Justin SextonJames Cook University · College of Science and Engineering
Justin Sexton
Doctor of Philosophy
Currently developing an online web-app for weather and irrigation forecasts for sugarcane growers. (www.opticane.net)
About
31
Publications
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Introduction
Justin Sexton is a research focused, Associate Lecturer at James Cook University. He has recently completed his PhD at JCU in the area of Near Infra-Red Spectroscopy (NIRS). Justin has a background in statistical analysis. His research focus has primarily been within the Australian Sugarcane industry.
Currently Justin is working on the Climate Smart Sugarcane irrigation Partnership (CSSIP). More details are available at https://www.opticane.net/#/about/
Additional affiliations
September 2016 - present
January 2014 - August 2015
July 2010 - December 2013
Education
January 2016 - March 2020
August 2013 - September 2015
February 2006 - October 2010
Publications
Publications (31)
Increasing the precision of nitrogen (N) fertiliser management in cropping systems is integral to increasing the environmental and economic sustainability of cropping. In a simulation study, we found that natural variability in year-to-year climate had a major effect on optimum N fertiliser rates for sugarcane in the Tully region of north-eastern A...
Justin Sexton investigated techniques to identify atypical sugarcane from spectral data. He found that identifying atypical samples could help remove bias in estimates of CCS. His results can be used to track occurrences of atypical cane or improve quality estimates providing benefits at various stages along the industry value chain.
In any given season thousands of tonnes of sugarcane with atypically low quality can pass undocumented through Australian sugarcane mills. Sugarcane with atypically low quality can negatively impact mill processes and throw off grower payment calculations. Mill laboratory operators often observe a small subset (1–5%) of cane consignments that have...
This is the pre-completion seminar for my PhD thesis. The seminar overviews the thesis entirely, with a focus on what I think are the key outcomes.At the moment the video is available on mediasite.
https://mediasite.jcu.edu.au/Mediasite/Play/9f6e96b0950d42bb8e051e78b70f15841d
Many sugarcane mills only test a small subset of cane in the laborator...
On-line near infrared spectroscopic (NIRS) analysis systems play an important role in assessing the quality of sugarcane in Australia. As quality measures are used to calculate the payment made to growers, it is imperative that NIRS models are both accurate and robust. Machine learning and non-linear modelling approaches have been explored as metho...
The Australian sugarcane industry is under pressure to reduce nitrogen (N) fertiliser applications and hence N losses to the environment. One pathway suggested to reduce N applications is to match yield targets in N fertiliser recommendations to the yields achieved by farmers. This seems a sensible strategy: smaller crops generally grown by farmers...
On-line near infrared spectroscopic (NIRS) analysis systems, play an important role in assessing the quality of sugarcane in Australia. As quality measures are used to calculate the payment made to growers, it is imperative that NIRS models are both accurate and robust. Machine learning and non-linear modelling approaches have been explored as meth...
MILL RESEARCHERS HAVE noted that in any given season, 1-5% of samples often have unusually low laboratory estimates of Pol in juice (Pij) given the recorded Brix in juice (Bij) value. These 'atypical' samples are of particular concern as they may represent deteriorated or contaminated cane samples. Deteriorated or contaminated cane has a number of...
A comparison of plsr, svr, ann and gbt methods used to estimate CCS from shredded cane on-line in a sugarcane mill.
NEAR INFRARED (NIR) analysis systems are used to estimate cane quality measures such as brix and pol in juice and apparent purity. Within the Australian sugarcane industry, partial least squares regression (PLSR) has been used to build NIR models of cane quality measures in the lab, on-line and in the field. PLSR relies on the linear relationship b...
IDENTIFYING OPTIMAL NITROGEN application rates that reduce nitrogen loss without adversely reducing yields would benefit growers and the environment. In order to identify optimal nitrogen application rates throughout the Tully mill area, it is important to identify sub-regions that share similar topographical, soil, farm management, productivity or...
Process based agricultural systems models allow researchers to investigate the interactions between variety, environment and management. The ‘Sugar’ module in the Agricultural Productions Systems sIMulator (APSIM-Sugar) currently includes definitions for 14 sugarcane varieties, most of which are no longer commercially grown. This study evaluated th...
Foreknowledge about sugarcane crop size can help industry members make more informed decisions. There exists many different combinations of climate variables, seasonal climate prediction indices, and crop model outputs that could prove useful in explaining sugarcane crop size. A data mining method like random forests can cope with generating a pred...
In order to fully capture the benefits of rising CO2 in adapting agriculture to climate change, we first need to understand how CO2 affects crop growth. Several recent studies reported unexpected increases in sugarcane (C4) yields under elevated CO2, but it is difficult to distinguish direct leaf-level effects of rising CO2 on photosynthesis from i...
Foreknowledge of the size of the crop can help farmers, millers and marketers make better plans. Farmers can use this information to decide how much nitrogen to apply. Millers can better plan mill labour requirements and mill maintenance scheduling activities. Marketers armed with early and reliable information about crop size can better plan the s...
Process‐based agricultural systems models capable of simulating crop growth, management decisions and varietal differences in productivity allow researchers to investigate the interactions between varieties, production environments and management decisions. The Agricultural Production Systems sIMulator (APSIM) currently includes variety parameters...
New sugarcane cultivars are continuously developed to improve sugar industry productivity. Despite this sugarcane crop models such as the ‘Sugar’ module in the Agricultural Productions System sIMulator (APSIM-Sugar) have not been updated to reflect the most recent cultivars. The implications of misrepresenting cultivar parameters in APSIM-Sugar is...
Over the last decade agricultural models have made great strides in simulating not only crop growth but also whole farming systems. One emerging advantage of improved agricultural models is the ability to explore interactions between genotypes, environments and farm management. Calibrating the ‘Sugar’ module in APSIM as new cultivars are developed...
INTERANNUAL CLIMATE VARIABILITY impacts sugarcane yields. Local climate data such as daily rainfall, temperature and radiation were used to describe yields collected from three locations–Victoria sugar mill (1951–1999), Bundaberg averaged across all mills (1951–2010) and Condong sugar mill (1965–2013). Three regression methods, which have their own...
Purpose
– This study aims to investigate the effects of climate change on harvestability for sugarcane-growing regions situated between mountain ranges and the narrow east Australian coastline.
Design/methodology/approach
– Daily rainfall simulations from 11 general circulation models (GCMs) were downscaled for seven Australian sugarcane regions (...
Climate is a key driver of sugarcane production and all its by-products. Consequently, it is impor- tant to understand how climate change will influence sugarcane crop productivity. Ensembles from a crop model and climate projections form part of the dual ensemble methodology to assess climate change impacts on sugarcane productivity for three majo...
UNDERSTANDING THE effect of CO2 concentrations on sugarcane will improve simulations of yield under a changing climate and help develop robust management strategies for the future. To achieve these simulations it is necessary to upgrade crop modelling technology to reflect the latest physiological knowledge. Regional yields for the Burdekin sugarca...
THE POTENTIAL of crop modelling to aid farm management decisions has been demonstrated in the sugar industry. Models such as the Agricultural Production Systems Simulator (APSIM) have been used in scheduling irrigation and fertilisation and for forecasting yields. APSIM models were developed based on cultivar parameters of a limited number of trait...
While several statistical methods are available to analyse model sensitivity, their application to complex process-based models is often impractical due to the large number of simulation runs required. A Bayesian approach to global sensitivity analysis can greatly reduce the number of simulation runs required by building an emulator of the model wh...
Climate is a key driver of sugarcane production and its by-products. Given the significant contribution of sugarcane production to economic growth and development in Australia, it is critical to understand how this production system will be impacted by climate change. This project investigated the impact climate change will have on productivity and...
Faced with the challenges of a changing climate, it is imperative that primary industry decision makers have access to climate projections on a local scale. In the Australian sugar industry, changes in maximum and minimum temperature, radiation and rainfall can significantly affect future economic and environmental sustainability. In northern regio...
Today's scientist is faced with complex problems that require interdisciplinary solutions. Consequently, tertiary science educators have had to develop and deliver interdisciplinary science courses to equip students with the skills required to solve the evolving real-world challenges of today and tomorrow. There are few reported studies of the less...
An excess or deficit in rainfall can affect regional crop productivity and sugar industry operations. This paper investigated the implications of climate change on seasonal rainfall in the Burdekin, Mackay and NSW using a range of downscaled Global Circulation Models (GCMs). Eleven statistically downscaled GCMs were used to produce seasonal rainfal...
Mathematics anxiety is a well recognized and for many students a performance inhibiting impediment. As part of a larger study aimed to guide interventions to improve quantitative skills of science students we investigated students' entry-level maths anxiety, explored its effect on their performance and observed how anxiety and different assessment...
Industries strive to find the balance between increeased productivity and future sustainability of production. To this end, the sucar cane industry maintains recors from each farm about CCS (commercial cane sugar content (%)), total cane yield, cane varieties and growing conditions throughout each region. A challenge that the cane industry faces is...
Questions
Question (1)
I am looking for reference papers that have have identified sub-regional climatic 'zones' that have been used to develop farm management practices. For example in sugarcane a 'wetter' sub-region may need to be harvested before a 'drier' sub-region within a milling region. What I've seen is either very large scale and not really used in decision support (Awan et al. 2015; doi: http://dx.doi.org/10.1002/joc.4066) or precision level and based on soils or other sensors (pedroso et al., 2010; http://dx.doi.org/10.1016/j.compag.2009.10.007).
I'm looking for something in-between, using local, spatial climate variability.
Any advice would be welcome.
Cheers,
Justin
Projects
Projects (3)
To investigate the simulation of sugarcane varieties within ASPIM
This project is a PhD thesis run from James Cook University, Townsville.
The objective of this thesis is to develop statistical data mining methodologies to accurately measure cane attributes for anomalous cases from NIR spectra contained within large NIR databases.
