No abstract

In recent years, many olive orchards, which are a major crop in the Mediterranean basin, have been converted into intensive or super high-density hedgerow systems. This configuration is more efficient in terms of yield per hectare, but at the same time the water requirements are higher than in traditional grove arrangements. Moreover, irrigation regulations have a high environmental (through water use optimization) impact and influence on crop quality and yield. The mapping of (spatio-temporal) variability with conventional water stress assessment methods is impractical due to time and labor constraints, which often involve staff training. To address this problem, this work presents the development of a new low-cost device based on a thermal infrared (IR) sensor for the measurement of olive tree canopy temperature and monitoring of water status. The performance of the developed device was compared to a commercial thermal camera. Furthermore, the proposed device was evaluated in a commercially managed olive orchard, where two different irrigation treatments were established: a full irrigation treatment (FI) and a regulated deficit irrigation (RDC), aimed at covering 100% and 50% of crop evapotranspiration (ETc), respectively. Predawn leaf water potential (ΨPD) and stomatal conductance (gs), two widely accepted indicators for crop water status, were regressed to the measured canopy temperature. The results were promising, reaching a coefficient of determination R2 ≥ 0.80. On the other hand, the crop water stress index (CWSI) was also calculated, resulting in a coefficient of determination R2 ≥ 0.79. The outcomes provided by the developed device support its suitability for fast, low-cost, and reliable estimation of an olive orchard’s water status, even suppressing the need for supervised acquisition of reference temperatures. The newly developed device can be used for water management, reducing water usage, and for overall improvements to olive orchard management.

No abstract

El objetivo de este artículo es revisar la evolución de los estilos de enseñanza en España, desde la perspectiva de un docente que ha trabajado e investigado el tema durante 40 años de vida profesional. Pretende reflexionar sobre las fases de su vida profesional, al tiempo que analiza su desarrollo personal y como docente ligado a los estilos de enseñanza que estudia, practica, enseña e investiga sobre los mismos. Paralelamente se detiene en las patologías docentes que aparecen en cada fase provocando cambios en su forma de enseñar. Finalmente plantea algunas conclusiones sobre la evolución seguida y las perspectivas de futuro de los estilos de enseñanza. Abstract. This work is the essay on the evolution of teaching styles in Spain, from the perspective of a teacher of 40 years of professional life. The aim of this article is to review the evolution of teaching styles in Spain, from the perspective of a teacher who has worked and researched the subject for 40 years of professional life. Some thoughts about the stages of his career, while analyzing their personal development and teacher linked to teaching styles studying, practice, teaching and research on them. Parallel stops in teaching conditions that appear in each phase causing changes in their teaching. Finally presents some conclusions about the evolution followed and future prospects of teaching styles.

The state of ripeness at harvest is a key piece of information for growers as it determines the market price of the yield. This has been traditionally assessed by destructive chemical methods, which lead to low-spatiotemporal resolution in the monitorization of crop development and poor responsiveness for growers. These limitations have shifted the focus to remote-sensing, spectroscopy-based approaches. However, most of the research focusing on these approaches has been accomplished with expensive equipment, which is exorbitant for most users. To combat this issue, this work presents a low-cost, hand-held, multispectral device with original hardware specially designed to face the complexity related to in-field use. The proposed device is based on a development board (AS7265x, AMS AG) that has three sensor chips with a spectral response of eighteen channels in a range from 410 to 940 nm. The proposed device was evaluated in a red-grape field experiment. Briefly, it was used to acquire the spectral signature of eighty red-grape samples in the vineyard. Subsequently, the grape samples were analysed using standard chemical methods to generate ground-truth values of ripening status indicators (soluble solid content (SSC) and titratable acidity (TA)). The eighteen pre-process reflectance measurements were used as input for training artificial neural network models to estimate the two target parameters (SSC and TA). The developed estimation models were evaluated through a leave-one-out cross-validation approach obtaining promising results (R2 = 0.70, RMSE = 1.21 for SSC; and R2 = 0.67, RMSE = 0.91 for TA).