Implementation of the Internet of Things for Monitoring the Companys Electrical Power Consumption

This research aims to design an electric panel monitoring system using the Internet of Things technology in company buildings so that consumers can monitor real-time electricity consumption. The energy consumption monitoring method that we propose uses PM2100 by implementing a real-time monitoring function of the power consumption of a 3-phase electric panel. The monitoring system implementation results show that the value is very close to measuring the digital multimeter measuring instrument. The monitoring system produces a current measurement accuracy of 97.38% with an error of 2.62%, while the 3-phase voltage measurement error is 0.616%. This system design helps companies obtain information faster to be considered data to improve efficiency in the Company.

Inheritance of Phytic Acid and Other Agronomic Traits in Bread Wheat

Phytic acid (Myo-inositol 1, 2, 3, 4, 5, 6 hexa-kisphophate) is a storage form of phosphorus and can accumulate to levels as high as 35% in the wheat kernel. Phytic acid acts as an anti-nutritional macromolecule (anti-nutrient) in the wheat kernel. Due to its inhibitory role, a high concentration of phytic acid is undesirable as it hinders the bioavailability of some essential nutrients such as Fe, Mg, Ca, Zn and Cu, etc. To see the inheritance of phytic acid in wheat, phytic acid concentration was initially determined in kernels of 10 wheat genotypes to identify two contrasting genetic groups for diallel analysis. Based on pre-screening results of 10 wheat genotypes, five wheat genotypes (3 with high and 2 with low phytic acid concentration) were crossed in all possible combinations during 2007-08 to generate a 5 × 5 full diallel set for studying the inheritance of phytic acid and other agronomic traits. All 20 F1 hybrids and five parental genotypes were planted using a completely randomized block design with 3 replications during 2008- 09 at Khyber Pakhtunkhwa Agricultural University, Peshawar. Variance analysis for all traits revealed significant differences, providing justification for diallel analysis. According to Hotelling’s t2 test and regression analysis, the model of additive-dominance was adequate for phytic acid, plant height, flag leaf area, tillers plant-1, grains spike-1, biological yield; partially adequate for days to heading, grain filling duration, spikelets spike-1,1000- grain weight, grain yield, harvest index and inadequate for plant maturity. Values of D greater than H1 and H2 for flag leaf area and plant height indicated their additive nature, whereas values of D less than H1 and H2 for grain filling duration, grains spike-1, 1000- grain weight, tillers plant-1, spike length, biological yield, grain yield, harvest index and phytic acid concentration accounted for non-additive control of these traits. The same results were confirmed by average degree of dominance calculations. The narrow and broad sense heritability estimates varied widely among traits - days to heading (0.07, 0.32), flag leaf area (0.31, 0.55), grain filling duration (0.24, 0.91), plant height (0.12, 0.28), spike length (0.17, 0.62), spikelets spike-1 (0.35, 0.74), tillers plant-1 (0.05, 0.52), grains spike-1 (0.05, 0.68), 1000-grain weight (0.25, 0.68), biological yield (0.10, 0.89), grain yield (0.13, 0.98), harvest index (0.09, 0.64) and phytic acid concentration (0.01, 0.86). The values for phytic acid concentration ranged from 0.56 to 3.43% among F1 hybrids and 1.06 to 3.67% for parental genotypes. The following F1 hybrids, Ps-2005 × Ghaznavi (0.56%), AUP-4006 × Ps-2004 (0.74%), Janbaz × Ps-2004 (0.89%) and Janbaz × Ps-2005 (1.01%), had the lowest concentration of phytic acid. This research confirms that F1 hybrids with low phytic acid concentration could yield desirable segregants.