They studied three In the present fact-finding work different humus dose versus chemical payments and an absolute witness in the Maíz Blanco Duro cultivation ( Nutrimaíz ), looking for optima! application levels of the humus. Take him to end in the Distrito of the Banda of Shilcayo, in her Fund Miraflores Universidad National De San Martín to approximately 6 kilometers urban of Tarapoto. this work's objectives were to evaluate the biomass production and the white corn•s performance hard ( Nutrimaíz ), the effect of the fertilization with three humus dose of earthworm and his answer in C02 fixing, and to accomplish an economic cost analysis - 1 benefit of the studíed treatments. The design once was used was the one with blocks completely at random ( DBCA ), which 1 consist of 5 treatments and 4 repetitions. They made following observations: germination, height Percentage of plants,...

Antimicrobials with special considerations for use represent the last line of treatment, therefore, greater control in their consumption is warranted; in order to avoid resistance by microorganisms. Objective: to determine the characteristics of the consumption of antimicrobials with special considerations for use in hospitalized patients of the Regional Hospital of Loreto, period 2019. Methodology: The study was descriptive and the consumption of antimicrobials prescribed to patients of the surgery, gynecology, infectology, medicine and obstetrics, through the defined daily dose. Results: 67.7% of patients treated with antimicrobials with special considerations for use were female, 44.36% of patients were between 30 and 59 years of age, with the month of March being the month with the highest prescription (10.05%) and the most consumed antimicrobial per unit was ceftriaxone sodium 1g (4...

Spatial variability of soil properties is a key factor that influences productivity, nutrient management, and overall sustainability in tropical agricultural systems. This is especially true where differences in soil types make it difficult to apply site-specific management strategies. In this context, the study sets out to compare the performance of the same analytical workflow based on multispectral UAV imagery, multiple linear regression, and geostatistical interpolation, across two tropical farming systems that differ in their level of structural heterogeneity. One was a station-wide multicrop system, and the other was a rice system under varying planting densities, both located at the El Porvenir Agricultural Experimental Station in San Martín, Peru. The study included 60 soil samples from the multicrop component and 27 from the rice system. All samples were georeferenced and taken...

Accurate estimation of rice productivity at the sub-field level is still a major challenge in tropical agroecosystems, mainly because of the high spatial variability and the limits of traditional monitoring methods. This study looked at how well the soil-adjusted vegetation index (SAVI), pulled from multispectral images taken by UAVs, could separate productive and non-productive zones in rice fields under tropical lowland conditions in San Martín, Peru. We used a randomized complete block design across two locations with three rice varieties and captured multispectral images at key phenological stages using UAV platforms. Field yield came from georeferenced destructive sampling—we adjusted grain weight to standard moisture and expressed everything in t ha⁻¹. Based on those actual measurements, we set threshold criteria to classify zones as either productive or non-productive. SAVI ...

Rice is a globally important crop and a staple in the diet of a large part of the world's population. This underscores the need for hybridization and improvement of rice genotypes to meet food demand in an environmentally sustainable manner. Geographic Information Systems (GIS) have proven to be valuable tools for the morphometric phenotyping of different genotypes. In this study, seven different rice genotypes were evaluated with the objective of selecting those with high yield. Multispectral imagery was used to develop prediction models based on supervised learning algorithms, including Linear Regression (LR), Support Vector Machine (SVM), Random Forest (RF), Elastic Net (EN), and Neural Networks (NN). The variables studied were plant height, number of panicles, number of tillers, and yield. The results showed the following performances: R² = 0.44 for plant height using Random Forest,...