Artificial intelligence to predict soil temperatures by development of novel model

Soil temperatures at both surface and various depths are important in changing environments to understand the biological, chemical, and physical properties of soil. This is essential in reaching food sustainability. However, most of the developing regions across the globe face difficulty in establishing solid data measurements and records due to poor instrumentation and many other unavoidable reasons such as natural disasters like droughts, floods, and cyclones. Therefore, an accurate prediction model would fix these difficulties. Uzbekistan is one of the countries that is concerned about climate change due to its arid climate. Therefore, for the first time, this research presents an integrated model to predict soil temperature levels at the surface and 10 cm depth based on climatic factors in Nukus, Uzbekistan. Eight machine learning models were trained in order to understand the best-performing model based on widely used performance indicators. Long Short-Term Memory (LSTM) model performed in accurate predictions of soil temperature levels at 10 cm depth. More importantly, the models developed here can predict temperature levels at 10 cm depth with the measured climatic data and predicted surface soil temperature levels. The model can predict soil temperature at 10 cm depth without any ground soil temperature measurements. The developed model can be effectively used in planning applications in reaching sustainability in food production in arid areas like Nukus, Uzbekistan

Assessment of youth fitness under long-term exposure to toxic environmental conditions due to pesticides: Case from Aral Sea region

Ill-planned irrigation systems and pesticide overuse during 1950-1960 severely impacted the soil system in the Aral Sea region. Organochlorine compounds including DDT (dichlorodiphenyltrichloromethylmethane), DEE (dichlorodiphenyldichloroethylene), DDD (dichlorodiphenyldichloromethane), HCCH (hexachlorane) and toxic metals are readily available in soil systems. Thus, long-term exposure to these toxic environmental conditions increases the health risk of the people. Hence, this study investigates environmental influence on the development of power motor qualities, physical endurance, and oxygen capacity in young people living in this region. The study cohort included 609 volunteers aged 18-25 in two different geographical regions, North and Nukus in Uzbekistan. All participants were assessed based on the one-mile walking test for strength motor qualities, dynamic and static power endurance, and maximum oxygen consumption (MOC) in addition to hematological indices. Data analysis revealed significantly lower values of all fitness test parameters and MOC in young men and only parameters of dynamic power endurance living in the North region. Both male and female participants of the North cohort had lower red blood cell (RBC) and hemoglobin (Hb) levels compared to the cohort from Nukus. A high prevalence (28% of males and 96% of females) and the nature of anemia (normocytic and normochromic) were found. This study has sufficiently characterized the change in muscular strength and physical endurance in youth in this region. The decrease of MOC and muscle strength and endurance in young men and women may have an influence from organochlorine pesticides on haemopoiesis and subsequent decreasing of oxygen capacity in the blood