13,497 research outputs found

    A soil water indicator for a dynamic model of crop and soil water interaction

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    Water scarcity is a critical issue in agriculture, and the development of reliable methods for determining soil water content is crucial for effective water management. This study proposes a novel, theoretical, non-physiological indicator of soil water content obtained by applying the next-generation matrix method, which reflects the water-soil-crop dynamics and identifies the minimum viable value of soil water content for crop growth. The development of this indicator is based on a two-dimensional, nonlinear dynamic that considers two different irrigation scenarios: the first scenario involves constant irrigation, and the second scenario irrigates in regular periods by assuming each irrigation as an impulse in the system. The analysis considers the study of the local stability of the system by incorporating parameters involved in the water-soil-crop dynamics. We established a criterion for identifying the minimum viable value of soil water content for crop growth over time. Finally, the model was calibrated and validated using data from an independent field study on apple orchards and a tomato crop obtained from a previous field study. Our results suggest the advantages of using this theoretical approach in modeling the plants' conditions under water scarcity as the first step before an empirical model. The proposed indicator has some limitations, suggesting the need for future studies that consider other factors that affect soil water content

    ABC: Adaptive, Biomimetic, Configurable Robots for Smart Farms - From Cereal Phenotyping to Soft Fruit Harvesting

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    Currently, numerous factors, such as demographics, migration patterns, and economics, are leading to the critical labour shortage in low-skilled and physically demanding parts of agriculture. Thus, robotics can be developed for the agricultural sector to address these shortages. This study aims to develop an adaptive, biomimetic, and configurable modular robotics architecture that can be applied to multiple tasks (e.g., phenotyping, cutting, and picking), various crop varieties (e.g., wheat, strawberry, and tomato) and growing conditions. These robotic solutions cover the entire perception–action–decision-making loop targeting the phenotyping of cereals and harvesting fruits in a natural environment. The primary contributions of this thesis are as follows. a) A high-throughput method for imaging field-grown wheat in three dimensions, along with an accompanying unsupervised measuring method for obtaining individual wheat spike data are presented. The unsupervised method analyses the 3D point cloud of each trial plot, containing hundreds of wheat spikes, and calculates the average size of the wheat spike and total spike volume per plot. Experimental results reveal that the proposed algorithm can effectively identify spikes from wheat crops and individual spikes. b) Unlike cereal, soft fruit is typically harvested by manual selection and picking. To enable robotic harvesting, the initial perception system uses conditional generative adversarial networks to identify ripe fruits using synthetic data. To determine whether the strawberry is surrounded by obstacles, a cluster complexity-based perception system is further developed to classify the harvesting complexity of ripe strawberries. c) Once the harvest-ready fruit is localised using point cloud data generated by a stereo camera, the platform’s action system can coordinate the arm to reach/cut the stem using the passive motion paradigm framework, as inspired by studies on neural control of movement in the brain. Results from field trials for strawberry detection, reaching/cutting the stem of the fruit with a mean error of less than 3 mm, and extension to analysing complex canopy structures/bimanual coordination (searching/picking) are presented. Although this thesis focuses on strawberry harvesting, ongoing research is heading toward adapting the architecture to other crops. The agricultural food industry remains a labour-intensive sector with a low margin, and cost- and time-efficiency business model. The concepts presented herein can serve as a reference for future agricultural robots that are adaptive, biomimetic, and configurable

    Informing policy and practice on insect pollinator declines: Tensions between conservation and animal welfare

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    Climate change, agricultural intensification, and other anthropogenic ecosystem challenges have caused declines in the diversity and abundance of insect pollinators. In response to these declines, entomologists have called for greater attention to insect pollinator conservation. Conservation primarily aims to protect groups of non-human animals—populations or species—with only secondary concern for the welfare of individual animals. While conservation and animal welfare goals are sometimes aligned, they often are not. And because animal welfare comes second, it tends to be sacrificed when in tension with conversation priorities. Consider, for example, lethal sampling to monitor many pollinator populations. Growing evidence suggests that the welfare of individual insect pollinators may be morally significant, particularly in the Hymenoptera and Diptera. Considering insect welfare in conservation practices and policies presents many challenges as, in the face of rapid, anthropogenic change, it may be impossible to avoid harming individual animals while promoting diverse populations. We suggest some practical, implementable strategies that can allow for more robust integration of animal welfare goals into insect pollinator conservation. By following these strategies, entomologists may be able to find policies and practices that promote the health of ecosystems and the individual animals within them

    Inhibitory effect and underlying mechanism of cinnamon and clove essential oils on Botryosphaeria dothidea and Colletotrichum gloeosporioides causing rots in postharvest bagging-free apple fruits

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    Bagging-free apple is more vulnerable to postharvest disease, which severely limits the cultivation pattern transformation of the apple industry in China. This study aimed to ascertain the dominant pathogens in postharvest bagging-free apples, to evaluate the efficacy of essential oil (EO) on inhibition of fungal growth, and to further clarify the molecular mechanism of this action. By morphological characteristics and rDNA sequence analyses, Botryosphaeria dothidea (B. dothidea) and Colletotrichum gloeosporioides (C. gloeosporioides) were identified as the main pathogens isolated from decayed bagging-free apples. Cinnamon and clove EO exhibited high inhibitory activities against mycelial growth both in vapor and contact phases under in vitro conditions. EO vapor at a concentration of 60 μL L−1 significantly reduced the incidence and lesion diameter of inoculated decay in vivo. Observations using a scanning electron microscope (SEM) and transmission electron microscope (TEM) revealed that EO changed the mycelial morphology and cellular ultrastructure and destroyed the integrity and structure of cell membranes and major organelles. Using RNA sequencing and bioinformatics, it was demonstrated that clove EO treatment impaired the cell membrane integrity and biological function via downregulating the genes involved in the membrane component and transmembrane transport. Simultaneously, a stronger binding affinity of trans-cinnamaldehyde and eugenol with CYP51 was assessed by in silico analysis, attenuating the activity of this ergosterol synthesis enzyme. Moreover, pronounced alternations in the oxidation/reduction reaction and critical materials metabolism of clove EO-treated C. gloeosporioides were also observed from transcriptomic data. Altogether, these findings contributed novel antimicrobial cellular and molecular mechanisms of EO, suggesting its potential use as a natural and useful preservative for controlling postharvest spoilage in bagging-free apples

    Agroclimatic Requirements of Traditional European Pear (Pyrus communis L.) Cultivars from Australia, Europe, and North America

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    Flowering in temperate fruit trees depends on the temperatures during the previous months; chill is required to overcome endodormancy, and then heat exposure is needed. These agroclimatic requirements are cultivar-specific and determine their adaptability to the growing area and their response to climate change. We aim to estimate the agroclimatic requirements of 16 traditional cultivars of European pears grown in Zaragoza (Spain). We used Partial Least Squares regression analysis to relate 20-year records of flowering dates to the temperatures of the 8 previous months. This approach allowed us to establish the chilling and forcing periods, through which we quantified temperatures with three models for chill accumulation (Chilling Hours, Utah model, and Dynamic model) and one model for heat accumulation (Growing Degree Hours). The results indicated very little difference in the chilling and forcing periods. Chill requirements ranged from 43.9 to 49.2 Chill Portions; from 1027 to 1163 Chilling Units; and from 719 to 774 Chilling Hours. Heat requirements ranged from 6514 to 7509 Growing Degree Hours. Flowering dates were mainly determined by the temperatures during the chilling period. This means that reductions in winter chill caused by global warming in many regions could cause flowering delays or even failures in the fulfillment of chill requirements.Publishe

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    Effects of foliage biomass amounts per tree or orchard road widths (ORWs) on orchard light environment, leaf net photosynthetic rates and amounts of photosynthates per orchard land area were investigated. In each crown model group (CMG), total 375 crown models were designed to possess fifteen grades of leafy block number per 3D grid (NLB). Total 33,750 orchard models were made by combining these crown models with nine grades of orchard road width (ORW). Light environment in their leaf layers and the photosynthesis of these orchard models were analyzed using OLEAS (Yamamoto, 1999). Daily means of leaf PPFD on a clear day (CDMPPFD) in August and that on an overcast day (ODMPPFD) remarkably decreased by increases of the NLB. High and negative correlations were found between both CDMPPFDs and ODMPPFDs and several characteristics of canopy shape. CDMPPFDs, ODMPPFDs, the leaf net photosynthetic rates on a clear day (CDMPNs) and that on an overcast day (ODMPNs) decreased as the ORWs shortened. When leaf area index per orchard was used as a standard, CDMPPFDs, ODMPPFDs, CDMPNs, ODMPNs, amounts of net photosynthate per orchard land area on a clear day (CDMPNOs) and that on an overcast day (ODMPNOs) were compared between the ten CMGs. Clear differences in these values were found between the CMGs. Using these data above-mentioned, values of CDMPNO and NLB were estimated which were correspondent to three plans for fruit production, viz. slight fruits with excellent quality, moderate fruits with good quality and many fruits with ordinary quality

    Land Use and Land Cover Mapping in a Changing World

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    It is increasingly being recognized that land use and land cover changes driven by anthropogenic pressures are impacting terrestrial and aquatic ecosystems and their services, human society, and human livelihoods and well-being. This Special Issue contains 12 original papers covering various issues related to land use and land use changes in various parts of the world (see references), with the purpose of providing a forum to exchange ideas and progress in related areas. Research topics include land use targets, dynamic modelling and mapping using satellite images, pressures from energy production, deforestation, impacts on ecosystem services, aboveground biomass evaluation, and investigations on libraries of legends and classification systems
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