ACIAR Scoping Study on disease and agronomic issues - Vanuatu

ACIAR Scoping Study on disease and agronomic issues - Vanuatu.

Agronomic Packages for Improved Yield and Quality in the Australian Peanut Industry

Monitoring aflatoxin and developing improved peanut drying practices, cadmium management and web based irrigation decision support systems.

Developing agronomic solutions to improve barley yield and grain quality

The main aim of this project is to develop variety management packages to help tailor commercial malt and feed barley production in the Northern GRDC Region to commercial malt and feed barley specifications. Field trials are designed to give information.

DAN00106 Developing agronomic solutions to improve barley yield and grain quality

Producing management packages for new northern barley varieties. Evaluating silage barley varieties.

Agronomic challenges for organic crop husbandry

With respect to resource management and environmental impact, organic farming offers rationales for agricultural sustainability. However, agronomic productivity is usually higher with conventional farming. This work aimed at investigating two factors of major importance for the agronomic productivity of organic crop husbandry, nitrogen (N) supply through symbiotic N fixation (SNF) and weed occurrence. Perennial red clover-grass leys and spring cereal crops subjected to regular agricultural practices were studied on 34 organic farms located in the southern and the north-western coastal regions of Finland. Herbage growth, clover content as a proportion of the ley and extent of SNF in perennial leys, and the occurrence of weed species and weed-crop competition in spring cereal stands were related to climate conditions, soil properties, and management measures. The herbage accumulated from the first and the second cut of one- and two-year-old leys averaged 7.5 t DM ha-1 (SD ± 1.7 t DM ha-1); the clover content averaged 43.9% (SD ± 18.8%). Along with the clover content, herbage production decreased with ley age. Radiation use efficiency (RUE) correlated positively with clover proportion but despite low clover contents, three-year-old leys were still productive with regard to RUE. SNF in the accumulated annual growth of one- and two-year-old leys averaged 247.5 kg N ha-1 yr-1 (SD ± 114.4 kg N ha-1 yr-1). It was supposed that if red clover-grass leys constituted 40% of the rotation, then the mean N supply by SNF would be able to sustain two or three succeeding cereal crops (green manure and forage ley, respectively), yielding 3.0 to 4.0 t grain ha-1. Being a function of clover biomass, the SNF increased from the first to the second cut and thereafter declined with ley age. Coefficients of variation of clover contents (and SNF) between and within fields were around 50%, which was about twice as high as those of herbage production. The lower were the clover contents, the higher were the within-field variations of clover as a proportion of the ley. Low clover contents in one-year-old leys and increasing variability with ley age suggested that red clover growth was limited by poor establishment and poor overwintering. The proportions of clover in leys were lower and their variability was higher in the northwest than in the south. Soil properties, primarily texture and structure, had a major impact on clover proportion and herbage production, which largely explained regional differences in ley growth. Within-field variability of soil properties can be amended through site-specific measures, including drainage, liming, and applications of organic manures and mineral fertilizers. Overwintering and the persistence of leys can be improved by the choice of winter-hardy varieties, careful establishment and the appropriate harvest regime. Mean grain yields of spring cereal crops amounted to 3.2 t ha-1 in the south and 3.6 t ha-1 in the northwest. At 570 and 565 m-2 for the south and northwest respectively, mean weed densities did not differ between the regions, whereas the respective mean weed biomass of 697 and 1594 kg dry weight ha-1, respectively did differ. Weed abundance varied remarkably between single fields. The number of weed species was higher in the south than in the northwest. For example, Fumaria officinalis and Lamium spp. were found only in the south. Frequencies and abundances of Lapsana communis, Myosotis arvensis, Polygonum aviculare, Tripleurospermum inodorum, and Vicia spp. were higher in the south, whereas those of Elymus repens, Persicaria spp. and Spergula arvensis were higher in the northwest. The number of years since conversion to organic farming, i.e. long-term management, was one of the variables that explained the abundance of single weed species. E. repens was the weed species whose biomass increased most with the duration of organic farming. Another significant variable was crop biomass, which was affected by short-term management. The presence of different weed species was related to the duration of organic farming and to low crop yield. This finding demonstrated that it was not the organic farming regime per se, which resulted in high weed infestation and low yielding crops, but failures in the understanding and the management of organic farming systems. Successful weed control relies on farm- and field-specific long- and short-term management approaches. The agronomic productivity of ley and spring cereal crops managed by full-time farmers with an interest in organic farming was on the same level as of the mean for conventional farming. Given the many options for further improvements of the agronomic performance of organic arable systems, organic farming offers foundations for the development of sustainable agriculture. The main threat to the sustainability of farming in Finland, both conventional and organic, is the spatial separation of crop production and animal husbandry by region, along with the simplification of associated crop rotations.

Dynamic Space Warping Of Strokes For Recognition Of Online Handwritten Characters

This paper suggests a scheme for classifying online handwritten characters, based on dynamic space warping of strokes within the characters. A method for segmenting components into strokes using velocity profiles is proposed. Each stroke is a simple arbitrary shape and is encoded using three attributes. Correspondence between various strokes is established using Dynamic Space Warping. A distance measure which reliably differentiates between two corresponding simple shapes (strokes) has been formulated thus obtaining a perceptual distance measure between any two characters. Tests indicate an accuracy of over 85% on two different datasets of characters.

Agronomic indices, growth, yield-contributing traits, and yield of dry-seeded rice under varying herbicides

Dry-seeded rice (DSR) is an emerging resource-conserving technology in many Asian countries, but weeds remain the major threat to the production of DSR systems. A field study was conducted in 2012 and 2013 at the International Rice Research Institute (IRRI), Los Baños, Philippines, to evaluate the performance of sole and sequential applications of preemergence (oxadiazon and pendimethalin), early postemergence (butachlor + propanil and thiobencarb + 2,4-D), and late postemergence herbicides (bispyribac-sodium and fenoxaprop + ethoxysulfuron) with different modes of action in comparison to manual weeding in DSR. The sequential applications of all preemergence and postemergence herbicides reduced weed density and biomass by 80–100% compared to the nontreated plots. The sole application of postemergence herbicides reduced weed density by only 44–54% and weed biomass by 51–61%, whereas oxadiazon alone reduced weed density and biomass by 96–100%. All herbicide treatments and manual weeding significantly affected tiller number, biomass, crop growth rate, agronomic indices, yield-contributing parameters (panicle density and filled grains), and yield (biological and grain) of rice. The highest grain yield was obtained in the manually weeded plots (5.9–6.1 t ha−1) and the plots treated with oxadiazon alone (5.4–5.6 t ha−1) and oxadiazon followed by postemergence herbicides (5.2–5.8 t ha−1). The lowest paddy yield (0.22 t ha−1) was achieved in the nontreated plots followed by the plots treated with the sole application of bispyribac-sodium and fenoxaprop + ethoxysulfuron. The results suggest that oxadiazon is the best broad-spectrum and economically effective herbicide when applied alone or in combination with other effective postemergence herbicides with different modes of action, depending on the weed species present in the field.

What's up with Twitter, in fewer than 10,000 characters

The internet erupted in outrage last week at reports that Twitter is poised to increase the limit for tweets from 140 to 10,000 characters. The first rumours of such a move emerged in the tech news website Re/code back in September then again last week. The response on Twitter was immediate and, for the most part, somewhere between incensed and bemused, with many thousands of tweets posted with hashtags such as #10kTwitter, #Twitter10k, #10000gate, #140twitter, #beyond140 and #longtweets...

Agronomic benefits and risks associated with the irrigated peanut–maize production system under a changing climate in northern Australia

With the aim of increasing peanut production in Australia, the Australian peanut industry has recently considered growing peanuts in rotation with maize at Katherine in the Northern Territory—a location with a semi-arid tropical climate and surplus irrigation capacity. We used the well-validated APSIM model to examine potential agronomic benefits and long-term risks of this strategy under the current and warmer climates of the new region. Yield of the two crops, irrigation requirement, total soil organic carbon (SOC), nitrogen (N) losses and greenhouse gas (GHG) emissions were simulated. Sixteen climate stressors were used; these were generated by using global climate models ECHAM5, GFDL2.1, GFDL2.0 and MRIGCM232 with a median sensitivity under two Special Report of Emissions Scenarios over the 2030 and 2050 timeframes plus current climate (baseline) for Katherine. Effects were compared at three levels of irrigation and three levels of N fertiliser applied to maize grown in rotations of wet-season peanut and dry-season maize (WPDM), and wet-season maize and dry-season peanut (WMDP). The climate stressors projected average temperature increases of 1°C to 2.8°C in the dry (baseline 24.4°C) and wet (baseline 29.5°C) seasons for the 2030 and 2050 timeframes, respectively. Increased temperature caused a reduction in yield of both crops in both rotations. However, the overall yield advantage of WPDM increased from 41% to up to 53% compared with the industry-preferred sequence of WMDP under the worst climate projection. Increased temperature increased the irrigation requirement by up to 11% in WPDM, but caused a smaller reduction in total SOC accumulation and smaller increases in N losses and GHG emission compared with WMDP. We conclude that although increased temperature will reduce productivity and total SOC accumulation, and increase N losses and GHG emissions in Katherine or similar northern Australian environments, the WPDM sequence should be preferable over the industry-preferred sequence because of its overall yield and sustainability advantages in warmer climates. Any limitations of irrigation resulting from climate change could, however, limit these advantages.

Machine recognition of online handwritten Devanagari characters

In this paper, we describe a system for the automatic recognition of isolated handwritten Devanagari characters obtained by linearizing consonant conjuncts. Owing to the large number of characters and resulting demands on data acquisition, we use structural recognition techniques to reduce some characters to others. The residual characters are then classified using the subspace method. Finally the results of structural recognition and feature-based matching are mapped to give final output. The proposed system Ifs evaluated for the writer dependent scenario.

Resolving Ambiguities in Confused Online Tamil Characters with Post Processing Algorithms

This paper addresses the problem of resolving ambiguities in frequently confused online Tamil character pairs by employing script specific algorithms as a post classification step. Robust structural cues and temporal information of the preprocessed character are extensively utilized in the design of these algorithms. The methods are quite robust in automatically extracting the discriminative sub-strokes of confused characters for further analysis. Experimental validation on the IWFHR Database indicates error rates of less than 3 % for the confused characters. Thus, these post processing steps have a good potential to improve the performance of online Tamil handwritten character recognition.

CHITRA: Cognitive handprinted input-trained recursively analyzing system for recognition of alphanumeric characters

A novel system for recognition of handprinted alphanumeric characters has been developed and tested. The system can be employed for recognition of either the alphabet or the numeral by contextually switching on to the corresponding branch of the recognition algorithm. The two major components of the system are the multistage feature extractor and the decision logic tree-type catagorizer. The importance of ldquogoodrdquo features over sophistication in the classification procedures was recognized, and the feature extractor is designed to extract features based on a variety of topological, morphological and similar properties. An information feedback path is provided between the decision logic and the feature extractor units to facilitate an interleaved or recursive mode of operation. This ensures that only those features essential to the recognition of a particular sample are extracted each time. Test implementation has demonstrated the reliability of the system in recognizing a variety of handprinted alphanumeric characters with close to 100% accuracy.

Fusion of Complementary Online and Offline Strategies for Recognition of Handwritten Kannada Characters

This work describes an online handwritten character recognition system working in combination with an offline recognition system. The online input data is also converted into an offline image, and parallely recognized by both online and offline strategies. Features are proposed for offline recognition and a disambiguation step is employed in the offline system for the samples for which the confidence level of the classifier is low. The outputs are then combined probabilistically resulting in a classifier out-performing both individual systems. Experiments are performed for Kannada, a South Indian Language, over a database of 295 classes. The accuracy of the online recognizer improves by 11% when the combination with offline system is used.

Recognition of Kannada characters extracted from scene images

In this paper, we describe a method for feature extraction and classification of characters manually isolated from scene or natural images. Characters in a scene image may be affected by low resolution, uneven illumination or occlusion. We propose a novel method to perform binarization on gray scale images by minimizing energy functional. Discrete Cosine Transform and Angular Radial Transform are used to extract the features from characters after normalization for scale and translation. We have evaluated our method on the complete test set of Chars74k dataset for English and Kannada scripts consisting of handwritten and synthesized characters, as well as characters extracted from camera captured images. We utilize only synthesized and handwritten characters from this dataset as training set. Nearest neighbor classification is used in our experiments.

Phenotypic characters of rice landraces reveal independent lineages of short-grain aromatic indica rice

Rice landraces are lineages developed by farmers through artificial selection during the long-term domestication process. Despite huge potential for crop improvement, they are largely understudied in India. Here, we analyse a suite of phenotypic characters from large numbers of Indian landraces comprised of both aromatic and non-aromatic varieties. Our primary aim was to investigate the major determinants of diversity, the strength of segregation among aromatic and non-aromatic landraces as well as that within aromatic landraces. Using principal component analysis, we found that grain length, width and weight, panicle weight and leaf length have the most substantial contribution. Discriminant analysis can effectively distinguish the majority of aromatic from non-aromatic landraces. More interestingly, within aromatic landraces long-grain traditional Basmati and short-grain non-Basmati aromatics remain morphologically well differentiated. The present research emphasizes the general patterns of phenotypic diversity and finds out the most important characters. It also confirms the existence of very unique short-grain aromatic landraces, perhaps carrying signatures of independent origin of an additional aroma quantitative trait locus in the indica group, unlike introgression of specific alleles of the BADH2 gene from the japonica group as in Basmati. We presume that this parallel origin and evolution of aroma in short-grain indica landraces are linked to the long history of rice domestication that involved inheritance of several traits from Oryza nivara, in addition to O. rufipogon. We conclude with a note that the insights from the phenotypic analysis essentially comprise the first part, which will likely be validated with subsequent molecular analysis.