On Visual Detection of Highly-occluded Objects for Harvesting Automation in Horticulture

Developing accurate and reliable crop detection algorithms is an important step for harvesting automation in horticulture. This paper presents a novel approach to visual detection of highly-occluded fruits. We use a conditional random field (CRF) on multi-spectral image data (colour and Near-Infrared Reflectance, NIR) to model two classes: crop and background. To describe these two classes, we explore a range of visual-texture features including local binary pattern, histogram of oriented gradients, and learn auto-encoder features. The pro-posed methods are evaluated using hand-labelled images from a dataset captured on a commercial capsicum farm. Experimental results are presented, and performance is evaluated in terms of the Area Under the Curve (AUC) of the precision-recall curves.Our current results achieve a maximum performance of 0.81AUC when combining all of the texture features in conjunction with colour information.

Nonparametric rank regression for analyzing water quality concentration data with multiple detection limits

Environmental data usually include measurements, such as water quality data, which fall below detection limits, because of limitations of the instruments or of certain analytical methods used. The fact that some responses are not detected needs to be properly taken into account in statistical analysis of such data. However, it is well-known that it is challenging to analyze a data set with detection limits, and we often have to rely on the traditional parametric methods or simple imputation methods. Distributional assumptions can lead to biased inference and justification of distributions is often not possible when the data are correlated and there is a large proportion of data below detection limits. The extent of bias is usually unknown. To draw valid conclusions and hence provide useful advice for environmental management authorities, it is essential to develop and apply an appropriate statistical methodology. This paper proposes rank-based procedures for analyzing non-normally distributed data collected at different sites over a period of time in the presence of multiple detection limits. To take account of temporal correlations within each site, we propose an optimal linear combination of estimating functions and apply the induced smoothing method to reduce the computational burden. Finally, we apply the proposed method to the water quality data collected at Susquehanna River Basin in United States of America, which dearly demonstrates the advantages of the rank regression models.

Statistical power calculation and sample size determination for environmental studies with data below detection limits

Power calculation and sample size determination are critical in designing environmental monitoring programs. The traditional approach based on comparing the mean values may become statistically inappropriate and even invalid when substantial proportions of the response values are below the detection limits or censored because strong distributional assumptions have to be made on the censored observations when implementing the traditional procedures. In this paper, we propose a quantile methodology that is robust to outliers and can also handle data with a substantial proportion of below-detection-limit observations without the need of imputing the censored values. As a demonstration, we applied the methods to a nutrient monitoring project, which is a part of the Perth Long-Term Ocean Outlet Monitoring Program. In this example, the sample size required by our quantile methodology is, in fact, smaller than that by the traditional t-test, illustrating the merit of our method.

Thin-Layer Chromatography with Ultraviolet and Mass Spectrometric Detection: From Preparative-Layer to Miniaturized Ultra-Thin-Layer Technique

The present challenge in drug discovery is to synthesize new compounds efficiently in minimal time. The trend is towards carefully designed and well-characterized compound libraries because fast and effective synthesis methods easily produce thousands of new compounds. The need for rapid and reliable analysis methods is increased at the same time. Quality assessment, including the identification and purity tests, is highly important since false (negative or positive) results, for instance in tests of biological activity or determination of early-ADME parameters in vitro (the pharmacokinetic study of drug absorption, distribution, metabolism, and excretion), must be avoided. This thesis summarizes the principles of classical planar chromatographic separation combined with ultraviolet (UV) and mass spectrometric (MS) detection, and introduces powerful, rapid, easy, low-cost, and alternative tools and techniques for qualitative and quantitative analysis of small drug or drug-like molecules. High performance thin-layer chromatography (HPTLC) was introduced and evaluated for fast semi-quantitative assessment of the purity of synthesis target compounds. HPTLC methods were compared with the liquid chromatography (LC) methods. Electrospray ionization mass spectrometry (ESI MS) and atmospheric pressure matrix-assisted laser desorption/ionization MS (AP MALDI MS) were used to identify and confirm the product zones on the plate. AP MALDI MS was rapid, and easy to carry out directly on the plate without scraping. The PLC method was used to isolate target compounds from crude synthesized products and purify them for bioactivity and preliminary ADME tests. Ultra-thin-layer chromatography (UTLC) with AP MALDI MS and desorption electrospray ionization mass spectrometry (DESI MS) was introduced and studied for the first time. Because of the thinner adsorbent layer, the monolithic UTLC plate provided 10 100 times better sensitivity in MALDI analysis than did HPTLC plates. The limits of detection (LODs) down to low picomole range were demonstrated for UTLC AP MALDI and UTLC DESI MS. In a comparison of AP and vacuum MALDI MS detection for UTLC plates, desorption from the irregular surface of the plates with the combination of an external AP MALDI ion source and an ion trap instrument provided clearly less variation in mass accuracy than the vacuum MALDI time-of-flight (TOF) instrument. The performance of the two-dimensional (2D) UTLC separation with AP MALDI MS method was studied for the first time. The influence of the urine matrix on the separation and the repeatability was evaluated with benzodiazepines as model substances in human urine. The applicability of 2D UTLC AP MALDI MS was demonstrated in the detection of metabolites in an authentic urine sample.

Abacá mosaic virus: a distinct strain of Sugarcane mosaic virus

Abacá mosaic virus (AbaMV) is related to members of the sugarcane mosaic virus subgroup of the genus Potyvirus. The ~2 kb 3′ terminal region of the viral genome was sequenced and, in all areas analysed, found to be most similar to Sugarcane mosaic virus (SCMV) and distinct from Johnsongrass mosaic virus (JGMV), Maize dwarf mosaic virus (MDMV) and Sorghum mosaic virus (SrMV). Cladograms of the 3′ terminal region of the NIb protein, the coat protein core and the 3′ untranslated region showed that AbaMV clustered with SCMV, which was a distinct clade and separate from JGMV, MDMV and SrMV. The N-terminal region of the AbaMV coat protein had a unique amino acid repeat motif different from those previously published for other strains of SCMV. The first experimental transmission of AbaMV from abacá (Musa textilis) to banana (Musa sp.), using the aphid vectors Rhopalosiphum maidis and Aphis gossypii, is reported. Polyclonal antisera for the detection of AbaMV in western blot assays and ELISA were prepared from recombinant coat protein expressed in E. coli. A reverse transcriptase PCR diagnostic assay, with microtitre plate colourimetric detection, was developed to discriminate between AbaMV and Banana bract mosaic virus, another Musa-infecting potyvirus. Sequence data, host reactions and serological relationships indicate that AbaMV should be considered a distinct strain of SCMV, and the strain designation SCMV-Ab is suggested.

Learning Temporal Alignment Uncertainty for Efficient Event Detection

In this paper we tackle the problem of efficient video event detection. We argue that linear detection functions should be preferred in this regard due to their scalability and efficiency during estimation and evaluation. A popular approach in this regard is to represent a sequence using a bag of words (BOW) representation due to its: (i) fixed dimensionality irrespective of the sequence length, and (ii) its ability to compactly model the statistics in the sequence. A drawback to the BOW representation, however, is the intrinsic destruction of the temporal ordering information. In this paper we propose a new representation that leverages the uncertainty in relative temporal alignments between pairs of sequences while not destroying temporal ordering. Our representation, like BOW, is of a fixed dimensionality making it easily integrated with a linear detection function. Extensive experiments on CK+, 6DMG, and UvA-NEMO databases show significant performance improvements across both isolated and continuous event detection tasks.

Genetic variability of Tomato spotted wilt virus in Australia and validation of real time RT-PCR for its detection in single and bulked leaf samples

The potential for large-scale use of a sensitive real time reverse transcription polymerase chain reaction (RT-PCR) assay was evaluated for the detection of Tomato spotted wilt virus (TSWV) in single and bulked leaf samples by comparing its sensitivity with that of DAS-ELISA. Using total RNA extracted with RNeasy® or leaf soak methods, real time RT-PCR detected TSWV in all infected samples collected from 16 horticultural crop species (including flowers, herbs and vegetables), two arable crop species, and four weed species by both assays. In samples in which DAS-ELISA had previously detected TSWV, real time RT-PCR was effective at detecting it in leaf tissues of all 22 plant species tested at a wide range of concentrations. Bulk samples required more robust and extensive extraction methods with real time RT-PCR, but it generally detected one infected sample in 1000 uninfected ones. By contrast, ELISA was less sensitive when used to test bulked samples, once detecting up to 1 infected in 800 samples with pepper but never detecting more than 1 infected in 200 samples in tomato and lettuce. It was also less reliable than real time RT-PCR when used to test samples from parts of the leaf where the virus concentration was low. The genetic variability among Australian isolates of TSWV was small. Direct sequencing of a 587 bp region of the nucleoprotein gene (S RNA) of 29 isolates from diverse crops and geographical locations yielded a maximum of only 4.3% nucleotide sequence difference. Phylogenetic analysis revealed no obvious groupings of isolates according to geographic origin or host species. TSWV isolates, that break TSWV resistance genes in tomato or pepper did not differ significantly in the N gene region studied, indicating that a different region of the virus genome is responsible for this trait.

Peanut stripe potyvirus resistance in peanut (Arachis hypogaea L.) plants carrying viral coat protein gene sequences

Peanut (Arachis hypogaea L.) lines exhibiting high levels of resistance to peanut stripe virus (PStV) were obtained following microprojectile bombardment of embryogenic callus derived from mature seeds. Fertile plants of the commercial cultivars Gajah and NC7 were regenerated following co-bombardmentwith the hygromycin resistance gene and one of two forms of the PStV coat protein (CP) gene, an untranslatable, full length sequence (CP2) or a translatable gene encoding a CP with an N-terminal truncation (CP4). High level resistance to PStV was observed for both transgenes when plants were challenged with the homologous virus isolate. The mechanism of resistance appears to be RNA-mediated, since plants carrying either the untranslatable CP2 or CP4 had no detectable protein expression, but were resistant or immune (no virus replication). Furthermore, highly resistant, but not susceptible CP2 T0 plants contained transgene-specific small RNAs. These plants now provide important germplasm for peanut breeding, particularly in countries where PStV is endemic and poses a major constraint to peanut production.

A simplified PCR test for early detection of dwarf off-types in micropropagated Cavendish bananas (Musa spp. AAA)

The dwarf somaclonal variant is a major problem affecting micropropagation of the banana cultivar Williams (Musa spp. AAA; subgroup Cavendish). This problem arises from genetic changes that occur during the tissue culture process. Early identification of this problem is difficult and propagators must wait until plants are ex vitro in order to visualise the dwarfism phenotype. In this study, we have improved a SCAR-based molecular diagnostic technique, developed by Damasco et al. [Acta Hortic. 461 (1997) 157], for the early identification of dwarf off-types. We have included a positive internal control in a multiplex PCR and adapted the technique for use with small amounts of fresh in vitro leaf material as PCR template. The control product is a 500 bp fragment from 18S rRNA and is amplified in all tissues irrespective of phenotype. The use of small in vitro leaf material removing the need for genomic DNA extraction.

Characterisation and early detection of an offtype from micropropagated Lady Finger bananas

An offtype has been identified from micropropagated Lady Finger bananas (Musa spp., AAB group, Pome subgroup) that is characterised by its slow growth and poor bunch size. Bunch weights were approximately 25% those of normal Lady Finger plants and all of the fruit produced was unmarketable. This particular offtype is the most commonly encountered from micropropagated Lady Finger plants and, in 2 instances, blocks of 3000 and 1500 plants were entirely comprised of this single offtype. Detection of offtype plants was possible during establishment and growth of plants in the glasshouse by the presence of chlorotic streaks in the leaves. In more severe cases the streaks coalesced into chlorotic patches that developed thin, necrotic areas that eventually produced holes or splits in the leaves. Symptom expression was not ameliorated by the addition of fertiliser and even though symptoms were similar to severe Ca and B deficiency, both normal and offtype plants had similar levels of these elements in the leaves. The offtype plants were also slow growing in the glasshouse and produced significantly (P<0.05) smaller pseudostems and leaves than normal plants. Offtype plants could be readily detected after 4 weeks deflasking using the presence of chlorotic streaks in the leaves as the main selection criterion. Maximum discrimination was possible between weeks 5–7 and at the 6-leaf stage when all of the offtypes could be detected.

Pasteurella multocida detection by 5' Taq nuclease assay: a new tool for use in diagnosing fowl cholera

A 5′ Taq nuclease assay utilising minor groove binder technology and targeting the 16S rRNA gene was designed to detect Pasteurella multocida (the causative agent of fowl cholera) in swabs collected from poultry. The assay was first evaluated using pure cultures. The assay correctly identified four P. multocida taxonomic type strains, 18 P. multocida serovar reference strains and 40 Australian field isolates (17 from poultry, 11 from pigs and 12 from cattle). Representatives of nine other Pasteurella species, 26 other bacterial species (18 being members of the family Pasteurellaceae) and four poultry virus isolates did not react in the assay. The assay detected a minimum of approximately 10 cfu of P. multocida per reaction. Of 79 poultry swabs submitted to the laboratory for routine bacteriological culture, 17 were positive in the 5′ Taq nuclease assay, but only 10 were positive by culture. The other 62 swabs were negative for P. multocida by both 5′ Taq nuclease assay and culture. The assay is suitable for use in diagnosing fowl cholera, is more rapid than bacteriological culture, and may also have application in diagnosing P. multocida infections in cattle and pigs.

A universal test to determine the integrity of RNA, and its suitability for reverse transcription, in animal tissue laboratory specimens

Degradation of RNA in diagnostic specimens can cause false-negative test results and potential misdiagnosis when tests rely on the detection of specific RNA sequence. Current molecular methods of checking RNA integrity tend to be host species or group specific, necessitating libraries of primers and reaction conditions. The objective here was to develop a universal (multi-species) quality assurance tool for determining the integrity of RNA in animal tissues submitted to a laboratory for analyses. Ribosomal RNA (16S rRNA) transcribed from the mitochondrial 16S rDNA was used as template material for reverse transcription to cDNA and was amplified using polymerase chain reaction (PCR). As mitochondrial DNA has a high level of conservation, the primers used were shown to reverse transcribe and amplify RNA from every animal species tested. Deliberate degradation of rRNA template through temperature abuse of samples resulted in no reverse transcription and amplification. Samples spiked with viruses showed that single-stranded viral RNA and rRNA in the same sample degraded at similar rates, hence reverse transcription and PCR amplification of 16S rRNA could be used as a test of sample integrity and suitability for analysis that required the sample's RNA, including viral RNA. This test will be an invaluable quality assurance tool for determination of RNA integrity from tissue samples, thus avoiding erroneous test results that might occur if degraded target RNA is used unknowingly as template material for reverse transcription and subsequent PCR amplification.

Detection of Arcobacter spp. in piggery effluent and effluent-irrigated soils in southeast Queensland

Aims: To investigate the occurrence and levels of Arcobacter spp. in pig effluent ponds and effluent-treated soil. Methods and Results: A Most Probable Number (MPN) method was developed to assess the levels of Arcobacter spp. in seven pig effluent ponds and six effluent-treated soils, immediately after effluent irrigation. Arcobacter spp. levels in the effluent ponds varied from 6.5 × 105 to 1.1 × 108 MPN 100 ml-1 and in freshly irrigated soils from 9.5 × 102 to 2.8 × 104 MPN g-1 in all piggery environments tested. Eighty-three Arcobacter isolates were subjected to an abbreviated phenotypic test scheme and examined using a multiplex polymerase chain reaction (PCR). The PCR identified 35% of these isolates as Arcobacter butzleri, 49% as Arcobacter cryaerophilus while 16% gave no band. All 13 nonreactive isolates were subjected to partial 16S rDNA sequencing and showed a high similarity (>99%) to Arcobacter cibarius. Conclusions: A. butzleri, A. cryaerophilus and A. cibarius were isolated from both piggery effluent and effluent-irrigated soil, at levels suggestive of good survival in the effluent pond. Significance and Impact of the Study: This is the first study to provide quantitative information on Arcobacter spp. levels in piggery effluent and to associate A. cibarius with pigs and piggery effluent environments.

Identification of viral and non-viral reverse transcribing elements in pineapple ( Ananas comosus ), including members of two new badnavirus species

A previously published partial sequence of pineapple bacilliform virus was shown to be from a retrotransposon (family Metaviridae) and not from a badnavirus as previously thought. Two newly discovered sequence groups isolated from pineapple were associated with bacilliform virions and were transmitted by mealybugs. Phylogenetic analyses indicated that they were members of new badnavirus species. A third caulimovirid sequence was also amplified from pineapple, but available evidence suggests that this DNA is not encapsidated, but more likely derived from an endogenous virus.