Mašinska vizuelna klasifikacija sorti pirinča (Oryza sativa l.) upotrebom morfoloških, hromatskih i teksturalnih osobina slika semena

Variety identification is an important task for plant breeders, farmers and traders. DUS (Distinctness, Uniformity, Stability) protocol is generally carried out for identification of plant variety which is time consuming and laborious. An attempt was made to quantify 28 rice varieties based on seed images by digital image analysis. Rice seed images were captured using Canon-LiDE110 flatbed scanner at 600 dpi resolutions. An algorithm was developed using Matlab 2012B to capture and extract seven morphological, 18 textural features and seven chromatic features. Discriminant analysis was carried out to identify critical parameters and classified them into similar groups. The study identified 14 best features out of 32 features that has capability to discriminate between rice cultivars. Eccentricity, awn length, major axis, equivalent diameter, kernel area, kernel perimeter and minor axis were found to be most critical among morphological features while standard deviation (STD) and Energy were found to be most critical among textural features while Hue, Red and Green were found to be most critical among chromatic features. Thus the present study indicated that morphological, chromatic as well as textural features play a vital role in identification of new varieties and distinguishing them to classify into similar groups.Identifikacija vrste je važna za odgajivače, farmere i trgovce. DUS (Rastojanja, Ujednačenost, Stabilnost) protokol je generalno izveden za identifikaciju biljne vrste koja zahteva mnogo vremena i rada. Pokušali smo da kvantifikujemo 28 sorti pirinča na osnovu slika semena digitalnom analizom slike. Semena pirinča su snimljena skenerom Canon-LiDE110 u rezoluciji 600 dpi. Razvijen je algoritam upotrebom Matlab 2012B za hvatanje i izvođenje 7 morfoloških, 18 teksturalnih i 7 hromatskih osobina. Diskriminaciona analiza je izvedena radi identifikacije kritičnih parametara i njihove klasifikacije u slične grupe. Studija je identifikovala 14 najboljih od 32 osobine koje imaju mogućnost razlikovanja sorti pirinča. Ekscentričnost, dužina pleve, glavna osa, ekvivalentni prečnik, površina zrna, obim zrna i mala osa su definisane kao kritične među morfološkim osobinama dok su standardna devijacija i energija izdvojene kao najkritičnije među osobinama teksture. Crvena i zelena boja su bile najkritičnije među hromatskim osobinama. Tako je ova studija pokazala da morfološke, hromatske i osobine teksture igraju odlučujuću ulogu u identifikaciji novih sorti i mkihovog razlikovanja radi klasifikacije u slične grupe

Tailoring Pickering Double Emulsions by in Situ Particle Surface Modification

Fundamental studies on the formation and stability of Pickering double emulsions are crucial for their industrial applications. Available methods of double emulsion preparation involve multiple tedious steps and can formulate a particular type of double emulsion, that is, water-in-oil-in-water (w/o/w) or oil-in-water-in-oil (o/w/o). In this work, we proposed a simple single-step in situ surface modification method to stabilize different types of double emulsions using hematite and silica particle systems which involves the addition of oleic acid. In the emulsification studies, we use (i) a combination of hematite and oleic acid, which is termed the binary system, and (ii) a mixture of hematite and silica particles together with oleic acid, which is designated as the ternary system. The wettability of hematite particles is tuned by direct or sequential addition of oleic acid to the water–decane medium. The direct surface modification (which involves the addition of a known quantity of oleic acid to the oil–water mixtures at once) of hematite particles in both binary and ternary systems shows transitional phase inversion from oil-in-water (o/w) to water-in-oil (w/o) emulsions. However, sequential surface modification results in the transition of a single emulsion to double emulsions. In the case of the binary system, the sequential surface modification of the hematite-particle-stabilized o/w emulsion can be converted into double emulsions of o/w/o type. However, in the case of the ternary system, i.e., in the presence of silica particles, sequential surface modification of hematite particles stabilizes both single (o/w) and double (w/o/w and o/w/o) emulsions. The critical concentration of oleic acid required to form a double emulsion is observed to be dependent on the ratio of the surface area of the silica particle to the total surface area of particles (S) and mixing protocols. A study of the size distribution of oil and water droplets of double emulsions shows that droplet size can be controlled by oleic acid concentration and magnitude of S. The arrangements of the particles at interfaces are visualized by SEM imaging. In this way, we developed an easy and novel single-step method of double emulsion preparation and provide a strategy to tailor the formation of different types of emulsions with a single/binary particle system by sequential in situ surface modification of the particles

Tailoring Pickering Double Emulsions by in Situ Particle Surface Modification

Fundamental studies on the formation and stability of Pickering double emulsions are crucial for their industrial applications. Available methods of double emulsion preparation involve multiple tedious steps and can formulate a particular type of double emulsion, that is, water-in-oil-in-water (w/o/w) or oil-in-water-in-oil (o/w/o). In this work, we proposed a simple single-step in situ surface modification method to stabilize different types of double emulsions using hematite and silica particle systems which involves the addition of oleic acid. In the emulsification studies, we use (i) a combination of hematite and oleic acid, which is termed the binary system, and (ii) a mixture of hematite and silica particles together with oleic acid, which is designated as the ternary system. The wettability of hematite particles is tuned by direct or sequential addition of oleic acid to the water–decane medium. The direct surface modification (which involves the addition of a known quantity of oleic acid to the oil–water mixtures at once) of hematite particles in both binary and ternary systems shows transitional phase inversion from oil-in-water (o/w) to water-in-oil (w/o) emulsions. However, sequential surface modification results in the transition of a single emulsion to double emulsions. In the case of the binary system, the sequential surface modification of the hematite-particle-stabilized o/w emulsion can be converted into double emulsions of o/w/o type. However, in the case of the ternary system, i.e., in the presence of silica particles, sequential surface modification of hematite particles stabilizes both single (o/w) and double (w/o/w and o/w/o) emulsions. The critical concentration of oleic acid required to form a double emulsion is observed to be dependent on the ratio of the surface area of the silica particle to the total surface area of particles (S) and mixing protocols. A study of the size distribution of oil and water droplets of double emulsions shows that droplet size can be controlled by oleic acid concentration and magnitude of S. The arrangements of the particles at interfaces are visualized by SEM imaging. In this way, we developed an easy and novel single-step method of double emulsion preparation and provide a strategy to tailor the formation of different types of emulsions with a single/binary particle system by sequential in situ surface modification of the particles

Response of wastewater-based epidemiology predictor for the second wave of COVID-19 in Ahmedabad, India: A long-term data Perspective

In this work, we present an eight-month longitudinal study of wastewater-based epidemiology (WBE) in Ahmedabad, India, where wastewater surveillance was introduced in September 2020 after the successful containment of the first wave of COVID-19 to predict the resurge of the infection during the second wave of the pandemic. The study aims to elucidate the weekly resolution of the SARS-CoV-2 RNA data for eight months in wastewater samples to predict the COVID-19 situation and identify hotspots in Ahmedabad. A total of 287 samples were analyzed for SARS-CoV-2 RNA using RT-PCR, and Spearman\u27s rank correlation was applied to depict the early warning potential of WBE. During September 2020 to April 2021, the increasing number of positive wastewater influent samples correlated with the growing number of confirmed clinical cases. It also showed clear evidence of early detection of the second wave of COVID-19 in Ahmedabad (March 2021). 258 out of a total 287 samples were detected positive with at least two out of three SARS-CoV-2 genes (N, ORF- 1 ab, and S). Monthly variation represented a significant decline in all three gene copies in October compared to September 2020, followed by an abrupt increase in November 2020. A similar increment in the gene copies was observed in March and April 2021, which would be an indicator of the second wave of COVID-19. A lead time of 1–2 weeks was observed in the change of gene concentrations compared with clinically confirmed cases. Measured wastewater ORF- 1 ab gene copies ranged from 6.1 x 102 (October 2020) to 1.4 x 104 (November 2020) copies/mL, and wastewater gene levels typically lead to confirmed cases by one to two weeks. The study highlights the value of WBE as a monitoring tool to predict waves within a pandemic, identify local disease hotspots within a city, and guide rapid management interventions

Response of wastewater-based epidemiology predictor for the second wave of COVID-19 in Ahmedabad, India: A long-term data Perspective

In this work, we present an eight-month longitudinal study of wastewater-based epidemiology (WBE) in Ahmedabad, India, where wastewater surveillance was introduced in September 2020 after the successful containment of the first wave of COVID-19 to predict the resurge of the infection during the second wave of the pandemic. The study aims to elucidate the weekly resolution of the SARS-CoV-2 RNA data for eight months in wastewater samples to predict the COVID-19 situation and identify hotspots in Ahmedabad. A total of 287 samples were analyzed for SARS-CoV-2 RNA using RT-PCR, and Spearman's rank correlation was applied to depict the early warning potential of WBE. During September 2020 to April 2021, the increasing number of positive wastewater influent samples correlated with the growing number of confirmed clinical cases. It also showed clear evidence of early detection of the second wave of COVID-19 in Ahmedabad (March 2021). 258 out of a total 287 samples were detected positive with at least two out of three SARS-CoV-2 genes (N, ORF- 1 ab, and S). Monthly variation represented a significant decline in all three gene copies in October compared to September 2020, followed by an abrupt increase in November 2020. A similar increment in the gene copies was observed in March and April 2021, which would be an indicator of the second wave of COVID-19. A lead time of 1-2 weeks was observed in the change of gene concentrations compared with clinically confirmed cases. Measured wastewater ORF- 1 ab gene copies ranged from 6.1 x 102 (October 2020) to 1.4 x 104 (November 2020) copies/mL, and wastewater gene levels typically lead to confirmed cases by one to two weeks. The study highlights the value of WBE as a monitoring tool to predict waves within a pandemic, identify local disease hotspots within a city, and guide rapid management interventions.This work is funded by UNICEF, Gujarat, India and Science and Engineering Research Board, New Delhi (CVD/2022/000033). We acknowledge the help received from UPES SEED Grant, Gujarat Pollution Control Board and Ahmedabad Municipal Corporation. Funding for DWG was provided by an EPSRC Impact Acceleration Award (EP/R511584/1) and a NERC award (NE/V004883/1) in the COVID-19 Urgency Programme.Peer reviewe