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In Malaysia, the main constraints of rice yield and productivity are infertile soils and poor management practices because these soils are characterized by low pH, low nutrient availability, low organic matter, and high exchangeable Al and Fe ions, due to high rainfall and hot temperatures. Thus, an incubation study was conducted to determine the optimum amount of calcium silicate (HmbG brand) to improve the soil pH, electrical conductivity (EC), exchangeable Al, available P, and cation exchange capacity (CEC) of a paddy soil in Sabah, Malaysia. The Kelawat series (Typic Dystrudept) soil was incubated with calcium silicate at the application rates of 0 (T1), 1 (T2), 2 (T3), and 3 t ha−1 (T4) using a Completely Randomized Design (CRD) in triplicates for 30, 60, 90, and 120 days. The calcium silicate used significantly improved soil pH because of the release of SiO44− and Ca2+ ions, which neutralized and immobilized H+ ions. Furthermore, the neutralizing effects of the amendment impeded Al hydrolysis by up to 57.4% and this resulted in an increase in the available P in the soil by 31.26% to 50.64%. The increased availability of P in the soil was also due to the high affinity of SiO44− to desorb P from soil minerals and it is believed that SiO44− can temporarily adsorb exchangeable base cations such as K+, Ca2+, Mg2+, and Na+. Moreover, applying calcium silicate at 3 t ha−1 improved soil CEC by up to 54.84% compared to that of untreated soils (T1) because of increased pH and the number of negatively charged sites. The most suitable application rate of the calcium silicate was found to be 3 t ha−1 (T4). These findings suggest that calcium silicate can improve soil productivity and agronomic efficiency in rice farming. Greenhouse and field trials are necessary to ascertain the effects of the recommended treatments of this incubation study on soil productivity, rice growth, and yield. [ABSTRACT FROM AUTHOR]

Project management planning and assessment are of great significance in project performance activities. Without a realistic and logical plan, it isn't easy to handle project management efficiently. This paper presents a wide-ranging comprehensive review of papers on the application of Machine Learning in software project management. Besides, this paper presents an extensive literature analysis of (1) machine learning, (2) software project management, and (3) techniques from three main libraries, Web Science, Science Directs, and IEEE Explore. One-hundred and eleven papers are divided into four categories in these three repositories. The first category contains research and survey papers on software project management. The second category includes papers that are based on machine-learning methods and strategies utilized on projects; the third category encompasses studies on the phases and tests that are the parameters used in machine-learning management and the final classes of the results from the study, contribution of studies in the production, and the promotion of machine-learning project prediction. Our contribution also offers a more comprehensive perspective and a context that would be important for potential work in project risk management. In conclusion, we have shown that project risk assessment by machine learning is more successful in minimizing the loss of the project, thereby increasing the likelihood of the project success, providing an alternative way to efficiently reduce the project failure probabilities, and increasing the output ratio for growth, and it also facilitates analysis on software fault prediction based on accuracy. [ABSTRACT FROM AUTHOR]

A 45-day incubation and leaching experiments was conducted to determine the effect of different rates (0, 1, 2, 3, and 5 t ha−1) of enriched empty fruit bunches biochar (EEFB) and inorganic fertilizer (91 kg ha−1 triple superphosphate—TSP) on the availability and leaching losses of phosphorus from sandy soil (tin tailing soil). The treatments rates for the study were designated as T1—without fertilizer (control), T2—inorganic fertilizer treatment using TSP and T3, T4, T5, and T6, which refers to EEFB rate of 1, 2, 3, and 5 t ha−1, respectively. The enriched biochar was prepared by shaking biochar with chicken manure extract for 24 h. The addition of EEFB to the soils was found to increase pH of the soil compared to control and inorganic fertilizer treatment. After 45 days of incubation, the percentage increase in available P recorded in EEFB treatments were 1.6, 2.9, 2.8, and 4.1%, whereas for control treatment and inorganic fertilizer treatment, the available phosphorus was found to reduce by 10% and 83%, respectively. Loss of phosphorus via leaching in the soil was higher in EEFB treatments compared to control. However, the highest phosphorus leaching among all treatments in this study was recorded in inorganic fertilizer treatments. From the study, it was observed that biochar can be used to recapture phosphorus from chicken manure extract for transport to the soil, thereby reducing problems associated with chicken manure application. [ABSTRACT FROM AUTHOR]

Understanding carbon mineralization dynamics of organic amendments is essential to restore degraded lands. This study focused on the restoration potentials of tea-growing soils using organic materials available in tea ecosystems. The Selangor-Briah soil series association (Typic Endoaquepts) consisted of a high- (soil A) and a low-carbon (soil B) soils were incubated with different organic materials and released carbon dioxide (CO2) measured. Two kinetic models were applied to depict the mineralization process. Soil health parameters including microbial biomass carbon and nitrogen, dehydrogenase and catalase activities were determined to assess the restoration potentials. The parallel first-order kinetic model fitted well for all amendments. Gliricidia markedly enhanced the net cumulative CO2 flux in both soils. Charged biochar, tea waste and Gliricidia improved the microbial biomass carbon by 79–84% in soil A and 82–93% in soil B, respectively. Microbial quotients and biomass nitrogen were increased over 50 and 70% in amended soils, respectively. Dehydrogenase activity was significantly accelerated over 80% by compost, charged biochar and tea waste. Charged biochar remarkably increased the soil catalase activity by 141%. Microbial biomass, dehydrogenase and catalase activities, and cumulative CO2 flux were positively correlated (r > 0.452) with one another. The studied amendments showed greater potential in improving the soil quality, while charged biochar, raw biochar and compost enrich the soil recalcitrant C pool ensuring the soil health in long term. Even though biochar sequesters carbon, it has to be charged with nutrients to achieve the soil restoration goals. [ABSTRACT FROM AUTHOR]