Disentangling factors controlling fruit and seed removal by rodents in temperate forests

Fleshy fruits fall on to the ground together with cleaned seeds previously ingested by primary dispersers, offering a wide range of fruits and seeds to the ground foragers. Although nutritional properties strongly differ between fruits and seeds, this different seed presentation (cleaned seeds versus seeds within the pulp) has not been addressed in seed removal studies. This study reports on the removal of fruits versus their seeds in five fleshy-fruited species in a temperate forest. We found that rodents removed most of the seeds and partially consumed most of the fruits, preferring seeds to fruits. Rodents bit the fruits to extract the seeds, leaving most of the pulp. We found a preference ranking for the seeds (Sorbus aucuparia>Ilex aquifolium>Sorbus aria>Rosa canina>Crataegus monogyna) but no preferences were found for the fruits, probably due to their similarities in pulp constituents. Seed and fruit choice were affected by chemical and physical properties and not by their size. The presence of alternative and preferred seeds (nuts) delayed the encounter of the fruits and seeds and diminished their removal rates. We found that higher rodent abundance is not necessarily associated with higher removal rates of fleshy fruits. Rodent abundance, fruit size and seed size are minor factors in the removal of fleshy fruits and their seeds. This study underlines that scatter-hoarding rodents are important removers of fleshy fruits and their seeds, producing a differential seed removal depending on the seed presentation (with or without pulp), the nutritional properties of the seeds (but not of the fruits) and the presence of alternative food

Relations between resistance of fruit and skin characteristics in tomato varieties.

Varietal differences in physical properties of processing tomato fruits related with resistance are determined. Mean values of skin resistance and firmness are highly correlated with rupture of the fruits by quasi-static compression and by impact. Skin resistance is dependent on the features of the epidermis, studied microscopically.

Automatic physical activity pattern recognition and meal intake modelling in type 1 diabetes for their inclusion in artificial pancreas systems

La diabetes comprende un conjunto de enfermedades metabólicas que se caracterizan por concentraciones de glucosa en sangre anormalmente altas. En el caso de la diabetes tipo 1 (T1D, por sus siglas en inglés), esta situación es debida a una ausencia total de secreción endógena de insulina, lo que impide a la mayoría de tejidos usar la glucosa. En tales circunstancias, se hace necesario el suministro exógeno de insulina para preservar la vida del paciente; no obstante, siempre con la precaución de evitar caídas agudas de la glucemia por debajo de los niveles recomendados de seguridad. Además de la administración de insulina, las ingestas y la actividad física son factores fundamentales que influyen en la homeostasis de la glucosa. En consecuencia, una gestión apropiada de la T1D debería incorporar estos dos fenómenos fisiológicos, en base a una identificación y un modelado apropiado de los mismos y de sus sorrespondientes efectos en el balance glucosa-insulina. En particular, los sistemas de páncreas artificial –ideados para llevar a cabo un control automático de los niveles de glucemia del paciente– podrían beneficiarse de la integración de esta clase de información. La primera parte de esta tesis doctoral cubre la caracterización del efecto agudo de la actividad física en los perfiles de glucosa. Con este objetivo se ha llevado a cabo una revisión sistemática de la literatura y meta-análisis que determinen las respuestas ante varias modalidades de ejercicio para pacientes con T1D, abordando esta caracterización mediante unas magnitudes que cuantifican las tasas de cambio en la glucemia a lo largo del tiempo. Por otro lado, una identificación fiable de los periodos con actividad física es un requisito imprescindible para poder proveer de esa información a los sistemas de páncreas artificial en condiciones libres y ambulatorias. Por esta razón, la segunda parte de esta tesis está enfocada a la propuesta y evaluación de un sistema automático diseñado para reconocer periodos de actividad física, clasificando su nivel de intensidad (ligera, moderada o vigorosa); así como, en el caso de periodos vigorosos, identificando también la modalidad de ejercicio (aeróbica, mixta o de fuerza). En este sentido, ambos aspectos tienen una influencia específica en el mecanismo metabólico que suministra la energía para llevar a cabo el ejercicio y, por tanto, en las respuestas glucémicas en T1D. En este trabajo se aplican varias combinaciones de técnicas de aprendizaje máquina y reconocimiento de patrones sobre la fusión multimodal de señales de acelerometría y ritmo cardíaco, las cuales describen tanto aspectos mecánicos del movimiento como la respuesta fisiológica del sistema cardiovascular ante el ejercicio. Después del reconocimiento de patrones se incorpora también un módulo de filtrado temporal para sacar partido a la considerable coherencia temporal presente en los datos, una redundancia que se origina en el hecho de que en la práctica, las tendencias en cuanto a actividad física suelen mantenerse estables a lo largo de cierto tiempo, sin fluctuaciones rápidas y repetitivas. El tercer bloque de esta tesis doctoral aborda el tema de las ingestas en el ámbito de la T1D. En concreto, se propone una serie de modelos compartimentales y se evalúan éstos en función de su capacidad para describir matemáticamente el efecto remoto de las concetraciones plasmáticas de insulina exógena sobre las tasas de eleiminación de la glucosa atribuible a la ingesta; un aspecto hasta ahora no incorporado en los principales modelos de paciente para T1D existentes en la literatura. Los datos aquí utilizados se obtuvieron gracias a un experimento realizado por el Institute of Metabolic Science (Universidad de Cambridge, Reino Unido) con 16 pacientes jóvenes. En el experimento, de tipo ‘clamp’ con objetivo variable, se replicaron los perfiles individuales de glucosa, según lo observado durante una visita preliminar tras la ingesta de una cena con o bien alta carga glucémica, o bien baja. Los seis modelos mecanísticos evaluados constaban de: a) submodelos de doble compartimento para las masas de trazadores de glucosa, b) un submodelo de único compartimento para reflejar el efecto remoto de la insulina, c) dos tipos de activación de este mismo efecto remoto (bien lineal, bien con un punto de corte), y d) diversas condiciones iniciales. ABSTRACT Diabetes encompasses a series of metabolic diseases characterized by abnormally high blood glucose concentrations. In the case of type 1 diabetes (T1D), this situation is caused by a total absence of endogenous insulin secretion, which impedes the use of glucose by most tissues. In these circumstances, exogenous insulin supplies are necessary to maintain patient’s life; although caution is always needed to avoid acute decays in glycaemia below safe levels. In addition to insulin administrations, meal intakes and physical activity are fundamental factors influencing glucose homoeostasis. Consequently, a successful management of T1D should incorporate these two physiological phenomena, based on an appropriate identification and modelling of these events and their corresponding effect on the glucose-insulin balance. In particular, artificial pancreas systems –designed to perform an automated control of patient’s glycaemia levels– may benefit from the integration of this type of information. The first part of this PhD thesis covers the characterization of the acute effect of physical activity on glucose profiles. With this aim, a systematic review of literature and metaanalyses are conduced to determine responses to various exercise modalities in patients with T1D, assessed via rates-of-change magnitudes to quantify temporal variations in glycaemia. On the other hand, a reliable identification of physical activity periods is an essential prerequisite to feed artificial pancreas systems with information concerning exercise in ambulatory, free-living conditions. For this reason, the second part of this thesis focuses on the proposal and evaluation of an automatic system devised to recognize physical activity, classifying its intensity level (light, moderate or vigorous) and for vigorous periods, identifying also its exercise modality (aerobic, mixed or resistance); since both aspects have a distinctive influence on the predominant metabolic pathway involved in fuelling exercise, and therefore, in the glycaemic responses in T1D. Various combinations of machine learning and pattern recognition techniques are applied on the fusion of multi-modal signal sources, namely: accelerometry and heart rate measurements, which describe both mechanical aspects of movement and the physiological response of the cardiovascular system to exercise. An additional temporal filtering module is incorporated after recognition in order to exploit the considerable temporal coherence (i.e. redundancy) present in data, which stems from the fact that in practice, physical activity trends are often maintained stable along time, instead of fluctuating rapid and repeatedly. The third block of this PhD thesis addresses meal intakes in the context of T1D. In particular, a number of compartmental models are proposed and compared in terms of their ability to describe mathematically the remote effect of exogenous plasma insulin concentrations on the disposal rates of meal-attributable glucose, an aspect which had not yet been incorporated to the prevailing T1D patient models in literature. Data were acquired in an experiment conduced at the Institute of Metabolic Science (University of Cambridge, UK) on 16 young patients. A variable-target glucose clamp replicated their individual glucose profiles, observed during a preliminary visit after ingesting either a high glycaemic-load or a low glycaemic-load evening meal. The six mechanistic models under evaluation here comprised: a) two-compartmental submodels for glucose tracer masses, b) a single-compartmental submodel for insulin’s remote effect, c) two types of activations for this remote effect (either linear or with a ‘cut-off’ point), and d) diverse forms of initial conditions.

Bruise Simulation in Peach Grading Lines as a tool for designing Improvement Strategies.

The Physical Properties Laboratory (LPF) has been working on the improvement of fruit and vegetable grading lines since 1992'. The experience shows that the improvement of grading lines for decreasing mechanical damages has to be approached from two viewpoints: 1) machinery aggressiveness, and 2) fruit susceptibility. Machinery aggressiveness can be characterized as impact probability for different impact intensities assessed by means of electronic fruits (IS-100) 2,5 . On the other hand, bruise susceptibility can be determined using different laboratory tests. A recent study from LPF4 shows that damage may arise differently in pome and in stone fruits, since: a) pome fruits are mainly stress-susceptible, while stone fruits appear to be more deformation-susceptible, and b) bruise size may be a good predictor for bruise susceptibility in pome fruits while for stone fruits bruise probability is the most relevant characteristic of bruise susceptibility. Also, this study indicates the feasibility of predicting bruise probability using several mechanical and load characterization parameters. Despite the efforts to establish damage thresholds in peachess, no simulation models are currently available for predicting bruise occurrence in grading lines.

Effects of skin characteristics on impact response and bruising of apples and pears

Skin properties have an important influence on impact parameters and bruising. Skin deformation at puncture (a measure of the turgidity of the fruit skin) is negatively correlated with bruise volume in Golden apples after cold storage.

Bruise susceptibility in pome fruits under different loading and storage conditions

Samples of "Golden" and "Granny Smith" apples and "Conference" and "Doyenne of Cornice" pears have been tested. A great effect of storage conditions has been detected for pear but not for apple varieties. Both apple cultivars show to be equally resistant to quasi-static and to dinamic loading while pear varieties show great differences. All these effects can be quantified in order to describe mathematically species and varieties behavior.

Fruit quality sensing:Post-harvest ripeness

Firmness sensing of selected varieties of apples, pears and avocado fruits has been developed using a nondestructive impact technique. In addition to firmness measurements, postharvest ripeness of apples and pears was monitored by spectrophotometric reflectance measurements, and that of avocadoes by Hunter colour measurements. The data obtained from firmness sensing were analyzed by three analytical procedures: principal component, correlation and regression, and stepwise discriminant analysis. A new software was developed to control the impact test, analyse the data, and sort the fruit into specified classes, based on the criteria obtained from a training procedure. Similar procedures were used to analyse the reflectance and colour data. Both sensing systems were able to classify fruits w i th good accuracy.

Mechanical segregation of apricot varieties and their ripeness levels at harvest

Some laboratory tests consisting on quasi-static compression and puncture forces carried out on twelve varieties of apricot during 1990 and 1991 were effective in sorting them. These mechanical properties show a high correlation w i th the ethylene production rate per fruit, so allowing to discriminate between ripeness levels at harvest. In this study it is also demonstrated that puncture seems to be the less variable mechanical test. The values (N/mm) obtained with it show a highly significant correlation with compression resistance and with quasi-static compression damage of the fruits.

Effects of precooling and degreening treatments on the susceptibility of peach and citrus to handling damage.

Mechanical damage to fruits results from a combination of fruit properties and of damage inflicting effects by the handling equipment. Treatments were applied to fruits which affect mechanical damage susceptibility: precooling for stone fruits and degreening to citrus fruits. Laboratory tests (compression, impact, tumbling, abrasion) and field tests (damage in the handling lines) were applied to (3) peach, (2) apricot, (2) orange and (1) lemon varieties. Hydroor-air-cooling influence positively peach and apricot firmness and cause a significant reduction in: number of bruised fruits, and size of visible bruise, when combined with a low level of loading during handling. Degreening also affects the resistance of citrus fruits to handling, when compared to green fruits.

Models for the prediction of handling damage in citrus and peaches grading lines, related to their physical properties.

Fruit damage during harvesting and handling is a standing problem, particularly for susceptible fruits like peaches and apricots. The resulting mechanical damage is a combination of fruit properties and damage inflicting effects due to procedures and to the equipment. Nine packing lines in the region of Murcia (SE Spain) have been tested with the aid of two different-size electronic fruits IS-100. Probabilities of impacts above three preset thresholds (50 g's, 100 g's and 150 g's) were calculated for each transfer point. Interaction fruit-packing line tests have been also performed in order to study the real incidence of packing lines on natural produce: apricots (1 variety), peaches (3 v.), lemons (1 v.) and oranges (3 v.). Bruises of handled and not handled samples of fruits were compared.

Determination of firmness in a fruit packing line using a non destructive impact sensor.

The increasing of quality fruit demanded by the consumers is originating an advance in the development and application of sensors capable of measuring parameters of quality (sugar, acids, firmness, etc) on a non destructive way. Some of these sensors are already operative for their use in laboratory and even in lines. The Physical Properties laboratory of the Polytechnic University of Madrid, is developing different sensors for their implementation in lines. One of them is a non destructive impact sensor to measure fruit firmness.