Deep Learning for Plant Stress Phenotyping: Trends and Future Perspectives

Deep learning (DL), a subset of machine learning approaches, has emerged as a versatile tool to assimilate large amounts of heterogeneous data and provide reliable predictions of complex and uncertain phenomena. These tools are increasingly being used by the plant science community to make sense of the large datasets now regularly collected via high-throughput phenotyping and genotyping. We review recent work where DL principles have been utilized for digital image–based plant stress phenotyping. We provide a comparative assessment of DL tools against other existing techniques, with respect to decision accuracy, data size requirement, and applicability in various scenarios. Finally, we outline several avenues of research leveraging current and future DL tools in plant science

THERAPEUTIC SIGNIFICANCE OF FENUGREEK W.S.R TO ITS HYPOLIPIDEMIC ACTIVITY

The term Hyperlipidemia denotes excessive cholesterol in the blood. It is both LDL and triglycerides that are elevated in hyperlipidemia. As per Ayurveda, In Hyperlipidemia, Medodhatu vitiates because of improper working of Parthiva and Aapbhutagni rasa and Medodhatvagni. Mainly Asthivahasrotas are affected. Asthivahasrotas build from Medo and Jaghan part. Fenugreek having lipolytic property and it primarily works on Annahvahasrotas and Asthivahasrotas. It decreases cholesterol level, reduces body weight by decreasing plasma triglycerides and having hepatoprotective effect. Fenugreek (Trigonella foenum graecum) commonly known as Methi, family Fabaceae is a annual plant, cultivated world wide as a semiarid crop. The seeds of fenugreek are used as condiment and dried leaves as flavouring agent. Vegetative parts are rich in vit A, vit B and iron. Constituents of fenugreek seeds include flavonoids, alkaloids, coumarins, saponins; most prevalent alkaloid is trigonelline and coumarins include cinnamic acid and scopoletin. In southern part of india roasted seeds in the form of infusion are indicated in diarrhoea and small pox. It is an appetizer and carminative. Its porridge is used as galactagogue. Having antidiabetic, antiallergic, lactation induced, anti-oxidant potency. In this article we are going to discuss about fenugreek in all aspects including its Anti-hyperlipidemic action

Preparation and evaluation of the ZnO NP-Ampicillin/Sulbactam nanoantibiotic: Optimization of formulation variables using RSM coupled GA method and antibacterial activities

Nanoparticles (NPs) possessing antibacterial activity represent an effective way of overcoming bacterial resistance. In the present work, we report a novel formulation of a nanoantibiotic formed using Ampicillin/sulbactam (Ams) and a zinc oxide nanoparticle (ZnO NP). ‘ZnO NP–Ams’ nanoantibiotic formulation is optimized using response surface methodology coupled genetic algorithm approach. The optimized formulation of nanoantibiotic (ZnO NP: 49.9 μg/mL; Ams: 33.6 μg/mL; incubation time: 27 h) demonstrated 15% enhanced activity compared to the unoptimized formulation against K. pneumoniae. The reactive oxygen species (ROS) generation was directly proportional to the interaction time of nanoantibiotic and K. pneumoniae after the initial lag phase of ~18 h as evident from 2'-7'-Dichlorodihydrofluorescein diacetate assay. A low minimum inhibitory concentration (6.25 μg/mL) of nanoantibiotic formulation reveals that even a low concentration of nanoantibiotic can prove to be effective against K. pneumoniae. The importance of nanoantibiotic formulation is also evident by the fact that the 100 μg/mL of Ams and 25 μg of ZnO NP was required individually to inhibit the growth of K. pneumonia, whereas only 6.25 μg/mL of optimized nanoantibiotic formulation (ZnO NP and Ams in the ratio of 49.9: 33.6 in μg/mL and conjugation time of 27 h) was needed for the same

Cephalad Migration of Tunneled-Cuffed Catheter: The Importance of Post Procedure Imaging

TCC placement is a skilled procedure; one must be aware of possible complications, particularly those related to the positioning of catheters, which are vital for the proper functioning of catheters and hemodialysis procedure. It is also equally important to be familiar with the appropriate management if such complications are encountered

Cephalad Migration of Tunneled-Cuffed Catheter: The Importance of Post Procedure Imaging

TCC placement is a skilled procedure; one must be aware of possible complications, particularly those related to the positioning of catheters, which are vital for the proper functioning of catheters and hemodialysis procedure. It is also equally important to be familiar with the appropriate management if such complications are encountered

Energy scheduling optimisation of an islanded microgrid via artificial bee colony guided by global best, personal best and asynchronous scaling factors

An islanded microgrid (IMG) having renewable energy sources (RES), dispatchable sources and battery energy storage (BES) is an effective approach to supply the electricity in remote areas. The reliable operation of IMG is quite complex and challenging task, due to uncertain behaviour of RES, loads and energy bid. In this paper, an IMG is simulated to maximise the revenue considering a dynamic optimisation objective subjected to various constraints of system components for two different cases, i.e. considering the stationary and the dynamic energy bid. Artificial bee colony (ABC) and its variants based on global best (GABC), and global and personal best with asynchronous scaling factors (GPSABC) are implemented and the obtained results are also compared with the existing optimisation techniques. Results of GPSABC improve the revenues and offers better accuracy and stability parameters. Further, the effect on revenue results with different ramp rates of diesel generators is described through GPSABC

Deep Learning for Plant Stress Phenotyping: Trends and Future Perspectives

Deep learning (DL), a subset of machine learning approaches, has emerged as a versatile tool to assimilate large amounts of heterogeneous data and provide reliable predictions of complex and uncertain phenomena. These tools are increasingly being used by the plant science community to make sense of the large datasets now regularly collected via high-throughput phenotyping and genotyping. We review recent work where DL principles have been utilized for digital image–based plant stress phenotyping. We provide a comparative assessment of DL tools against other existing techniques, with respect to decision accuracy, data size requirement, and applicability in various scenarios. Finally, we outline several avenues of research leveraging current and future DL tools in plant science.This article is published as Singh, Asheesh Kumar, Baskar Ganapathysubramanian, Soumik Sarkar, and Arti Singh. "Deep learning for plant stress phenotyping: trends and future perspectives." Trends in plant science 23 (2018): 883-898. doi: 10.1016/j.tplants.2018.07.004.</p

Development of new Nanocomposite by using bagasse dust and polyaniline for removal of heavy metal ions from Pharma industry effluent

Nanotechnology has given the opportunity to the researcher for developing new nano-composites in all field including, pharmaceuticals, agriculture, electronics and other fields. In this study agriculture waste material like bagasse dust has been combined with polyaniline to prepare new Nano composites. So formed Nano composite was characterised by using XRD, FTIR and SEM. SEM confirmed the Nanocomposite formation with size in the range of 100-130 nm. Such nanocomposites were used in the removal of dyes and heavy metals from industrial effluent. About 80-99% heavy metals could be removed through adsorption successfully