pot investigations were part of the two stages of the experiment. Three concentrations of NaCl and priming treatments were utilized. Germination characteristics were impeded by rising saline levels. But seed priming, which boosted uniformity of germination by 50% as compared to unprimed seeds under saline stress, enhanced germination characteristics. A pot experiment revealed that the dry matter accumulation in roots was reduced by 24.6% due to salt stress. Si priming increased number of lateral roots by 32.6% compared to control seeds, whereas salt stress lowered it by 22.8%. The total length of lateral roots (TLLR) and mean length of lateral roots (MLLR) were inhibited by salinity stress by 75% and 63, respectively. Total root area was reduced by salinity stress by almost 70%, although seed priming increased it by as much as 29.3%. The SA and Si priming treatments improved germination stage and induced seedling growth by reducing salinity stress via more effective shoot development and root system architecture. In conclusion, seed priming with SA and Si is an affordable and sustainable method for reducing salt stress in lentil farming.

Amerikan beyazkelebeği, Hyphantria cunea Drury (Lepidoptera: Arctidae) önemli karantina zararlılarından birisidir. Polifag bir zararlı olup, başlıca fındık olmak üzere sert ve yumuşak çekirdekli meyvelerde ve orman ağaçlarında zarara neden olmaktadır. H. cunea larvaları, yaprakların üzerinde oluşturdukları ağın içerisinde önce yüzeysel olarak daha sonra ise sadece ana damarları kalacak şekilde yiyerek zarar meydana getirmektedirler. Bu çalışma 2015-2016 yılları arasında Bolu ve Düzce ili fındık bahçelerinde yürütülmüştür. H. cunea’nın zarar seviyesi her bahçeden 1-10 dekar büyüklükteki bahçelerde 10 ocak; 10-30 dekar büyüklükteki bahçelerde 20 ocak; 30 dekardan büyük bahçelerde 30 ocakta kontrol yapılmış ve zarar derecesi 1-10 skalasına göre derecelendirilmiştir. H. cunea, Bolu ilinde merkez ve Mudurnu’da belirlenmiştir. Düzce ilinde ise Yığılca ilçesi hariç yedi ilçede H. cunea’nın yayılış gösterdiği tespit edilmiştir. Fındık üretimi yapılan ilçelerde H. cunea’nın zarar oranları bakımından fark anlamlı bulunmuştur (P<0.05). H. cunea’nın en fazla Çilimli mahalle ve köylerinde olduğu belirlenmiştir. Bu ilçeleri, benzer ortalamaya sahip olan Düzce-merkez köy ve mahalleri ile Gümüşova köyleri izlemektedir. H. cunea zararından en az etkilenen alanlar ise Akçakoca mahalleri ile Yığılca köy ve mahalleleri olduğu belirlenmiştir.

This research assessed 42 lentil genotypes developed by ICARDA along with a local variety over three growing seasons (2019–2022) in Southeastern Türkiye. Phenological, morphological, and yield attributes were determined to observe earliness, yield stability, and adaptation properties. Genotype G3771 showed outstanding performance in grain yield (2579 kg ha⁻¹), 1000-seed weight (54.9 g), and harvest index (37.3%), although it had lower stability under more severe drought conditions. Early-maturing genotypes like G3744, G3715, and G3716 consistently flowered and matured sooner, making them better suited for escaping terminal drought stress areas. The highest yields were recorded during the 2019–2020 season, which experienced favorable rainfall and soil nutrient levels, while the lowest yields occurred due to changing climatic conditions in the 2020–2021 season, highlighting the crop’s sensitivity to climate. Principal component analysis, hierarchical clustering, the Modified Multi-Trait Stability Index (MTSI), and the Multi-Trait Genotype-Ideotype Distance Index (MGIDI) aided in effective genotype classification. Although G3771 was the most productive, genotypes G3687, G3715, and G3689 proved to be the most stable and early maturing based on MGIDI scores. Strong relationships between grain yield, biological yield, and seed size identified these as key selection criteria. This study underscores the value of multi-trait selection tools like MGIDI and MTSI in consistently pinpointing lentil genotypes that balance earliness, productivity, and adaptability, laying a strong foundation for developing climate-resilient varieties suited to semi-arid climates.

This study explores the combined effects of biochar and boron on chickpea growth, soil chemistry and nutrient composition offering a novel approach to sustainable agriculture. A controlled experiment was conducted using biochar derived from poultry litter at four doses (0%, 2%, 4%, and 8%) and boron supplementation at three levels (0, 1 and 2 mg kg^− 1 boron). Growth attributes, soil chemistry, macro and micro nutrient status and heavy metals accumulation were determined in chickpea (Cicer arietinum). Phosphorus, potassium, magnesium and calcium uptake were promoted with higher biochar doses by 20.2%, 16.6%, 20.2% and 25% over control, respectively. Similarly, boron and copper picked with 8% of biochar, while nickel had the highest value with 2% of it. Boron treatments increased magnesium and manganese uptake, whereas they reduced calcium and copper accumulations in plant tissues. biochar inhibited lead, chromium and aluminum absorption at low doses (2%), but increased at higher doses. The highest phosphorus concentration (2458 mg kg⁻¹) was observed with 8% biochar, while magnesium and potassium contents increased by 28.9% and 15.6%, respectively. Principal component analysis showed strong positive correlations between heavy metal uptake and biochar application, highlighting potential shifts in bioavailability. Plant growth parameters responded positively to biochar but negatively to excessive boron. Soil EC increased by 47% under 8% biochar, underscoring the need for careful application to avoid salinity issues. Biochar and boron application rates can promote soil nutrient bioavailability and chickpea growth, and restrict heavy metal accumulation in plants. However, high applications limit plant growth due to intense heavy metal accumulation and ion imbalances in the plant. The application of 2% biochar and 1 mg kg^− 1 boron are considered optimal because it enhances nutrient uptake, minimizes heavy metal accumulation, and maintains low salinity risk. Graphical Abstract

This study proposes Optimized Skewness and Kurtosis Transformation (OSKT), a novel moment-targeting normality transformation that corrects asymmetry and peakedness in non-normal data. OSKT employs a transformation function derived from the Tukey g–h distribution, incorporating skewness and kurtosis parameters, and is optimized by minimizing a single objective function based on the Anderson–Darling test statistic. The optimization process uses L-BFGS-B to tune the transformation parameters to find the best fit for the standard normal distribution. OSKT ensures a balance between symmetry and tail behavior by minimizing deviations from theoretical normality. It has highly competitive performance compared to the alternative, Box–Cox, Yeo–Johnson transformations, including their robust variants and moment-matching Lambert W method, for normalizing complex distributions. According to our analysis, OSKT also achieves superior normalization for highly non-Gaussian data, successfully transforming highly resistant distributions, including approximately symmetric bimodal datasets, where other methods fail.

This study aims to apply the Apriori association rule algorithm on 14 continuous egg quality traits recorded from 4320 eggs of three commercial white-laying chicken lines. In the study all the continuous data were discretized using Equal-Width-Interval method based the number of intervals obtained with Rice formula. Association rules analysis on the discretized dataset resulted with a total of 349 rules consists of 3 and 4 items. According to the top five rules by support and confidence, some important associations were obtained between the certain value ranges of the traits egg weight, egg width, egg length, shell thickness, and shell breaking strength when compared to the others. The appropriate biological and economic interpretations of the obtained rules may contribute to the poultry industry in practice.