Annual forecasting of the Australian macadamia crop - integrating tree census data with statistical climate-adjustment models

To facilitate marketing and export, the Australian macadamia industry requires accurate crop forecasts. Each year, two levels of crop predictions are produced for this industry. The first is an overall longer-term forecast based on tree census data of growers in the Australian Macadamia Society (AMS). This data set currently accounts for around 70% of total production, and is supplemented by our best estimates of non-AMS orchards. Given these total tree numbers, average yields per tree are needed to complete the long-term forecasts. Yields from regional variety trials were initially used, but were found to be consistently higher than the average yields that growers were obtaining. Hence, a statistical model was developed using growers' historical yields, also taken from the AMS database. This model accounted for the effects of tree age, variety, year, region and tree spacing, and explained 65% of the total variation in the yield per tree data. The second level of crop prediction is an annual climate adjustment of these overall long-term estimates, taking into account the expected effects on production of the previous year's climate. This adjustment is based on relative historical yields, measured as the percentage deviance between expected and actual production. The dominant climatic variables are observed temperature, evaporation, solar radiation and modelled water stress. Initially, a number of alternate statistical models showed good agreement within the historical data, with jack-knife cross-validation R2 values of 96% or better. However, forecasts varied quite widely between these alternate models. Exploratory multivariate analyses and nearest-neighbour methods were used to investigate these differences. For 2001-2003, the overall forecasts were in the right direction (when compared with the long-term expected values), but were over-estimates. In 2004 the forecast was well under the observed production, and in 2005 the revised models produced a forecast within 5.1% of the actual production. Over the first five years of forecasting, the absolute deviance for the climate-adjustment models averaged 10.1%, just outside the targeted objective of 10%.

Pre-anthesis ovary development determines genotypic differences in potential kernel weight in sorghum

Kernel weight is an important factor determining grain yield and nutritional quality in sorghum, yet the developmental processes underlying the genotypic differences in potential kernel weight remain unclear. The aim of this study was to determine the stage in development at which genetic effects on potential kernel weight were realized, and to investigate the developmental mechanisms by which potential kernel weight is controlled in sorghum. Kernel development was studied in two field experiments with five genotypes known to differ in kernel weight at maturity. Pre-fertilization floret and ovary development was examined and post-fertilization kernel-filling characteristics were analysed. Large kernels had a higher rate of kernel filling and contained more endosperm cells and starch granules than normal-sized kernels. Genotypic differences in kernel development appeared before stamen primordia initiation in the developing florets, with sessile spikelets of large-seeded genotypes having larger floret apical meristems than normal-seeded genotypes. At anthesis, the ovaries for large-sized kernels were larger in volume, with more cells per layer and more vascular bundles in the ovary wall. Across experiments and genotypes, there was a significant positive correlation between kernel dry weight at maturity and ovary volume at anthesis. Genotypic effects on meristem size, ovary volume, and kernel weight were all consistent with additive genetic control, suggesting that they were causally related. The pre-fertilization genetic control of kernel weight probably operated through the developing pericarp, which is derived from the ovary wall and potentially constrains kernel expansion.

Maize kernel hardness classification by near infrared (NIR) hyperspectral imaging and multivariate data analysis.

The use of near infrared (NIR) hyperspectral imaging and hyperspectral image analysis for distinguishing between hard, intermediate and soft maize kernels from inbred lines was evaluated. NIR hyperspectral images of two sets (12 and 24 kernels) of whole maize kernels were acquired using a Spectral Dimensions MatrixNIR camera with a spectral range of 960-1662 nm and a sisuChema SWIR (short wave infrared) hyperspectral pushbroom imaging system with a spectral range of 1000-2498 nm. Exploratory principal component analysis (PCA) was used on absorbance images to remove background, bad pixels and shading. On the cleaned images. PCA could be used effectively to find histological classes including glassy (hard) and floury (soft) endosperm. PCA illustrated a distinct difference between glassy and floury endosperm along principal component (PC) three on the MatrixNIR and PC two on the sisuChema with two distinguishable clusters. Subsequently partial least squares discriminant analysis (PLS-DA) was applied to build a classification model. The PLS-DA model from the MatrixNIR image (12 kernels) resulted in root mean square error of prediction (RMSEP) value of 0.18. This was repeated on the MatrixNIR image of the 24 kernels which resulted in RMSEP of 0.18. The sisuChema image yielded RMSEP value of 0.29. The reproducible results obtained with the different data sets indicate that the method proposed in this paper has a real potential for future classification uses.

Timing of infection of macadamia fruit by Pseudocercospora macadamiae and climatic effects on growth and spore germination.

Pseudocercospora macadamiae causes husk spot of macadamia. Husk spot control would be improved by verifying the stages in fruit development susceptible to infection, and determine some of the climatic conditions likely to lead to high disease pressure periods in the field. Our results showed that the percent conidia germination and growth of germ tubes and mycelia of P. macadamiae were greatest at 26 degrees C, with better conidia germination associated with high relative humidity and free water. The exposure of match-head-sized and pea-sized fruit stages to natural P. macadamiae inoculum in the field led to 2 5-fold increases in husk spot incidence, and up to 8.5-fold increases in premature abscission, compared with unexposed fruit. Exposure of fruit stages later than match-head-sized and pea-sized fruit generally caused no further increases in disease incidence or premature abscission. Climatic conditions were found to have a strong influence on the behaviour of P. macadamiae, the host, oil accumulation, and the subsequent impact of husk spot on premature abscission. Our findings suggest that fungicide application should target fruit at the match-head-sized stage of development in order to best reduce yield losses, particularly in seasons where oil accumulation in fruit is prolonged and climatic conditions are optimal for P. macadamiae.

Macadamia Information Kit. Agrilink, your growing guide to better farming guide

ABSTRACT: Each Agrilink kit has been designed to be both comprehensive and practical. As the kits are arranged to answer questions of increasing complexity, they are useful references for both new and experienced producers of specific crops. Agrilink integrates the technology of horticultural production with the management of horticultural enterprises. REPRINT INFORMATION - PLEASE READ! For updated information please call 13 25 23 or visit the website www.deedi.qld.gov.au (Select: Queensland Industries – Agriculture link) This publication has been reprinted as a digital book without any changes to the content published in macadamia grower's handbook. We advise readers to take particular note of the areas most likely to be out-of-date and so requiring further research: see detailed information on first page of the kit. Even with these limitations we believe this information kit provides important and valuable information for intending and existing growers. This publication was last revised in 2004. The information is not current and the accuracy of the information cannot be guaranteed by the State of Queensland. This information has been made available to assist users to identify issues involved in the production of macadamias. This information is not to be used or relied upon by users for any purpose which may expose the user or any other person to loss or damage. Users should conduct their own inquiries and rely on their own independent professional advice. While every care has been taken in preparing this publication, the State of Queensland accepts no responsibility for decisions or actions taken as a result of any data, information, statement or advice, expressed or implied, contained in this publication.

Macadamia Modelling Scoping Study

Investigate the feasibility and utility of a macadamia physiological model.

Better Macadamia crop forecasting

Better Macadamia crop forecasting.

Production of Macadamia Rootstock

Production of Macadamia Rootstock.

Towards the Development of a Functional-Structural model for Macadamia

Towards the Development of a Functional-Structural model for Macadamia.

Better Macadamia Crop Forecasting - Part 2

The continually expanding macadamia industry needs an accurate crop forecasting system to allow it to develop effective crop handling and marketing strategies, particularly when the industry faces recurring cycles of unsustainably high and low commodity prices. This project aims to provide the AMS with a robust, reliable predictive model of national crop volume within 10% of the actual crop by 1 April each year by factoring known seasonal, environmental, cultural, climatic, management and biological constraints, together with the existing AMS database which includes data on tree numbers, tree age, variety, location and previous season's production.

Macadamia Breeding and Conservation

DEEDI is tendering for this project because it considers that macadamia breeding is essential for long-term industry viability and that new productive cultivars will be the basis for the industry to withstand future competition from overseas and from other nut crops.

Improving information for the macadamia industry via an information "bank"

Macadamia growers are under increasing pressure to remain viable in an increasingly competitive global market. A key need is quick access to high quality information. Current industry information is poorly integrated, poorly updated, and because it is largely in hard-copy, is difficult to access efficiently. With the dramatic growth in the use of the internet by growers, as evidenced in a recent industry communications survey, an opportunity exists to address this problem through the development of a high quality, internet-based information “bank”. The bank would bring together the macadamia information resources and collective knowledge of R&D and other relevant agencies into a one-stop information shop, aligned more effectively with grower needs.

Macadamia Regional Variety Trials Series 3 - Phase 2

Regional variety trials (RVT) established in 1983 and again in 1997 identified superior varieties for the macadamia industry. From the 1983 trials, guidelines were developed to assist growers to select the most appropriate new varieties for their particular orchards and many of these superior varieties have been enthusiastically adopted by industry. This is also being done for varieties in the 1997 trials. Many of the best cultivars have already been adopted by growers on the basis of annual reports of yield and quality. Industry development over the next 10 to 20 years will be largely dependent on new, superior varieties selected in these RVT5, including new selections from the macadamia industry breeding program.

Single kernel NIR assessment for QTL identification

Development and evaluation of a single kernel NIR assessment method for improving baley malting quality QTL identification.

Pericarps retained in the tree canopy and stomatal abundance are components of resistance to husk spot caused by Pseudocercospora macadamiae in macadamia

Pseudocercospora macadamiae Beilharz, Mayers and Pascoe infects macadamia fruit via stomata causing husk spot disease. Information on the variability of fruit stomatal abundance, its association with diseased fruit pericarps (sticktights) that are retained in the tree canopy, and its influence on the husk spot intensity (incidence, severity and lesion number) among macadamia genotypes is lacking. We examined a total of 230 macadamia trees comprising 19 cultivars, 56 wild germplasm accessions and 40 breeding progeny, for the prevalence of sticktights and husk spot intensity over three production seasons. We observed a strong association between the prevalence of sticktights and disease intensity indicating its usefulness as a predictor of husk spot and as a useful phenotypic trait for husk spot resistance selection in breeding programmes. Similarly, stomatal abundance varied among macadamia genotypes, and a significant linear relationship (P < 0.001; 93%) was observed between fruit stomatal abundance and husk spot for all the macadamia genotypes analysed, confirming the utility of that trait for disease resistance screening. The genotypes were grouped into disease resistance groups. Correlations between fruit stomatal abundance, disease intensity and prevalence of sticktights revealed that the numbers of sticktights, and relative stomatal abundance were the main factors influencing the intensity of husk spot among macadamia genotypes. This is the first comprehensive study of natural variation of stomatal abundance in Macadamia species that reveals genetic variation, and provides relevant relationships with disease intensity and the prevalence of sticktights. The phenotypic plant traits indentified in this study may serve as selection tools for disease resistance screening in macadamia breeding programmes.