912 resultados para 2016 Crop Condition
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Report produced by the The Department of Agriculture and Land Stewardship, Climatology Bureau. Weather report released by the USDA National Agricultural Statistical Service. The report is released weekly from April through October. Formally titled: Iowa Crop and Weather Report
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Report produced by the The Department of Agriculture and Land Stewardship, Climatology Bureau. Weather report released by the USDA National Agricultural Statistical Service. The report is released weekly from April through October. Formally titled: Iowa Crop and Weather Report
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Investigating trends and current issues affecting degree and certificate attainment in the State of Iowa. The report considers workforce demands for educated workers, population and demographic trends and projections, educational preparation for college, financial preparation for college, enrollment trends at Iowa colleges and universities, entering the Iowa workforce, and meeting the needs of the Iowa workforce. Data compares Iowa against national trends.
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La culture sous abris avec des infrastructures de type grands tunnels est une nouvelle technologie permettant d’améliorer la production de framboises rouges sous des climats nordiques. L’objectif principal de ce projet de doctorat était d’étudier les performances de ces technologies (grands tunnels vs. abris parapluie de type Voen, en comparaison à la culture en plein champ) et leur effets sur le microclimat, la photosynthèse, la croissance des plantes et le rendement en fruits pour les deux types de framboisiers non-remontants et remontants (Rubus idaeus, L.). Puisque les pratiques culturales doivent être adaptées aux différents environnements de culture, la taille d’été (pour le cultivar non-remontant), l’optimisation de la densité des tiges (pour le cultivar remontant) et l’utilisation de bâches réfléchissantes (pour les deux types des framboisiers) ont été étudiées sous grands tunnels, abris Voen vs. en plein champ. Les plants cultivés sous grands tunnels produisent en moyenne 1,2 et 1,5 fois le rendement en fruits commercialisables que ceux cultivés sous abri Voen pour le cv. non-remontant ‘Jeanne d’Orléans’ et le cv. remontant ‘Polka’, respectivement. Comparativement aux framboisiers cultivés aux champs, le rendement en fruits des plants sous grands tunnels était plus du double pour le cv. ‘Jeanne d’Orléans’ et près du triple pour le cv. ‘Polka’. L’utilisation de bâches réfléchissantes a entrainé un gain significatif sur le rendement en fruits de 12% pour le cv. ‘Jeanne d’Orléans’ et de 17% pour le cv. ‘Polka’. La taille des premières ou deuxièmes pousses a significativement amélioré le rendement en fruits du cv. ‘Jeanne d’Orléans’ de 26% en moyenne par rapport aux framboisiers non taillés. Des augmentations significatives du rendement en fruits de 43% et 71% du cv. ‘Polka’ ont été mesurées avec l’accroissement de la densité à 4 et 6 tiges par pot respectivement, comparativement à deux tiges par pot. Au cours de la période de fructification du cv. ‘Jeanne d’Orléans’, les bâches réfléchissantes ont augmenté significativement la densité de flux photonique photosynthétique (DFPP) réfléchie à la canopée inférieure de 80% en plein champ et de 60% sous grands tunnels, comparativement à seulement 14% sous abri Voen. Durant la saison de fructification du cv. ‘Polka’, un effet positif de bâches sur la lumière réfléchie (jusqu’à 42%) a été mesuré seulement en plein champ. Dans tous les cas, les bâches réfléchissantes n’ont présenté aucun effet significatif sur la DFPP incidente foliaire totale et la photosynthèse. Pour le cv. ‘Jeanne d’Orléans’, la DFPP incidente sur la feuille a été atténuée d’environ 46% sous le deux types de revêtement par rapport au plein champ. Par conséquent, la photosynthèse a été réduite en moyenne de 43% sous grands tunnels et de 17% sous abris Voen. Des effets similaires ont été mesurés pour la DFPP incidente et la photosynthèse avec le cv. Polka. En dépit du taux de photosynthèse des feuilles individuelles systématiquement inférieur à ceux mesurés pour les plants cultivés aux champs, la photosynthèse de la plante entière sous grands tunnels était de 51% supérieure à celle observée au champ pour le cv. ‘Jeanne d’Orléans’, et 46% plus élevée pour le cv. ‘Polka’. Ces résultats s’expliquent par une plus grande (près du double) surface foliaire pour les plants cultivés sous tunnels, qui a compensé pour le plus faible taux de photosynthèse par unité de surface foliaire. Les températures supra-optimales des feuilles mesurées sous grands tunnels (6.6°C plus élevé en moyenne que dans le champ), ainsi que l’atténuation de la DFPP incidente (env. 43%) par les revêtements de tunnels ont contribué à réduire le taux de photosynthèse par unité de surface foliaire. La photosynthèse de la canopée entière était étroitement corrélée avec le rendement en fruits pour les deux types de framboisiers rouges cultivés sous grands tunnels ou en plein champ.
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Organic agriculture represents one of the fastest growing segments of U.S. agriculture (USDA-RMA). With this in mind, the USDA’s Risk Management Agency (RMA) continues to expand crop insurance options for organic growers. In 2016 and 2017, organic producers in Maryland will see additional crops with organic crop insurance options. Increasing crop insurance options will allow this segment of producers new opportunities to manage their risks.
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Scarcity of freshwater due to recurrent drought threatens the sustainable crop production in semi-arid regions of Ethiopia. Deficit irrigation is thought to be one of the promising strategies to increase water use efficiency (WUE) under scarce water resources. A study was carried out to investigate the effect of alternate furrow irrigation (AFI), deficit irrigation (DI) and full irrigation (FI) on marketable fruit yield, WUE and physio-chemical quality of four fresh-market tomato cultivars (Fetan, Chali, Cochoro and ARP Tomato d2) in 2013 and 2014. The results showed that marketable yield, numbers of fruits per plant and fruit size were not significantly affected by AFI and DI irrigations. WUE under AFI and DI increased by 36.7% and 26.1%, respectively with close to 30% irrigation water savings achieved. A different response of cultivars to irrigation treatments was found for marketable yield, number of fruits and fruit size, WUE, total soluble solids (TSS) of the fruit juice, titratable acids (TA) and skin thickness. Cochoro and Fetan performed well under both deficit irrigation treatments exhibited by bigger fruit size which led to higher WUE. ARP Tomato d2 showed good yields under well-watered conditions. Chali had consistently lower marketable fruit yield and WUE. TSS and TA tended to increase under deficit irrigation; however, the overall variations were more explained by irrigation treatments than by cultivars. It was shown that AFI is a suitable deficit irrigation practice to increase fresh yield, WUE and quality of tomato in areas with low water availability. However, AFI requires suitable cultivars in order to exploit its water saving potential.
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Report produced by the The Department of Agriculture and Land Stewardship, Climatology Bureau. Weather report released by the USDA National Agricultural Statistical Service. Formally titled: Iowa Crop & Progress Report
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Appendix to 2015/16 annual report.
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tWater use control methods and water resources planning are of high priority. In irrigated agriculture, theright way to save water is to increase water use efficiency through better management. The present workvalidates procedures and methodologies using remote sensing to determine the water availability in thesoil at each moment, giving the opportunity for the application of the water depth strictly necessaryto optimise crop growth (optimum irrigation timing and irrigation amount). The analysis is applied tothe Irrigation District of Divor, Évora, using 7 experimental plots, which are areas irrigated by centre-pivot systems, cultivated to maize. Data were determined from images of the cultivated surface obtainedby satellite and integrated with atmosphere and crop parameters to calculate biophysical indicatorsand indices of water stress in the vegetation—Normalized Difference Vegetation Index (NDVI), Kc, andKcb. Therefore, evapotranspiration (ETc) was estimated and used to calculate crop water requirement,together with the opportunity and the amount of irrigation water to allocate. Although remote sensingdata available from satellite imagery presented some practical constraints, the study could contribute tothe validation of a new methodology that can be used for irrigation management of a large irrigated area,easier and at lower costs than the traditional FAO recommended crop coefficients method. The remotesensing based methodology can also contribute to significant saves of irrigation water.
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We investigated the effect of maize residues and rice husk biochar on biomass production, fertiliser nitrogen recovery (FNR) and nitrous oxide (N2O) emissions for three different subtropical cropping soils. Maize residues at two rates (0 and 10 t ha−1) combined with three rates (0, 15 and 30 t ha-1) of rice husk biochar were added to three soil types in a pot trial with maize plants. Soil N2O emissions were monitored with static chambers for 91 days. Isotopic 15N-labelled urea was applied to the treatments without added crop residues to measure the FNR. Crop residue incorporation significantly reduced N uptake in all treatments but did not affect overall FNR. Rice husk biochar amendment had no effect on plant growth and N uptake but significantly reduced N2O and carbon dioxide (CO2) emissions in two of the three soils. The incorporation of crop residues had a contrasting effect on soil N2O emissions depending on the mineral N status of the soil. The study shows that effects of crop residues depend on soil properties at the time of application. Adding crop residues with a high C/N ratio to soil can immobilise N in the soil profile and hence reduce N uptake and/or total biomass production. Crop residue incorporation can either stimulate or reduce N2O emissions depending on the mineral N content of the soil. Crop residues pyrolysed to biochar can potentially stabilise native soil C (negative priming) and reduce N2O emissions from cropping soils thus providing climate change mitigation potential beyond the biochar C storage in soils. Incorporation of crop residues as an approach to recycle organic materials and reduce synthetic N fertiliser use in agricultural production requires a thorough evaluation, both in terms of biomass production and greenhouse gas emissions.
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Progress in crop improvement is limited by the ability to identify favourable combinations of genotypes (G) and management practices (M) in relevant target environments (E) given the resources available to search among the myriad of possible combinations. To underpin yield advance we require prediction of phenotype based on genotype. In plant breeding, traditional phenotypic selection methods have involved measuring phenotypic performance of large segregating populations in multi-environment trials and applying rigorous statistical procedures based on quantitative genetic theory to identify superior individuals. Recent developments in the ability to inexpensively and densely map/sequence genomes have facilitated a shift from the level of the individual (genotype) to the level of the genomic region. Molecular breeding strategies using genome wide prediction and genomic selection approaches have developed rapidly. However, their applicability to complex traits remains constrained by gene-gene and gene-environment interactions, which restrict the predictive power of associations of genomic regions with phenotypic responses. Here it is argued that crop ecophysiology and functional whole plant modelling can provide an effective link between molecular and organism scales and enhance molecular breeding by adding value to genetic prediction approaches. A physiological framework that facilitates dissection and modelling of complex traits can inform phenotyping methods for marker/gene detection and underpin prediction of likely phenotypic consequences of trait and genetic variation in target environments. This approach holds considerable promise for more effectively linking genotype to phenotype for complex adaptive traits. Specific examples focused on drought adaptation are presented to highlight the concepts.
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Agricultural pests are responsible for millions of dollars in crop losses and management costs every year. In order to implement optimal site-specific treatments and reduce control costs, new methods to accurately monitor and assess pest damage need to be investigated. In this paper we explore the combination of unmanned aerial vehicles (UAV), remote sensing and machine learning techniques as a promising methodology to address this challenge. The deployment of UAVs as a sensor platform is a rapidly growing field of study for biosecurity and precision agriculture applications. In this experiment, a data collection campaign is performed over a sorghum crop severely damaged by white grubs (Coleoptera: Scarabaeidae). The larvae of these scarab beetles feed on the roots of plants, which in turn impairs root exploration of the soil profile. In the field, crop health status could be classified according to three levels: bare soil where plants were decimated, transition zones of reduced plant density and healthy canopy areas. In this study, we describe the UAV platform deployed to collect high-resolution RGB imagery as well as the image processing pipeline implemented to create an orthoimage. An unsupervised machine learning approach is formulated in order to create a meaningful partition of the image into each of the crop levels. The aim of this approach is to simplify the image analysis step by minimizing user input requirements and avoiding the manual data labelling necessary in supervised learning approaches. The implemented algorithm is based on the K-means clustering algorithm. In order to control high-frequency components present in the feature space, a neighbourhood-oriented parameter is introduced by applying Gaussian convolution kernels prior to K-means clustering. The results show the algorithm delivers consistent decision boundaries that classify the field into three clusters, one for each crop health level as shown in Figure 1. The methodology presented in this paper represents a venue for further esearch towards automated crop damage assessments and biosecurity surveillance.
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This paper presents a novel crop detection system applied to the challenging task of field sweet pepper (capsicum) detection. The field-grown sweet pepper crop presents several challenges for robotic systems such as the high degree of occlusion and the fact that the crop can have a similar colour to the background (green on green). To overcome these issues, we propose a two-stage system that performs per-pixel segmentation followed by region detection. The output of the segmentation is used to search for highly probable regions and declares these to be sweet pepper. We propose the novel use of the local binary pattern (LBP) to perform crop segmentation. This feature improves the accuracy of crop segmentation from an AUC of 0.10, for previously proposed features, to 0.56. Using the LBP feature as the basis for our two-stage algorithm, we are able to detect 69.2% of field grown sweet peppers in three sites. This is an impressive result given that the average detection accuracy of people viewing the same colour imagery is 66.8%.
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Multimetric ecological condition assessment has become an important biodiversity management tool. This study was the first to examine the reliability of these ecological surrogates across variable environments, and the implications for surrogate efficacy. It was demonstrated that through strategic application and design of the multimetric ecological condition index, the effects of environmental gradients and disturbance regimes can be mitigated, and that ecological condition assessment may serve as a scientifically rigorous approach for conservation planning.