Potassium fertilization for pineapple: effects on plant growth and fruit yield

A field experiment with pineapple (Smooth Cayenne) was carried out on an Ultisol located in the city of Agudos (22º30'S; 49º03'W), in the state of São Paulo, Brazil, with the objective of investigating the effects of rates and sources of potassium fertilizer on plant growth and fruit yield. The experiment was a complete factorial design (4x3) with four rates (0, 175, 350, and 700 kg ha-1 of K2O) and three combinations of K sources (100% KCl, 100% K2SO4, and 40% K2SO4 + 60% KCl). Plant growth and fruit yield were evaluated. Biomass accumulation of pineapple plants was impaired by chlorine added with potassium chloride. Fruit yield increased with potassium fertilization. At high rates of K application, fertilization with K2SO4 showed better results than with KCl. Detrimental effects of KCl were associated with excess of chlorine.

Potassium fertilization for pineapple: effects on soil chemical properties and plant nutrition

A field experiment was carried out on an Ultisol located at the city of Agudos (22º30'S; 49º03'W), in the state of São Paulo, Brazil, in order to determine the effects of rates and sources of potassium fertilizer on nutritional status of 'Smooth Cayenne' pineapple and on some soil chemical properties. The experiment was a complete factorial design with four rates (0, 175, 350, and 700 kg ha-1 of K2O) and three combinations of K sources (100% KCl, 100% K2SO4 and 40% K2SO4 + 60% KCl). Soil samples were taken from the depths 0-20 cm, 20-40 cm and 40-60 cm at planting and 14 months after. Nutritional status of pineapple plants was assessed by means of tissue analysis. Soil K availability increased with application of K fertilizer, regardless of K sources. Soil chlorine and Cl concentration in pineapple leaves increased with application of KCl or K2SO4+KCl. Plant uptake of potassium was shaped by soil K availability and by the application rates of K fertilizer, independently of K sources.

β-Glucan contents of groats of different oat cultivars in official variety, in organic cultivation, and in nitrogen fertilization trials in Finland

Selostus: Kauran ytimen β-glukaanipitoisuus

La intel·ligència artificial i la seva aplicació a l'ensenyament

L'objectiu fonamental d'aquest article és mostrar com les técniques desenvolupades en intel'ligéncia artificial (lA) són d'una gran utilitat per tal de millorar el software destinat a I'ambit educatiu. Per a aixó, en primer Iloc, s'hi fa un breu resum de les finalitats i els objectius generals de les investigacions en lA realitzades fins al moment. Posteriorment, es descriuen les diferents aplicacions de la lA en I'educació dirigides als alumnes en tasques formatives i instructives, i als professors en tasques de disseny i planificació de les activitats docents. L'article acaba amb una reflexió sobre les tendéncies futures de la lA aplicada a I'educació.

Nitrogen and potassium fertilization affecting the plum postharvest quality

The goal of this research was evaluated the effects of potassium and nitrogen fertilization on the plum (Prunus salicina) fresh fruit quality and after cold storage. The experiment was carried out in a five year-old plum orchard 'Reubennel', located at Araucaria County, Parana State, Southern Brazil, in a Haplumbrept Soil. Potassium fertilizer was applied at 55 and 110 kg/ha/year of K2O, as KCl. Nitrogen fertilizer was applied at 40, 80, 120, 160 and 200 kg/ha/year of N, as urea. It was used a split-plot design in a factorial scheme (2x5). One hundred plum fruits were harvested from each plot, in the same day, when 25 to 50% of the peel presented yellow-reddish color. At harvest and after 17, 27 and 37 days of storage at 0 ± 0.5 ºC, the flesh firmness, the total soluble solids, and the titratable acidity were assessed. Fresh fruit quality was affected by N application, with the best results obtained by applying 40 kg/ha/year of N. The N and K rate of 40 and 110 kg/ha/year, respectively, kept superior fruit quality during the storage. 'Reubennel' cold storage can not exceed 27 days. Fresh and stored 'Reubennel' plum fruit qualities depend on the N and K fertilizer rates.

Balancing guava nutrition with liming and fertilization

Guava response to liming and fertilization can be monitored by tissue testing. Tissue nutrient signature is often diagnosed against nutrient concentration standards. However, this approach has been criticized for not considering nutrient interactions and to generate numerical biases as a result of data redundancy, scale dependency and non-normal distribution. Techniques of compositional data analysis can control those biases by balancing groups of nutrients, such as those involved in liming and fertilization. The sequentially arranged and orthonormal isometric log ratios (ilr) or balances avoid numerical bias inherent to compositional data. The objectives were to relate tissue nutrient balances with the production of "Paluma" guava orchards differentially limed and fertilized, and to adjust the current patterns of nutrient balance with the range of more productive guava trees. It was conducted one experiment of 7-yr of liming and three experiments of 3-yr with N, P and K trials in 'Paluma' orchards on an Oxisol. Plant N, P, K, Ca and Mg were monitored yearly. It was selected the [N, P, K | Ca, Mg], [N, P | K], [N | P] and [Ca | Mg] balances to set apart the effects of liming (Ca-Mg) and fertilizers (N-K) on macronutrient balances. Liming largely influenced nutrient balances of guava in the Oxisol while fertilization was less influential. The large range of guava yields and nutrient balances allowed defining balance ranges and comparing them with the critical ranges of nutrient concentration values currently used in Brazil and combined into ilr coordinates.

THE PEAR TREE RESPONSE TO PHOSPHORUS AND POTASSIUM FERTILIZATION

The aim of this study was to evaluate the response to phosphorus (P) and potassium (K) fertilization and to establish the critical levels of P and K in the soil and in the plant tissue in pear trees. Two experiments were conducted in São Joaquim (SC), Brazil. In experiment 1, the plants received annually the application of increasing rates of phosphate fertilizer (0, 40, 80, 120 and 160 kg P2O5 ha-1), while in experiment 2, increasing rates of potassium fertilizer (0, 40, 80, 120 and 160 kg K2O ha-1) were applied annually. In the two experiments, soil was collected annually from the 0-10, 10-20 and 0-20 cm layers, and the available P (experiment 1) and exchangeable K (experiment 2) content was analyzed. Whole leaves were collected annually, which were subjected to analysis of total P (experiment 1) and total K (experiment 2) content. The number and weight of the fruits per plant and fruit yield were evaluated. Application of P on the soil planted with pear trees increased the nutrient content in the soil and, in most crop seasons, in the whole leaf, but it did not affect the yield components and fruit yield. The application of K on the soil with pear trees increased the nutrient content in the soil and, in most of the crop seasons, in the whole leaf, but the potassium content in the whole leaf decreased in the crop season with greater fruit yield. The yield components and fruit yield were not affected by K fertilization.

HETEROTIC GROUP FORMATION IN PSIDIUM GUAJAVA L. BY ARTIFICIAL NEURAL NETWORK AND DISCRIMINANT ANALYSIS

ABSTRACT The present study aimed at evaluating the heterotic group formation in guava based on quantitative descriptors and using artificial neural network (ANN). For such, we evaluated eight quantitative descriptors. Large genetic variability was found for the eight quantitative traits in the 138 genotypes of guava. The artificial neural network technique determined that the optimal number of groups was three. The grouping consistency was determined by linear discriminant analysis, which obtained classification percentage of the groups, with a value of 86 %. It was concluded that the artificial neural network method is effective to detect genetic divergence and heterotic group formation.

Bio-inspired Mechanisms for Artificial Self-organised Systems

Self-organization is a growing interdisciplinary field of research about a phenomenon that can be observed in the Universe, in Nature and in social contexts. Research on self-organization tries to describe and explain forms, complex patterns and behaviours that arise from a collection of entities without an external organizer. As researchers in artificial systems, our aim is not to mimic self-organizing phenomena arising in Nature, but to understand and to control underlying mechanisms allowing desired emergence of forms, complex patterns and behaviours. Rather than attempting to eliminate such self-organization in artificial systems, we think that this might be deliberately harnessed in order to reach desirable global properties. In this paper we analyze three forms of self-organization: stigmergy, reinforcement mechanisms and cooperation. The amplification phenomena founded in stigmergic process or in reinforcement process are different forms of positive feedbacks that play a major role in building group activity or social organization. Cooperation is a functional form for self-organization because of its ability to guide local behaviours in order to obtain a relevant collective one. For each forms of self-organisation, we present a case study to show how we transposed it to some artificial systems and then analyse the strengths and weaknesses of such an approach

Manipulador robótico con visión artificial

En los tiempos que corren la robótica forma uno de los pilares más importantes en la industria y una gran noticia para los ingenieros es la referente a las ventas de estos, ya que en 2013, unos 179.000 robots industriales se vendieron en todo el mundo, de nuevo un máximo histórico y un 12% más que en 2012 según datos de la IFR (International Federation of Robotics). Junto a esta noticia, la robótica colaborativa entra en juego en el momento que los robots y los seres humanos deben compartir el lugar de trabajo sin que nos veamos excluidos por las maquinas, por lo tanto lo que se intenta es que los robots mejoren la calidad del trabajo al hacerse cargo de los trabajos peligrosos, tediosos y sucios que no son posibles o seguros para los seres humanos. Otro concepto muy importante y directamente relacionado con lo anterior que está muy en boga y se escucha desde hace relativamente poco tiempo es el de la fabrica del futuro o “Factory Of The Future” la cual intenta que los operarios y los robots encuentren la sintonía en el entorno laboral y que los robots se consideren como maquinaria colaborativa y no como sustitutiva, considerándose como uno de los grandes nichos productivos en plena expansión. Dejando a un lado estos conceptos técnicos que nunca debemos olvidar si nuestra carrera profesional va enfocada en este ámbito industrial, el tema central de este proyecto está basado, como no podía ser de otro modo, en la robótica, que junto con la visión artificial, el resultado de esta fusión, ha dado un manipulador robótico al que se le ha dotado de cierta “inteligencia”. Se ha planteado un sencillo pero posible proceso de producción el cual es capaz de almacenar piezas de diferente forma y color de una forma autónoma solamente guiado por la imagen capturada con una webcam integrada en el equipo. El sistema consiste en una estructura soporte delimitada por una zona de trabajo en la cual se superponen unas piezas diseñadas al efecto las cuales deben ser almacenadas en su lugar correspondiente por el manipulador robótico. Dicho manipulador de cinemática paralela está basado en la tecnología de cables, comandado por cuatro motores que le dan tres grados de libertad (±X, ±Y, ±Z) donde el efector se encuentra suspendido sobre la zona de trabajo moviéndose de forma que es capaz de identificar las características de las piezas en situación, color y forma para ser almacenadas de una forma ordenada según unas premisas iníciales.