Scientific Journals of INIA (Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria)
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Physical and physiological quality of Jatropha curcas L. seeds at different maturity stages using image analysis
Get PDFAim of study: To assess the potential of automated X-ray image analysis to evaluate the physical characteristics of Jatropha curcas seeds, and to relate the parameters obtained with the physiological quality of the seeds harvested at different maturity stages.Area of study: Experimental area of Agronomy Department, Federal University of Viçosa (UFV), Brazil.Material and methods: The fruits were harvested from 20 plants, based on the external skin color (green, yellow, brownish-yellow and brown). The study was performed by automated and visual analysis of radiographic images of the seeds, in which measurements of tissue integrity, density and seed filling were performed. Seed dry matter, germination and seedling growth were also analysed.Main results: Variables obtained through automated analysis of radiographic images correlated significantly with all physiological variables (r > 0.9), as well as visual image evaluations (r > 0.75). The seeds extracted from green fruits presented lower tissue integrity and lower physiological quality. Radiographic analysis was efficient for monitoring J. curcas seed quality at different maturity stages. Morpho-anatomical parameters obtained from X-ray analysis were highly correlated with seed physiological attributes.Research highlights: It is important to develop and improve methodologies based on lower-cost techniques, such as X-ray analysis. In this context, we verified that X-ray images can be used for monitoring J. curcas seed filling and maturation. Radiographic images of seeds can be analyzed automatically with ImageJ software. Internal morphology and physical characteristics of seeds have relationship with their physiological quality
Spain’s national network of silos and granaries: architectural and technological change over time
Get PDFAim of study: To analyse the 670 silos in Spain’s NNSG (National Network of Silos and Granaries), along with the changes in typologies and degree of mechanisation taking place over time.Area of study: Spain.Material and methods: Research began in 2014, collecting NNSG grain storage data across Spain further to the methodology developed by the authors. In a first stage the information was gathered from the FEGA’s general archives in Madrid and the archives of the departments of agriculture in the 13 regions where silos were built. In the second stage of the study, 665 silos were explored in situ. Photographs were taken and information was gathered on their characteristics (general features; architectural features; technological facilities).Main results: This paper discusses the architectural and typological changes taking place over time, from the earliest small, local, richly adorned brick silos to larger, more modern and austere reinforced concrete structures. The machinery with which they are fitted is also addressed, with the progression from basic grain storage to more sophisticated equipment designed to clean, refrigerate or disinfect the grain. Some facilities were used exclusively to select and condition seed for subsequent sowing. The most modern structures, known as macrosilos, are highly mechanised affairs.Research highlights: Spain’s national network of silos and granaries was 41 years in the building. The inventory of the 665 existing silos identified 20 types or subtypes. Early richly adorned units gradually gave way to more austere, functional structures. The machinery in place in silos varied with type/purpose and period of construction
Evaluating the current ecological status and proposing rehabilitation interventions for the low flooded riparian reserve forest in Punjab Pakistan
Get PDFAim of Study: The complex community of riparian reserve forest has become of great concern for researchers to develop more viable management strategies. The paper aimed to evaluate the current structural diversity of vegetation and its association with the physical environment of low-lying forest for proposing the rehabilitation interventions. Area of Study: We studied two forests, Chung-Mohlanwal and Dhana-Bheni on both riverbanks along river Ravi in the Jhok riparian reserve forest situated in the southwest of Lahore, Pakistan.Material and Methods: A methodological framework was developed based firstly, on direct comparison of diversity (measured by Hill numbers) and structure of existed vegetation layers (trees, shrubs, herbs, and grasses) and environmental factors (canopy structure, anthropogenic activities, microclimate, and soil characteristics) between the two forests and secondly, on environment-vegetation association using Canonical Correspondence Analysis (CCA) ordination method.Results: Dhana forest was more diverse vegetation layers (Shannon Diversity index 1D < 11) and intact due to plantation of uneven-aged tree stands of varied stand basal area and stem density. Microclimate under this forest could not support the dominant understory positively unlike the monoculture forest. On the contrary, Chung-Mohlanwal forest was under the influence of uncontrolled grazing activities, fuelwood extraction, and invasive species. Multivariate analysis CCA elucidated that most variance was shown by soil characteristics (38.5 %) for understory vegetation in both forests.Research Highlights: Overstory stand structure, species composition, distance to nearby communities, and soil characteristics should be considered for developing forest planting and management strategies.Keywords: Vegetation Structure; Hill Numbers; Grazing; Environment; Management.Abbreviation used: CCA (Canonical Correspondence Analysis); 1D (Shannon Diversity); Ca + Mg (Calcium + Magnesium); Na (Sodium); ECe (Electrical Conductivity); DBH (Diameter at Breast Height); IUCN (International Union for Conservation of Nature); SBA (Stand Basal area); BA (Basal Area); 0D (Richness); 2D (Simpson Index); IVI (Importance Value Index); LU (Livestock Unit); GPS (Global Positioning System); OC (Organic Carbon); OM (Organic matter); SAR (Sodium Adsorption Ratio); N (Nitrogen); P (Phosphorous); K (Potassium); DCA (Detrended Correspondence Analysis); S (Shrub); H (Herb); G (Grass)
Responses in growth and dynamics of the shade-tolerant species Theobroma subincanum to logging gaps in the Eastern Amazon
Get PDFAim of study: To assess responses of the shade-tolerant species Theobroma subincanum in relation to canopy gaps created by reduced impact logging (RIL).Materials and methods: A managed forest in themunicipality ofMoju, Pará state,Brazil, harvested in 1997 through RIL was monitored during 12 years (1998-2010). Nine logging gaps were selected and classified in small, medium, and large. Four 10 m x 50 m strips starting from the gap’s border towards the forest and following the directions of cardinal points were installed. Each strip was divided in five 10 m x 10 m plots. Density, diameter distribution (DBH ≥ 5 cm with intervals = 5 cm), and diameter growth were measured.Main results: No significant changes in seedling density of T. subincanum were found, and its diameter distribution followed the reverse “J” shape during all monitoring time. T. subincanum presented diameter growth of 0.15 cm year-1 with highest Periodic Annual Increment in diameter up to three years, and stabilization in nine years after RIL. The species responded to a growth gradient inversely proportional to the gap’s border distance (p = 0.001) but not to gap size and plots direction in cardinal points around the gap.Research highlights: Shade-tolerant species such as T. subincanum have sensible and positive growth responses to disturbances caused by RIL even when seedlings received low amounts of indirect sunlight. These positive responses should be considered in the management of production forests.Keywords: Ecological group; forest management; diameter distribution; reduced impact logging (RIL)
Designing Cluster Plots for Sampling Local Plant Species Composition for Biodiversity Management
Get PDFAim of study: Cluster plot designs are widely used in national forest inventory systems to assess current forest resources. By spreading subplots apart, a cluster plot could potentially capture a large variety of local plant species. This aspect has rarely been examined in the past. This study is conducted to understand how design factors of a cluster plot affect estimates of local plant species composition.Area of study: Two large census forest plots in Taiwan and Peninsular Malaysia over 25 ha with different species richness were used.Material and methods: Design factors of a cluster plot were plot configuration (PCONFIG), plot area (PAREA), cluster layout (CLAYOUT), and extent of ground area covered by a cluster (CEXTENT). Jaccard and Sørensen similarity indices were used to compare species compositional similarity between two cluster plot designs. A simulation study was carried out.Main results: Results were consistent among the study sites and similarity indices. PAREA, CLAYOUT, and CEXTENT notably influenced how species composition was sampled. Larger PAREA increased similarity in species composition between two cluster plot designs. Square and rectangle CLAYOUT had the most dissimilar species composition between them. Larger CEXTENT decreased similarity in species composition.Research highlights: We recommend that for CEXTENT ≤ 1000 m2 and PAREA ≤ 500 m2, a cluster plot of rectangle CLAYOUT is preferred for information gain. The study could potentially benefit forest managers designing cluster plots for plant diversity assessment.Keywords: Biodiversity assessment; composition similarity; national forest inventory; species diversity; sampling design; sampling efficiency.Abbreviation used: extent of ground area covered by a cluster (CEXTENT); cluster layout (CLAYOUT); Jaccard similarity index (JAC); plot area (PAREA); plot configuration (PCONFIG); Sørensen similarity index (SOR)
Modelling of the leaf area for various pear cultivars using neuro computing approaches
Get PDFAim of study: Leaf area (LA) is an important variable for many stages of plant growth and development such as light interception, water and nutrient use, photosynthetic efficiency, respiration, and yield potential. This study aimed to determine the easiest, most accurate and most reliable LA estimation model for the pear using linear measurements of leaf geometry and comparing their performance with artificial neural networks (ANN).Area of study: Samsun, Turkey. Material and methods: Different numbers of leaves were collected from 12 pear cultivars to measure leaf length (L), and width (W) as well as LA. The multiple linear regression (MLR) was used to predict the LA by using L and W. Different ANN models comprising different number of neuron were trained and used to predict LA.Main results: The general linear regression LA estimation model was found to be LA = -0.433 + 0.715LW (R2 = 0.987). In each pear cultivar, ANN models were found to be more accurate in terms of both the training and testing phase than MLR models.Research highlights: In the prediction of LA for different pear cultivars, ANN can thus be used in addition to MLR, as effective tools to circumvent difficulties met in the direct measurement of LA in the laboratory
The importance of disease incidence rate on performance of GBLUP, threshold BayesA and machine learning methods in original and imputed data set
Get PDFAim of study: To predict genomic accuracy of binary traits considering different rates of disease incidence.Area of study: SimulationMaterial and methods: Two machine learning algorithms including Boosting and Random Forest (RF) as well as threshold BayesA (TBA) and genomic BLUP (GBLUP) were employed. The predictive ability methods were evaluated for different genomic architectures using imputed (i.e. 2.5K, 12.5K and 25K panels) and their original 50K genotypes. We evaluated the three strategies with different rates of disease incidence (including 16%, 50% and 84% threshold points) and their effects on genomic prediction accuracy.Main results: Genotype imputation performed poorly to estimate the predictive ability of GBLUP, RF, Boosting and TBA methods when using the low-density single nucleotide polymorphisms (SNPs) chip in low linkage disequilibrium (LD) scenarios. The highest predictive ability, when the rate of disease incidence into the training set was 16%, belonged to GBLUP, RF, Boosting and TBA methods. Across different genomic architectures, the Boosting method performed better than TBA, GBLUP and RF methods for all scenarios and proportions of the marker sets imputed. Regarding the changes, the RF resulted in a further reduction compared to Boosting, TBA and GBLUP, especially when the applied data set contained 2.5K panels of the imputed genotypes.Research highlights: Generally, considering high sensitivity of methods to imputation errors, the application of imputed genotypes using RF method should be carefully evaluated
Greenhouse application of light-drone imaging technology for assessing weeds severity occurring on baby-leaf red lettuce beds approaching fresh-cutting
Get PDFAim of study: For baby-leaf lettuces greenhouse cultivations the absence of weeds is a mandatory quality requirement. One of the most promising and innovative technologies in weed research, is the use of Unmanned Aerial Vehicles (or drones) equipped with acquisition systems. The aim of this study was to provide an estimation of the exact weed amount on baby-sized red lettuce beds using a light drone equipped with an RGB microcamera.Area of study: Trials were performed at specialized organic farm site in Eboli (Salerno, Italy), under polyethylene multi-tunnel greenhouse.Material and methods: The RGB images acquired were processed with specific algorithms distinguishing weeds from crop yields, estimating the weeds covered surface and the severity of weed contamination in terms of biomass. A regression between the percentage of the surface covered by weed (with respect to the image total surface) and the weight of weed (with respect to the total harvested biomass) was calculated.Main results: The regression between the total cover values of the 25 calibration images and the total weight measured report a significant linear correlation. Digital monitoring was able to capture with accuracy the highly variable weed coverage that, among the different grids positioned under real cultivation conditions, was in the range 0-16.4% of the total cultivated one.Research highlights: In a precision weed management context, with the aim of improving management and decreasing the use of pesticides, this study provided an estimation of the exact weed amount on baby-sized red lettuce beds using a light drone
Efficacy of invasive alien plants in controlling Arionidae slugs
Get PDFAim of study: To develop an alternative slug control method, we explored the use of plant material from seven invasive plant species against Arion slugs.Area of study: The experiments were performed at the University of Ljubljana (Slovenia).Material and methods: In laboratory (exp. A-C) and semi-field studies (exp. D), we investigated the contact and barrier efficacy of plant material (powder or liquid formulation) of seven invasive plant species (Japanese knotweed, bohemian knotweed, Canadian goldenrod, giant goldenrod, staghorn sumac, tree of heaven, and false indigo) against Arion slugs. In order to test a contact efficacy of the substance (exp. A), slugs were rolled in a plant material powder. In exp. B, powder made from a plant material was used as a barrier for slugs. Antifeedant effect of the slugs was tested in exp. C, where lettuce leaves were treated with a liquid formulation of a plant material. In exp. D, all above mentioned techniques were used in a semi-field trial.Main results: The results of our studies showed that the plant material of staghorn sumac, giant goldenrod, and Japanese knotweed showed the strongest anti-feedant and barrier effects against the slugs. In the semi-field trial, only 7% of the plants treated with giant goldenrod plant material were attacked by slugs.Research highlights: A contact efficacy of plant powders against Arion slugs was not confirmed in our investigation. Furthermore, several plant powders (goldenrods, staghorn sumac) showed good barrier efficacy. A semi-field trial showed that plant material (giant goldenrod) could represent an alternative solution in slug control