Estimating crop area using seasonal time series of enhanced vegetation index from MODIS satellite imagery

Cereal grain is one of the main export commodities of Australian agriculture. Over the past decade, crop yield forecasts for wheat and sorghum have shown appreciable utility for industry planning at shire, state, and national scales. There is now an increasing drive from industry for more accurate and cost-effective crop production forecasts. In order to generate production estimates, accurate crop area estimates are needed by the end of the cropping season. Multivariate methods for analysing remotely sensed Enhanced Vegetation Index (EVI) from 16-day Moderate Resolution Imaging Spectroradiometer (MODIS) satellite imagery within the cropping period (i.e. April-November) were investigated to estimate crop area for wheat, barley, chickpea, and total winter cropped area for a case study region in NE Australia. Each pixel classification method was trained on ground truth data collected from the study region. Three approaches to pixel classification were examined: (i) cluster analysis of trajectories of EVI values from consecutive multi-date imagery during the crop growth period; (ii) harmonic analysis of the time series (HANTS) of the EVI values; and (iii) principal component analysis (PCA) of the time series of EVI values. Images classified using these three approaches were compared with each other, and with a classification based on the single MODIS image taken at peak EVI. Imagery for the 2003 and 2004 seasons was used to assess the ability of the methods to determine wheat, barley, chickpea, and total cropped area estimates. The accuracy at pixel scale was determined by the percent correct classification metric by contrasting all pixel scale samples with independent pixel observations. At a shire level, aggregated total crop area estimates were compared with surveyed estimates. All multi-temporal methods showed significant overall capability to estimate total winter crop area. There was high accuracy at pixel scale (>98% correct classification) for identifying overall winter cropping. However, discrimination among crops was less accurate. Although the use of single-date EVI data produced high accuracy for estimates of wheat area at shire scale, the result contradicted the poor pixel-scale accuracy associated with this approach, due to fortuitous compensating errors. Further studies are needed to extrapolate the multi-temporal approaches to other geographical areas and to improve the lead time for deriving cropped-area estimates before harvest.

Inter-seasonal population dynamics and pest status of Bemisia tabaci (Gennadius) biotype B in an Australian cropping system

Bemisia tabaci, biotype B, commonly known as the silverleaf whitefly (SLW) is an alien species that invaded Australia in the mid-90s. This paper reports on the invasion ecology of SLW and the factors that are likely to have contributed to the first outbreak of this major pest in an Australian cotton cropping system, population dynamics of SLW within whitefly-susceptible crop (cotton and cucurbit) and non-crop vegetation (sowthistle, Sonchus spp.) components of the cropping system were investigated over four consecutive growing seasons (September-June) 2001/02-2004/05 in the Emerald Irrigation Area (EIA) of Queensland, Australia. Based on fixed geo-referenced sampling sites, variation in spatial and temporal abundance of SLW within each system component was quantified to provide baseline data for the development of ecologically sustainable pest management strategies. Parasitism of large (3rd and 4th instars) SLW nymphs by native aphelinid wasps was quantified to determine the potential for natural control of SLW populations. Following the initial outbreak in 2001/02, SLW abundance declined and stabilised over the next three seasons. The population dynamics of SLW is characterised by inter-seasonal population cycling between the non-crop (weed) and cotton components of the EIA cropping system. Cotton was the largest sink for and source of SLW during the study period. Over-wintering populations dispersed from weed host plant sources to cotton in spring followed by a reverse dispersal in late summer and autumn to broad-leaved crops and weeds. A basic spatial source-sink analysis showed that SLW adult and nymph densities were higher in cotton fields that were closer to over-wintering weed sources throughout spring than in fields that were further away. Cucurbit fields were not significant sources of SLW and did not appear to contribute significantly to the regional population dynamics of the pest. Substantial parasitism of nymphal stages throughout the study period indicates that native parasitoid species and other natural enemies are important sources of SLW mortality in Australian cotton production systems. Weather conditions and use of broad-spectrum insecticides for pest control are implicated in the initial outbreak and on-going pest status of SLW in the region.

Seasonal changes in pasture quality and diet selection and their relationship with liveweight gain of steers grazing tropical grass and grass-legume pastures in northern Australia.

The variation in liveweight gain in grazing beef cattle as influenced by pasture type, season and year effects has important economic implications for mixed crop-livestock systems and the ability to better predict such variation would benefit beef producers by providing a guide for decision making. To identify key determinants of liveweight change of Brahman-cross steers grazing subtropical pastures, measurements of pasture quality and quantity, and diet quality in parallel with liveweight were made over two consecutive grazing seasons (48 and 46 weeks, respectively), on mixed Clitoria ternatea/grass, Stylosanthes seabrana/grass and grass swards (grass being a mixture of Bothriochloa insculpta cv. Bisset, Dichanthium sericeum and Panicum maximum var. trichoglume cv. Petrie). Steers grazing the legume-based pastures had the highest growth rate and gained between 64 and 142 kg more than those grazing the grass pastures in under 12 months. Using an exponential model, green leaf mass, green leaf %, adjusted green leaf % (adjusted for inedible woody legume stems), faecal near infrared reflectance spectroscopy predictions of diet crude protein and diet dry matter digestibility, accounted for 77, 74, 80, 63 and 60%, respectively, of the variation in daily weight gain when data were pooled across pasture types and grazing seasons. The standard error of the regressions indicated that 95% prediction intervals were large (+/- 0.42-0.64 kg/head.day) suggesting that derived regression relationships have limited practical application for accurately estimating growth rate. In this study, animal factors, especially compensatory growth effects, appeared to have a major influence on growth rate in relation to pasture and diet attributes. It was concluded that predictions of growth rate based only on pasture or diet attributes are unlikely to be accurate or reliable. Nevertheless, key pasture attributes such as green leaf mass and green leaf% provide a robust indication of what proportion of the potential growth rate of the grazing animals can be achieved.

Epidemiological data of seasonal variation in mood and behaviour

The aim of this study was to measure seasonal variation in mood and behaviour. The dual vulnerability and latitude effect hypothesis, the risk of increased appetite, weight and other seasonal symptoms to develop metabolic syndrome, and perception of low illumination in quality of life and mental well-being were assessed. These variations are prevalent in persons who live in high latitudes and need balancing of metabolic processes to adapt to environmental changes due to seasons. A randomized sample of 8028 adults aged 30 and over (55% women) participated in an epidemiological health examination study, The Health 2000, applying the probability proportional to population size method for a range of socio-demographic characteristics. They were present in a face-to-face interview at home and health status examination. The questionnaires included the modified versions of the Seasonal Pattern Assessment Questionnaire (SPAQ) and Beck Depression Inventory (BDI), the Health Related Quality of Life (HRQoL) instrument 15D, and the General Health Questionnaire (GHQ). The structured and computerized Munich Composite International Diagnostic Interview (M-CIDI) as part of the interview was used to assess diagnoses of mental disorders, and, the National Cholesterol Education Program Adult Treatment Panel III (NCEP-ATPIII) criteria were assessed using all the available information to detect metabolic syndrome. A key finding was that 85% of this nationwide representative sample had seasonal variation in mood and behaviour. Approximately 9% of the study population presented combined seasonal and depressive symptoms with a significant association between their scores, and 2.6% had symptoms that corresponded to Seasonal Affective Disorder (SAD) in severity. Seasonal variations in weight and appetite are two important components that increase the risk of metabolic syndrome. Other factors such as waist circumference and major depressive disorder contributed to the metabolic syndrome as well. Persons reported of having seasonal symptoms were associated with a poorer quality of life and compromised mental well-being, especially if indoors illumination at home and/or at work was experienced as being low. Seasonal and circadian misalignments are suggested to associate with metabolic disorders, and could be remarked if individuals perceive low illumination levels at home and/or at work that affect the health-related quality of life and mental well-being. Keywords: depression, health-related quality of life, illumination, latitude, mental well-being, metabolic syndrome, seasonal variation, winter.

Studying the diurnal and seasonal acclimation of photosystem Ii using chlorophyll-a fluorescence

A small fraction of the energy absorbed in the light reactions of photosynthesis is re-emitted as chlorophyll-a fluorescence. Chlorophyll-a fluorescence and photochemistry compete for excitation energy in photosystem II (PSII). Therefore, changes in the photochemical capacity can be detected through analysis of chlorophyll fluorescence. Chlorophyll fluorescence techniques have been widely used to follow the diurnal (fast), and the seasonal (slow) acclimation in the energy partitioning between photochemical and non-photochemical processes in PSII. Energy partitioning in PSII estimated through chlorophyll fluorescence can be used as a proxy of the plant physiological status, and measured at different spatial and temporal scales. However, a number of technical and theoretical limitations still limit the use of chlorophyll fluorescence data for the study of the acclimation of PSII. The aim of this Thesis was to study the diurnal and seasonal acclimation of PSII in field conditions through the development and testing of new chlorophyll fluorescence-based tools, overcoming these limitations. A new model capable of following the fast acclimation of PSII to rapid fluctuations in light intensity was developed. The model was used to study the rapid acclimation in the electron transport rate under fluctuating light. Additionally, new chlorophyll fluorescence parameters were developed for estimating the seasonal acclimation in the sustained rate constant of thermal energy dissipation and photochemistry. The parameters were used to quantitatively evaluate the effect of light and temperature on the seasonal acclimation of PSII. The results indicated that light environment not only affected the degree but also the kinetics of response of the acclimation to temperature, which was attributed to differences in the structural organization of PSII during seasonal acclimation. Furthermore, zeaxanthin-facilitated thermal dissipation appeared to be the main mechanisms modulating the fraction of absorbed energy being dissipated thermally during winter in field Scots pine. Finally, the integration between diurnal and seasonal acclimation mechanisms was studied using a recently developed instrument MONI-PAM (Walz GmbH, Germany) capable of continuously monitoring the energy partitioning in PSII.

Latitudinal and seasonal effects on growth of the Australian eastern king prawn (Melicertus plebejus)

The growth of the Australian eastern king prawn (Melicertus plebejus) is understood in greater detail by quantifying the latitudinal effect. The latitudinal effect is the change in the species’ growth rate during migration. Mark–recapture data (N = 1635, latitude 22.21°S–34.00°S) presents northerly movement of the eastern king prawn, with New South Wales prawns showing substantial average movement of 140 km (standard deviation: 176 km) north. A generalized von Bertalanffy growth model framework is used to incorporate the latitudinal effect together with the canonical seasonal effect. Applying this method to eastern king prawn mark–recapture data guarantees consistent estimates for the latitudinal and seasonal effects. For M. plebejus, it was found that growth rate peaks on 25 and 29 January for males and females, respectively; is at a minimum on 27 and 31 July, respectively; and that the shape parameter, k (per year), changes by –0.0236 and –0.0556 every 1 degree of latitude south increase for males and females, respectively.

Effects of seasonal variability on FT-NIR prediction of dry matter content for whole Hass avocado fruit

Fourier Transform (FT)-near infra-red spectroscopy (NIRS) was investigated as a non-invasive technique for estimating percentage (%) dry matter of whole intact 'Hass' avocado fruit. Partial least squares (PLS) calibration models were developed from the diffuse reflectance spectra to predict % dry matter, taking into account effects of seasonal variation. It is found that seasonal variability has a significant effect on model predictive performance for dry matter in avocados. The robustness of the calibration model, which in general limits the application for the technique, was found to increase across years (seasons) when more seasonal variability was included in the calibration set. The R-v(2) and RMSEP for the single season prediction models predicting on an independent season ranged from 0.09 to 0.61 and 2.63 to 5.00, respectively, while for the two season models predicting on the third independent season, they ranged from 0.34 to 0.79 and 2.18 to 2.50, respectively. The bias for single season models predicting an independent season was as high as 4.429 but <= 1.417 for the two season combined models. The calibration model encompassing fruit from three consecutive years yielded predictive statistics of R-v(2) = 0.89, RMSEP = 1.43% dry matter with a bias of -0.021 in the range 16.1-39.7% dry matter for the validation population encompassing independent fruit from the three consecutive years. Relevant spectral information for all calibration models was obtained primarily from oil, carbohydrate and water absorbance bands clustered in the 890-980, 1005-1050, 1330-1380 and 1700-1790 nm regions. These results indicate the potential of FT-NIRS, in diffuse reflectance mode, to non-invasively predict the % dry matter of whole 'Hass' avocado fruit and the importance of the development of a calibration model that incorporates seasonal variation. Crown Copyright (c) 2012 Published by Elsevier B.V. All rights reserved.

Seasonal abundance of thrips (Thysanoptera) in capsicum and chilli crops in south-east Queensland, Australia

Thrips can be important pests of capsicum and chilli crops, causing damage through their feeding and by vectoring viral diseases. As different species vary in their ability to transmit viruses and in their susceptibility to insecticides, it is important to know which species are present in a crop. The seasonal occurrence of thrips in capsicum and chilli crops in the Bundaberg district of south-east Queensland was investigated from July 2002 to June 2003. Fifty flowers were collected weekly from crops on seven farms and the adult thrips extracted and identified. Thrips palmi Karny and Frankliniella occidentalis (Pergande) were collected in the greatest numbers, with T. palmi predominant in autumn crops (March to July) and F. occidentalis predominant in spring crops (August to November). Pseudanaphothrips achaetus (Bagnall) was common, while Thrips tabaci Lindeman, Thrips imaginis Bagnall and Frankliniella schultzei (Trybom) were collected in low numbers.

Sources and seasonal dynamics of Alternaria inoculum associated with leaf blotch and fruit spot of apples

Alternaria leaf blotch and fruit spot caused by Alternaria spp. cause annual losses to the Australian apple industry. Control options are limited, mainly due to a lack of understanding of the disease cycle. Therefore, this study aimed to determine potential sources of Alternaria spp. inoculum in the orchard and examine their relative contribution throughout the production season. Leaf residue from the orchard floor, canopy leaves, twigs and buds were collected monthly from three apple orchards for two years and examined for the number of spores on their surface. In addition, the effects of climatic factors on spore production dynamics in each plant part were examined. Although all four plant parts tested contributed to the Alternaria inoculum in the orchard, significant higher numbers of spores were obtained from leaf residue than the other plant parts supporting the hypothesis that overwintering of Alternaria spp. occurred mainly in leaf residue and minimally on twigs and buds. The most significant period of spore production on leaf residue occurred from dormancy until bloom and on canopy leaves and twigs during the fruit growth stage. Temperature was the single most significant factor influencing the amount of Alternaria inoculum and rainfall and relative humidity showed strong associations with temperature influencing the spore production dynamics in Australian orchards. The practical implications of this study include the eradication of leaf residue from the orchard floor and sanitation of the canopy after harvest to remove residual spores from the trees.

Seasonal Greeting token-1981

Obverse: Emblem of the Israel Government and Medals Corporation. Reverse: A Jerusalem panorama, inscription.

Seasonal Greeting token-1977

Obverse: Within a circle (a symbol of the sun) an inscription. Reverse: The emblem of the Israel Government Coins and Medals Corporation, inscription.

Seasonal Greeting token-1976

Obverse: Stylized Star of David. Reverse: Emblem of the Israel Government Coins and Medals Corporation.

Seasonal Greeting token-1974

Obverse: Emblem of the 25th Anniversary of the State of Israel, menorah and number 25 created by ribbon. Reverse: Emblem of the Israel Government Coins and Medals Corporation.

Seasonal Greeting token-1973

Obverse: Stylized Desing of an Israeli Navy ship with rocket coming out of the canon. Reverse: Emblem of the Israel Government coins and Medals Corporation.