Macronutrients distribution and cycling of pineapple planted on tropical peat

This research quantifies P, K, Ca and Mg inputs, losses, retention in soil, and uptake and returns for burnt and unburnt pineapple residue in management practices. Treatments used were: leaves residue removed and no fertilization (LRRNF), leaves residue burnt and no fertilization (LRBNF), leaves residue removed and fertilization (LRRF), and leaves residue burnt and fertilization (the usual practice) (LRBF). Nitrogen, P and K were applied in the forms of urea (46.00% N), China phosphate rock (CPR 14.00% P) and muriate of potash (MOP 49.80% K) at the rates of 701.04, 35.56, and 556.56 kg N, K, and P per ha respectively. Rainfall simulator was used for surface runoff measurement on burnt plots before planting. Soil sampling at the depths of 0-5, 525 and . 25 cm were done before planting, during and after fertilization stages. Extractable P, K, Ca and Mg were extracted using the double-acid method. The subtraction method was used to estimate P, K, Ca and Mg leached (kg per haY. At maturity, plants were sampled from each treatment and partitioned into roots, stem, leaves, fruit, crown and peduncle, and the dry weights, of P, K, Ca and Mg contents determined. Molybdate blue method and atomic absorption spectrophotometer were used in determining P, K, Ca and Mg in soil, plant parts and rainwater, K, Ca and Mg additions from fertilizer, ash and precipitation for LRBF were estimated at 54.25, 816.68, 103.31 and 23.54 kg per ha, and those of LRRF (fertilizer and precipitation) were 35.56, 576.05, 100.17, and 4.93 kg P, K, Ca, and Mg per ha, respectively. The estimated amounts of P, K, Ca and Mg lost under LRBF were 18.44, 300.45, 66.06 and 8.63 kg per ha and in the case of LRRF, the losses were 23.19, 244.88, 45.79 and 5.49 kg per ha. Leaching was the major source of P, K, Ca and Mg loss for both practices and this was attributed to inappropriate fertilization frequency. A positive balance of P, K, Ca and Mg was recorded for LRBF, 46.00% P, 28.00% K, 20.00% Ca and 27.00% Mg which could be recycled after cropping. In the case of LRRF, a positive balance ofP, K and Ca was observed. About 60.00%P, 20.00% K, 13.00% Ca and 36.47% Mg get recycled for LRRF

Application of machine learning with impedance based techniques for structural health monitoring of civil infrastructure

Increased attentiveness on the environmental and effects of aging, deterioration and extreme events on civil infrastructure has created the need for more advanced damage detection tools and structural health monitoring (SHM). Today, these tasks are performed by signal processing, visual inspection techniques along with traditional well known impedance based health monitoring EMI technique. New research areas have been explored that improves damage detection at incipient stage and when the damage is substantial. Addressing these issues at early age prevents catastrophe situation for the safety of human lives. To improve the existing damage detection newly developed techniques in conjugation with EMI innovative new sensors, signal processing and soft computing techniques are discussed in details this paper. The advanced techniques (soft computing, signal processing, visual based, embedded IOT) are employed as a global method in prediction, to identify, locate, optimize, the damage area and deterioration. The amount and severity, multiple cracks on civil infrastructure like concrete and RC structures (beams and bridges) using above techniques along with EMI technique and use of PZT transducer. In addition to survey advanced innovative signal processing, machine learning techniques civil infrastructure connected to IOT that can make infrastructure smart and increases its efficiency that is aimed at socioeconomic, environmental and sustainable development

Interval Load Forecasting for Individual Households in the Presence of Electric Vehicle Charging

The transition to Electric Vehicles (EV) in place of traditional internal combustion engines is increasing societal demand for electricity. The ability to integrate the additional demand from EV charging into forecasting electricity demand is critical for maintaining the reliability of electricity generation and distribution. Load forecasting studies typically exclude households with home EV charging, focusing on offices, schools, and public charging stations. Moreover, they provide point forecasts which do not offer information about prediction uncertainty. Consequently, this paper proposes the Long Short-Term Memory Bayesian Neural Networks (LSTM-BNNs) for household load forecasting in presence of EV charging. The approach takes advantage of the LSTM model to capture the time dependencies and uses the dropout layer with Bayesian inference to generate prediction intervals. Results show that the proposed LSTM-BNNs achieve accuracy similar to point forecasts with the advantage of prediction intervals. Moreover, the impact of lockdowns related to the COVID-19 pandemic on the load forecasting model is examined, and the analysis shows that there is no major change in the model performance as, for the considered households, the randomness of the EV charging outweighs the change due to pandemic

Effect of different concentrations of chitosan coating on storage life and quality characteristics of Papaya (Carica Papaya L.)

Mature green stage of papaya fruits were treated with different concentrations of chitosan at 0, 0.5, 0.75 and 1%, and stored at 13±1 °C for 28 days to study the effect of these concentrations on the storage life and maintaining quality of papaya. Chitosan concentrations 0.75 and 1% showed the best control effect on decay compared with 0% (Control) and 0.5%. At 0.75 and 1% of chitosan, flesh firmness maintained resulted in prolonging in storage life of 28 and 26 days compared with 21 and 19 days, respectively for 0.5 and 0%. Furthermore, they were significantly decreased the weight loss of fruit. All of the treatments inhibited increase of soluble solid contents and pH values of pulp fruits after 21 days of storage at 13 ± 1°C. Titratable acidity and ascorbic acid were higher for coated fruits (0.5, 0.75 and 1%) compared with uncoated fruits. Concern treatments of chitosan at 0.75 and 1% improve papaya fruit quality and resistance to decay

Phosphorus fertilizer use in pineapple cultivation with in situ residues burning on organic soils

In Malaysia, pineapples are grown on peat soils, but most phosphorus (P) fertilizer recommendations are made without due quantification of P uptake; the distribution of P in roots, stem, leaves, peduncle, fruit, and crown; or loss through leaching even though P retention in peat soils is low. This study was conducted to determine applied P-use efficiency under a conventionally recommended fertilization regime in pineapple cultivation with in situ residues burning before replanting. Results showed that most of the P uptake in pineapple can be found in the fruit, stem, leaves, and crown, but the general trend of P distribution was in the order of fruits > leaves > stem > crown > peduncle > roots. Phosphorus recovery in pineapple cultivation was about 40%, and this low recovery was attributed to leaching. Hence, fertilizer recommendations need to take into consideration P loss through leaching. This will help to increase P-use efficiency because it is not possible to build up P content of peat soils. As a result, the need to assess the possibility of side-dress applications of phosphatic fertilizers on peat soil is necessary. Copyright © Taylor & Francis Group, LLC

Unique flowers produced from West Indian lemongrass, Cymbopogon citratus (DC.) Stapf. through induced mutation

West Indian Lemongrass, Cymbopogon citratus, is hardly seen to flower which contributes the major obstacle for hybridization. Induced mutation with gamma irradiation has been suggested as the solution to this problem. The objective of this study is to analyse the effect of gamma irradiation dosage on the survival rate of lemongrass prior to mutation. Vegetative stalks of lemongrass were exposed to different doses of gamma rays at doses of 0, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 110, 120 Gy. Results showed that the practical ranges for induced mutation were 40, 60 and 80 Gy with mutation rates were 25.8%, 36.4% and 69.2% respectively. Dose 80 Gy was identified as the dose for LD50. Irradiation caused plants to produce long above ground stem 50 (not stalk) with obvious appearance of nodes and internodes together with unique production of flowers. This phenomenon has created an astonishing opportunity for future studies in this flower of West Indian Lemongrass mutant as another potential source of Halal traditional medicine

The effects of residue management practices on phosphorus and potassium uptake in pineapple

Pineapple residue in Malaysia is usually burnt. The need for sustainable agricultural development coupled with the 1997 haze problem in Southeast Asia has led to the calls for "zero burning". A study was initiated at Simpang Renggam Pineapple Estate, Johore to quantify P and K uptake in pineapple parts and to also compare the efficiency of P and K uptake for burn and no-burn practices. At maturity (sixteen months after planting), three plants were sampled from each treatment and partitioned into roots, stem, leaves, fruit, peduncle and crown, and their dry weight, P and K concerntrations determined. Irrespective of treatment difference, P uptake was highest in the fruit, followed by the leaves, stem, crown and roots. The order of K was fruit, stem, peduncle, crown and roots. Between 66 and 58% of the total P and K taken up is recycled and the rest (42 and 34%) is lost through harvest. In situ burning of pineapple leaves before planting does not improve P and K uptake and yield. Major difference in P efficiency for butn (51.60%) and no-burn (53.21%) under fertilized was not observed