Phosphorus (P) is one of the six key elements in plant nutrition and effectively plays a vital role in all major metabolic activities. It is an essential nutrient for plants linked to human food production. Although abundantly present in both organic and inorganic forms in soil, more than 40% of cultivated soils are commonly deficient in P concentration. Then, the P inadequacy is a challenge to a sustainable farming system to improve the food production for an increasing population. It is expected that the whole world population will rise to 9 billion by 2050 and, therefore, it is necessary at the same time for agricultural strategies broadly to expand food production up to 80% to 90% by handling the global dilemma which has affected the environment by climatic changes. Furthermore, the phosphate rock annually produced about 5 million metric tons of phosphate fertilizers per year. About 9.5 Mt of phosphorus enters human food through crops and animals such as milk, egg, meat, and fish and is then utilized, and 3.5 Mt P is physically consumed by the human population. Various new techniques and current agricultural practices are said to be improving P-deficient environments, which might help meet the food requirements of an increasing population. However, 4.4% and 3.4% of the dry biomass of wheat and chickpea, respectively, were increased under intercropping practices, which was higher than that in the monocropping system. A wide range of studies showed that green manure crops, especially legumes, improve the soil-available P content of the soil. It is noted that inoculation of arbuscular mycorrhizal fungi could decrease the recommended phosphate fertilizer rate nearly 80%. Agricultural management techniques to improve soil legacy P use by crops include maintaining soil pH by liming, crop rotation, intercropping, planting cover crops, and the consumption of modern fertilizers, in addition to the use of more efficient crop varieties and inoculation with P-solubilizing microorganisms. Therefore, exploring the residual phosphorus in the soil is imperative to reduce the demand for industrial fertilizers while promoting long-term sustainability on a global scale.
Diabetes is a growing global issue, with socioeconomic status (SES) influencing the incidence and prevalence of the condition. Adults with lower incomes are more likely to develop diabetes and experience higher rates of complications and mortality. In SES assessments, education quality is considered more important than quantity. High-income individuals are less likely to develop diabetes due to their ability to afford balanced diets and medications. Long work hours and illiteracy also contribute to the onset of diabetes. Research conducted in Bahawalpur, Pakistan, found that socioeconomic factors significantly affect diabetes patients, with poor economic status and inadequate diabetic education being more prevalent. Physical inactivity and lack of life insurance further contribute to the condition. In Bahawalpur, a cross-sectional study involving 374 participants from diverse social and economic backgrounds examined the impact of socioeconomic factors on diabetes management and outcomes across different age and gender groups. Among the participants, 60% were male and 39.39% were female, with 66.80% over the age of 50. Out of the 374 participants, 236 (63.10%) were unemployed. Additionally, 41.97% of participants had limited knowledge about diabetes. Due to poor knowledge, economic constraints, and lack of physical activity, participants experienced poor diabetes management, leading to negative outcomes.
Satellite remote sensing is widely being used by the researchers and geospatial scientists due to its free data access for land observation and agricultural activities monitoring. The world is suffering from food shortages due to the dramatic increase in population and climate change. Various crop genotypes can survive in harsh climatic conditions and give more production with less disease infection. Remote sensing can play an essential role in crop genotype identification using computer vision. In many studies, different objects, crops, and land cover classification is done successfully, while crop genotypes classification is still a gray area. Despite the importance of genotype identification for production planning, a significant method has yet to be developed to detect the genotypes varieties of crop yield using multispectral radiometer data. In this study, three genotypes of wheat crop (Aas-'2011', 'Miraj-'08', and 'Punjnad-1) fields are prepared for the investigation of multispectral radio meter band properties. Temporal data (every 15 days from the height of 10 feet covering 5 feet in the circle in one scan) is collected using an efficient multispectral Radio Meter (MSR5 five bands). Two hundred yield samples of each wheat genotype are acquired and manually labeled accordingly for the training of supervised machine learning models. To find the strength of features (five bands), Principle Component Analysis (PCA), Linear Discriminant Analysis (LDA), and Nonlinear Discernment Analysis (NDA) are performed besides the machine learning models of the Extra Tree Classifier (ETC), Random Forest (RF), Support Vector Machine (SVM), Decision Tree (DT), Logistic Regression (LR), k Nearest Neighbor (KNN) and Artificial Neural Network (ANN) with detailed of configuration settings. ANN and random forest algorithm have achieved approximately maximum accuracy of 97% and 96% on the test dataset. It is recommended that digital policymakers from the agriculture department can use ANN and RF to identify the different genotypes at farmer's fields and research centers. These findings can be used for precision identification and management of the crop specific genotypes for optimized resource use efficiency.
Boron (B) is an essential micronutrient in the growth of reproductive plant parts. Its deficiency and/or toxicity are widespread in arid and semi-arid soils with low clay contents. This study was planned to determine the response of sorghum (Sorghum bicolor L., non-leguminous crop) and cowpea (Vigna sinensis L., leguminous crop) to boron (0, 2, 4, and 16 µg g−1) on four distinct soil series from Punjab, Pakistan i.e., Udic Haplustalf (Pindorian region), Typic Torrifluvent (Shahdra region), Halic Camborthid (Khurianwala region), and Udic Haplustalf (Gujranwala region). Overall, there was a significant difference (p < 0.05) in yield between the sorghum (3.8 to 5.5 g pot−1 of 5 kg dry soil) and cowpea (0.2 to 3.2 g pot−1 of 5 kg dry soil) in response to B application. The highest yield was observed in both sorghum and cowpea either in control or at 2 µg g−1 B application in all four soils. Cowpea showed the same yield trend in all four soils (i.e., an increase in yield at 2 µg g−1 B application, followed by a significant decrease at the higher B levels). In contrast, sorghum exhibited greater variability of response on different soils; Udic Haplustalf (Pindorian region) produced the greatest yield at low levels of B application. However, Halic Camborthid produced its lowest yield at that level. Boron concentration in shoots increased with the levels of B application, particularly in sorghum. In cowpea, the plant growth was extremely retarded—and most of the plants died at higher levels of B application even if a lower concentration of B was measured within the shoot. Hot water-extractable B was the most available fraction for cowpea (R2 = 0.96), whereas the easily exchangeable B was most available for sorghum (R2 = 0.90). Overall, these results have implications for micronutrient uptake for both leguminous and non-leguminous crops.
This study was conducted at Bahawalpur Medical and Dental College (BMDC) in collaboration with Bahawalpur Institute of Nuclear Oncology (BINO) Hospital, Pakistan, and aimed to analyze the demographic and clinical characteristics of breast cancer patients. A self-structured questionnaire was developed to collect comprehensive data, including gender, age, regional residence, marital status, reproductive history, BMI, cancer type, stage, time of detection, and family cancer history. Data were collected from 500 female breast cancer patients, with 402 meeting inclusion criteria after excluding incomplete records and male patients. The study revealed a distribution of breast cancer cases across age groups, with a majority aged 41–60 years. BMI classification showed notable proportions of patients classified as obese. Family cancer history was reported in 35.3% of patients. Most patients were non-smokers (97%), and reproductive status showed 37.3% premenopausal, 60.2% postmenopausal, and 2.5% nulliparous. Cancer staging indicated 7.9% with stage 1, 27.4% with stage 2, 42.0% with stage 3, and 16.2% with stage 4 cancer. The majority (95.3%) were diagnosed within 0–5 years of detection. Comparisons with existing literature highlight consistency in age distribution trends and BMI correlations, while variations exist in family cancer history and smoking prevalence. The findings emphasize the importance of tailored prevention and early detection strategies, considering demographic and clinical profiles to enhance breast cancer management and outcomes in Bahawalpur, Pakistan. Further research is warranted to validate these findings and explore additional factors influencing breast cancer incidence and treatment responses.
Flooding is among the most catastrophic and common natural events.It not only endangers human lives, their livelihoods, and possessions but also devastates the nation's economy.Increased flooding is an inevitable consequence of climate change.Hence, Identification of flood suspectable hotspots is vital for flood risk management along with disaster handling.The primary objective of this research is to use a frequency ratio model to classify flood-prone zones in two provinces of Pakistan.The flood inventory map was developed using 230 flood location points in Northern Sindh and Southern Punjab.Aspect, profile curvature, elevation, slope, normalized difference vegetation index (NDVI), normalized difference soil index (NDSI), distance from the road, distance from the river, land use/land cover (LULC) and rainfall were among the ten (10) determining factors.The data were randomly divided into two distinct datasets, with 70% flood points (161) used for inventory formulation and the other 30% (69 flood points) for result validation.The flood vulnerability map was categorized into five different zones ranging from very low (19.73%) to very high (20.37%)susceptibility range.The area under the receiver operating characteristic curve (ROC) and area under curve (AUC) was used to demonstrate the prediction result that yielded a reasonable score of 77.4%.The study suggested that in comparison to other studied districts, Jacobabad is the most prone region with acute vulnerability and constrained resilience.The presented data can serve as a source for tracking, assessing, and predicting potential flood activity in the area and could be beneficial for planners and decision-makers involved in early disaster response planning within the country.
Plentiful quantities of agro-waste are generated after utilizing commercially valuable parts of the agrobiomass and often go to waste or are burned in the open air, resulting in environmental pollution.Herein, bio-nanocomposite is prepared using agro-waste-based activated carbon as a support and loading waste peel-mediated synthesized nanoparticles over it.The method used is cost-effective and simple due to its ease of synthesis and the availability of tons of agro-waste for sustainable agro-waste management.In the present work, orange peel extract is used to synthesize iron-oxide nanoparticles (IONPs) that are loaded over activated carbon derived from ice-apple fruit shell waste (IFSAC), based on the seventh principle of Green Chemistry.Batch studies were conducted using bio-nanocomposite to evaluate its adsorptive removal efficiency for Pb (II) ions from water.The optimum conditions obtained for a Pb (II) ion concentration of 25 ppm were pH 5.5 at 40 °C for 120 minutes and stirring at 120 RPM.The maximum removal (99.44%) of Pb (II) at an adsorbent dosage of 0.2 g 10 mL -1 of bio-nanocomposite was achieved.Kinetics and thermodynamic parameters were also calculated to determine the viability of removal.The findings demonstrated that agro-wastes could be converted into useful assets for the sustainable development of the ecosystem, viz.ice-apple shell residue-derived nanocomposites (IONP@IFSAC) was verified to be a cost-effective adsorbent for the mitigation of lead from water.
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