Monitoring plant responses in field-grown peanuts exposed to exogenously applied chitosan under full and limited irrigation levels.

In recent decades, numerous studies have examined the effects of climate change on the responses of plants. These studies have primarily examined the effects of solitary stress on plants, neglecting the simultaneous effects of mixed stress, which are anticipated to transpire frequently as a result of the extreme climatic fluctuations. Therefore, this study investigated the impact of applied chitosan on boosting the resistance responses of peanuts to alkali and mixed drought-alkali stresses. Peanuts were grown in mid-alkaline soil and irrigated with full irrigation water requirements (100%IR), represented alkali condition (100% IR × alkali soil) and stress conditions (70% IR × alkali soil-represented mixed drought-alkali conditions). Additionally, the plants were either untreated or treated with foliar chitosan. The study evaluated various plant physio-chemical characteristics, including element contents (leaves and roots), seed yield, and irrigation water use efficiency (IWUE). Plants that experienced solitary alkali stress were found to be more vulnerable. However, chitosan applications were effective for reducing (soil pH and sodium absorption), alongside promoting examined physio-chemical measurements, yield traits, and IWUE. Importantly, when chitosan was applied under alkali conditions, the accumulations of (phosphorus, calcium, iron, manganese, zinc, and copper) in leaves and roots were maximized. Under mixed drought-alkali stresses, the results revealed a reduction in yield, reaching about 5.1 and 5.8% lower than under (100% IR × alkali), in the first and second seasons, respectively. Interestingly, treated plants under mixed drought-alkali stresses with chitosan recorded highest values of relative water content, proline, yield, IWUE, and nutrient uptake of (nitrogen, potassium, and magnesium) as well as the lowest sodium content in leaves and roots. Enhances the accumulation of (N, K, and Mg) instead of (phosphorus, calcium, iron, manganese, zinc, and copper) was the primary plant response to chitosan applications, which averted severe damage caused by mixed drought-alkali conditions, over time. These findings provide a framework of the nutrient homeostasis changes induced by chitosan under mixed stresses. Based on the findings, it is recommended under mixed drought-alkali conditions to treat plants with chitosan. This approach offers a promising perspective for achieving optimal yield with reduced water usage.

Intelligent Modeling and Multi-Response Optimization of AWJC on Fiber Intermetallic Laminates through a Hybrid ANFIS-Salp Swarm Algorithm.

The attainment of intricate part profiles for composite laminates for end-use applications is one of the tedious tasks carried out through conventional machining processes. Therefore, the present work emphasized hybrid intelligent modeling and multi-response optimization of abrasive waterjet cutting (AWJC) of a novel fiber intermetallic laminate (FIL) fabricated through carbon/aramid fiber, reinforced with varying wt% of reduced graphene oxide (r-GO) filled epoxy resin and Nitinol shape memory alloy as the skin material. The AWJC experiments were performed by varying the wt% of r-GO (0, 1, and 2%), traverse speed (400, 500, and 600 mm/min), waterjet pressure (200, 250, and 300 MPa), and stand-off distance (2, 3, and 4 mm) as the input parameters, whereas kerf taper (Kt) and surface roughness (Ra) were considered as the quality responses. A hybrid approach of a parametric optimized adaptive neuro-fuzzy inference system (ANFIS) was adopted through three different metaheuristic algorithms such as particle swarm optimization, moth flame optimization, and dragonfly optimization. The prediction efficiency of the ANFIS network has been found to be significantly improved through the moth flame optimization algorithms in terms of minimized prediction errors, such as mean absolute percentage error and root mean square error. Further, multi-response optimization has been performed for optimized ANFIS response models through the salp swarm optimization (SSO) algorithm to identify the optimal AWJC parameters. The optimal set of parameters, such as 1.004 wt% of r-GO, 600 mm/min of traverse speed, 214 MPa of waterjet pressure, and 4 mm of stand-off distance, were obtained for improved quality characteristics. Moreover, the confirmation experiment results show that an average prediction error of 3.38% for Kt and 3.77% for Ra, respectively, were obtained for SSO, which demonstrates the prediction capability of the proposed optimization algorithm.

Wear and Friction Analysis of Brake Pad Material Using Natural Hemp Fibers.

Non-exhaust brake dust and pollution arising from metal, semi-metal, and ceramic brake pads have made recent research consider their replacement by potential natural fibers such as hemp, flax, sisal, etc. These natural fibers are lightweight, biodegradable, and cheap. This paper discusses the wear and friction analysis of hemp fiber reinforced polymer brake pad material. Three test specimens viz. HF4P20, HF5P20, and HF6P20 were prepared per ASTM G99 standards for the pin-on disc tribo-test. The test trials and validation were done using the Taguchi design of experiments and ANOVA. The optimum result showed a consistent coefficient of friction and lowered specific wear rate for HF6P20 brake pad material. Worn surface morphology was done using scanning electron microscopy.