Deciphering the fiber quality of Gossypium barbadense L.var.brasiliensis in La Convención,Cusco,Perú

Background The quality of cotton fiber determines its value in the textile market,influencing agricultural profitability and the efficiency of textile processing.The selection of genotypes with superior fibers is a key factor for genetic improvement programs seeking adaptability and sustainability in the face of climate change.This demonstrates the strategic importance of this plant for sustainable agriculture and the global textile industry.The objective of this research was to decipher the fiber quality of Gossypium barbadense var.brasiliensis in the native Amazonian communities of La Convención,Cusco-Perú,and to evaluate other critical aspects of native cotton that have not yet been identified.The methodology included non-probability sampling for accessibility,qualitative and quantitative analyses,and multivariate analyses.The fiber length(mm),micronaire index(maturity/fineness),fiber strength(gf/tex),length uniformity index(%),fiber elongation(%),maturation index(%),and short fiber index(%)were the fiber characteristics evaluated using the HVI method in cotton genotypes.Results Cotton accessions collected from Koribeni(Gossypium spp.)and Shivankoreni(Gossypium barbadense var.brasiliensis)stood out for their fiber quality properties,especially length,strength,and uniformity,which highlights their relevance for advanced textile applications and potential for use in plant genetic improvement programs.Conclusion These findings reinforce the need to conserve and study these native cotton accessions from the Peruvian Amazon region,which can offer promising perspectives for the textile industry and agricultural biodiversity.

Potential of Bamboo Species Guadua trinii and Guadua angustifolia for Nanocellulose Production

Non-traditional lignocellulosic materials are a significant resource for producing high-value products,including nanocellulose.This work studied the nanocellulose obtention from chemical pulps of the two fast-growing bamboo species,Guadua trinii,and Guadua angustifolia.Chemical pulps were produced by soda-anthraquinone(S)pulping from both autohydrolysis-pretreated(H)and unpretreated bamboo chips.Autohydrolysis-pretreated(SHP)and unpretreated soda-anthraquinone(AQ)(SP)pulps were characterized by yield,Kappa number,alpha,beta,and gamma cellulose,degree of polymerization,water retention value,and crystallinity.The nanocellulose was produced by a sequential chemical oxidation treatment(2,2,6,6-tetramethylpiperidine-1-oxyl,TEMPO reagent)and mechanical nanofibrillation.Nanocellulose was characterized by carboxylic group content and viscosity.The results revealed that autohydrolysis pretreatment resulted in a higher hemicelluloses extraction in G.angustifolia.In contrast,the pulping yield of unpretreated samples was higher for G.trinii,and the soda-AQ pulps from this species exhibited better delignification than the autohydrolysis-pretreated pulps.The crystallinity index values of the obtained pulps were high(>80%),and the alpha-cellulose contents were similar.The viscosities of the aqueous nanocellulose suspensions were higher for the nanocellulose solutions obtained from the unpretreated soda-AQ pulps.Besides,nanocellulose from G.trinii unpretreated soda-AQ pulps had a higher rate of carboxylic groups.The results of this work are significant in assessing the potential of both bamboo species as a source of high-value products within the biorefinery framework because the viscosities of the aqueous nanocellulose suspensions depend on the size and shape of nanofibrils.It has significant importance for industrial unit operations and potential applications.

Design and Construction of a Pneumatic Temporary Immersion Bioreactor System for the Multiplication of <i>Ananas comosus</i>var. Trujillana Red

The present work initially identified the design parameters of a temporary immersion bioreactor to later scale it to a complete system for the in vitro multiplication of Ananas comosus var. Trujillana Red. Thus, a low-cost pneumatic temporary immersion bioreactor system was designed and built with 24 tanks of 2 L each. The automation of the system was designed and implemented by means of a timer circuit whose design parameters were: duration of the propagation process, which depends on the multiplication period of the crop and is an open variable, which means that the operator decides when to turn off the system;the duration of each dive, which for reasons of complexity of the algorithm was standardized as one minute;immersion frequency, which was programmed for intervals of 1, 2, 3, 4, 5, 6, 7, 8 hours respectively and duration of aeration, which from a test run times of 0.20 were chosen, 30, 40, 50, 60, 70, and 80 seconds that correspond to the time of delivery of compressed air;additionally, the multiplication rate of Ananas comosus var. Trujillana Red in the immersion system which was 6.5 times per propagative unit inoculated in thirty days.

PM2.5 Estimation with the WRF/Chem Model,Produced by Vehicular Flow in the Lima Metropolitan Area

Lima is the capital of the Republic of Peru. It is the most important city in the country and as other Latin America metropolises have multiple problems, including air pollution due to particulate material above air quality standards, emitted by 1.6 million vehicles. The “on-line” coupled model of meteorology and chemistry of transport and meteorological/chemistry, WRF/Chem (Weather and Research Forecasting with Chemistry) has been used in the Lima Metropolitan Area, and validated against data observed at ground level with ten air quality stations of the National Service of Meteorology and Hydrology for the year 2016. The goal of this study was to estimate the concentration of PM2.5 particulate matter in the months of February and July of 2016. In both months, the model satisfactorily predicts temperature and relative humidity. The average observed PM2.5 concentrations in the month of July are higher than in February, probably because the relative humidity in July is greater than the relative humidity in February. In the months of February and July the standard observed deviations of the model have a factor of 2.4 and 3.7 respectively, indicating a greater dispersion in the data of the model. In the month of July, the model captures the characteristics of transport, shows characteristic peaks during peak hours, therefore, the model estimates transport behavior better in July than in February. The quality of the air is strongly influenced by the vehicular transport. The PM2.5 particulate material in February had an average bias that varied from [?13.2 to 4.4 μg/m3] and in July [?9.63 to 11.65 μg/m3] and a normalized average bias in February that varied from [?0.68 to 0.43] and in July of [?0.46 to 0.48].