A two-year study (harvest years 2019 and 2020) was conducted to investigate the effect of a commercially available biofertilizer, in combination with variable nitrogen (N) rate, on bread baking quality and agronomic traits in hard winter wheat grown in conventional (CONV) and organic (ORG) farming systems in Kentucky, USA. The hard red winter wheat cultivar ‘Vision 45’ was used with three N rates (44, 89.6 and 134.5 kg/ha as Low, Med and High, respectively) and three biofertilizer spray regimes (no spray, one spray and two sprays). All traits measured were significantly affected by the agricultural production system (CONV or ORG) and N rate, although trends in their interactions were inconsistent between years. In Y2, yield was

Sustainable agriculture requires eco-friendly inputs to improve crop productivity while reducing reliance on chemicals. Coco peat enhances root growth and nutrient availability, while fermented fish waste and sugarcane juice provide essential nutrients and growth stimulants. To further evaluate, a study was carried out during the fall season of 2024–2025 at University of Baghdad – Al-Jadiryah campus. Following standard field preparation, cauliflower (Brassica oleracea cv. Casper) saplings were transplanted on October 15, 2024, into raised beds in double rows (75 cm × 40 cm). The trial was conducted as a 5×3 factorial experiment in a split-plot RCBD, with coco peat as the main plot and foliar sprays as subplot. The main plot co

Precise forecasting of pore pressures is crucial for efficiently planning and drilling oil and gas wells. It reduces expenses and saves time while preventing drilling complications. Since direct measurement of pore pressure in wellbores is costly and time-intensive, the ability to estimate it using empirical or machine learning models is beneficial. The present study aims to predict pore pressure using artificial neural network. The building and testing of artificial neural network are based on the data from five oil fields and several formations. The artificial neural network model is built using a measured dataset consisting of 77 data points of Pore pressure obtained from the modular formation dynamics tester. The input variables

         The economy is exceptionally reliant on agricultural productivity. Therefore, in domain of agriculture, plant infection discovery is a vital job because it gives promising advance towards the development of agricultural production. In this work, a framework for potato diseases classification based on feed foreword neural network is proposed. The objective of this work  is presenting a system that can detect and classify four kinds of potato tubers diseases; black dot, common scab, potato virus Y and early blight based on their images. The presented PDCNN framework comprises three levels: the pre-processing is first level, which is based on K-means clustering algorithm to detect the infected area from potato image. The s

This study included isolation of some active materials from Curcuma longa such as tannins, saponins and volatile oils with percentage of 59%, 31%, and 9% respectively. Also the study included the determination of minerals in Curcuma longa such as " Na, Ca and K" using Flame photometer. The concentrations of these minerals were (14 ppm),(10 ppm) and )76 ppm) respectively. The anti-bacterial activity study was performed for the active materials isolated from Curcuma longa against two genus of pathogenic bacteria, Escherichia Coli and Staphylococcus aurous by using agar-well diffusion method. It appeared from this study that all of the extraction have inhibitory effect on bacteria was used. The inhibition zone diameter varies with

A factorial experiment (2× 3) in randomized complete block design (RCBD) with three replications was conducted to examine the effect of honeycomb selection method using three interplant distances on yield and its components of two cultivars of bean, Bronco and Strike. Interplant distances used were 75× 65 cm, 90× 78 cm, and 105× 91 cm (row× plant) represent short (high plant density), intermediate (intermediate plant density), and wide (low plant density) distance, respectively. Parameters used for selection were number of days from planting to the initiation of first flower, number of nodes formed prior to first flower, and number of main branches. Results showed significant superiority of the Bronco cultivar represented in the number