Highly nutritive and antioxidants-enriched okra (Abelmoschus esculentus) gets sub-optimal field yield due to the irregular germination coupled with non-synchronized harvests. Hence, the research aimed at assessing the combined impact of seed priming and field-level gibberellic acid (GA3) foliar spray on the yield and post-harvest quality of okra. The lab studies were conducted using a complete randomized design (CRD), while the field trials were performed following a factorial randomized complete block design (RCBD) with three replications. Okra seeds were subjected to ten different priming methods to assess their impact on seed germination and seeding vigor. In the premier step, okra seeds were subjected to ten different priming methods, like hydro priming for 6, 12, and 18 h, halo priming with 3% NaCl at 35 ℃, 45 ℃, and 60 ℃, acid priming with 80% H2SO4 for 2.5, 5, and 10 min. Based on the observation, hydro priming for 12 h exhibited the best germination rate (90%), followed by halo seed priming at 60 ℃ and acid priming for 5 min. Furthermore, the halo priming at 60 ℃ demonstrated the greatest seedling vigor index (1965), whereas acid priming for 5 min resulted in favorable outcomes in terms of early emergence in 2.66 days. In addition, varying concentrations of GA3 (0, 100, 200, and 300 ppm) were also administered to the best three primed seedlings for evaluating their field performance. The findings indicated that applying GA3 at a concentration of 300 ppm to seedlings raised through acid priming (80% H2SO4 for 5 min) resulted in improved leaf length, reduced time to flowering (first and 50%) and harvest, increased pod diameter, individual pod weight, and yield per plant (735.16 g). Additionally, the treatment involving GA3 at 300 ppm with halo priming (3% NaCl) at 60 ℃ exhibited the longest shelf life (21 days) of okra with the lowest levels of rotting (6.73%) and color change (1.12) in the polyethylene storage condition.
In order to optimize the environmental factors for cucumber growth, a fertilizer and water control system was designed based on the Internet of Things (IoT) system. The IoT system monitors environmental factors such as temperature, light and soil Ec value, and uses image processing to obtain four growth indicators such as cucumber stem height, stem diameter size, number of leaves and number of fruit set to establish a single growth indicator model for temperature, light, soil Ec value and growth stage, and the four growth indicators were fused to obtain the comprehensive growth indicator Ic for cucumber, and calculates its deviation to determine the cucumber growth status. Based on the integrated growth index Ic of cucumber, a soil Ec control model was established to provide the optimal environment and fertilizer ration for cucumber at different growth stages to achieve stable and high yield of cucumber.
Technical Pedagogical Content Knowledge (TPACK) encompasses teachers’ understanding of the intricate interplay among technology, pedagogy, and subject matter expertise, serving as the essential knowledge base for integrating technology into subject-specific instruction. Over the decade, advancements in information technology have led to the consistent application of the TPACK framework within studies on instructional technology and technology-enhanced learning, significantly advancing the evolution of contemporary teacher education in technology integration. In this paper, we utilize the Teaching and Learning Knowledge of Subjects Based on Integrated Technology (TPACK) framework to administer a questionnaire survey to teacher trainees at Chinese colleges and universities. This survey aims to evaluate the current status of their integrated technology-based subject teaching and learning knowledge. Based on the research findings, we propose strategies aimed at enhancing the educational technology integration knowledge of students pursuing integrated technology courses in colleges and universities. Furthermore, we integrate the smart classroom setting to develop a comprehensive TPACK-integrated model teaching framework. Our final objective is to offer valuable references for the progress of modern teaching skills among education students in higher education institutions.
Project risk management in the mining industry is necessary to identify, analyze and reduce uncertainty. The engineering features of mining enterprises, by their nature, require improved risk management tools. This article proves the relevance of creating a simulation model of the production process to reduce uncertainty when making investment decisions. The purpose of the study is to develop an algorithm for deciding on the economic feasibility of creating a simulation experiment. At the same time, the features and patterns of the cases for which the simulation experiment was carried out were studied. Criteria for feasibility assessment of the model introduction based on a qualitative parameters became the central idea for algorithm. The relevance of the formulated algorithm was verified by creating a simulation model of a potassium salt deposit with subsequent optimization of the production process parameters. According to the results of the experiment, the damage from the occurrence of a risk situations was estimated as a decrease in conveyor productivity by 32.6%. The proposed methods made it possible to minimize this risk of stops in the conveyor network and assess the lack of income due to the risk occurrences.
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