AGR3RP1 Applied Research Project For Pod Producing Crop
Questions:
2. Apply planning techniques and evidence-based knowledge to develop a research project proposal
3. Apply techniques of project management to maintain documentation
4. Apply project management skills to develop project aims, milestones and manage resources
Answer:
Introduction:
Canola is a pod producing crop of about 3 to 5 feet. The pods contains seeds that are usually harvested and crushed to make canola oil and canola meal. The seeds produced contains approximately 45 percent of oil which is pressed and used as biofuel. The plant produces small flowers that are yellow in colour. Canola production in Australia has continued to increase over years. Canola has a large variety of uses. It is most commonly used to produce Margarine and stock feed. It can also be used in bio-fuels, cosmetics and other various industrial products. Canola was first grown in Australia in 1969 (Colton, 2007). The reason as to why Australian farmers decided to start growing the Canola plant was in an endeavour to reduce overreliance of growing cereal crops. (Colton, 2007).
Arlo variety (B. rapa) and Target variety (Brassica napus) are the two Canola varieties grown in Australia (Colton, 2007). These varieties originated from Canada. Comparing the today’s Canola yield to that of the past, today’s production is far much better. In therms of yield and erucic acid level. In the past, the varieties grown had an erucic acid level of between 20 and 40 percent with today’s variety having only 0.5 percent of the erucic acid (Colton, 2007). In the 1970’s there were studies on the effect that erucic acid had. The research concentrated on the Canola variety grown in the southern stste of Australia (Colton, 2007). The Canola industry was initially wiped off by an outbreak of Blackleg shortly after adoption of Canola cultivation by many farmers. This is because the varieties grown then were not in any way resistant to the disease. (Colton, 2007). In western part of Australia, the disease attack on the Canola crop was the worst leading to great yield loss of up to 80 percent (Colton, 2007).
This brought the realisation of the need to develop canola varieties that were that were well adapted and suitable for their environment. This lead to setting up of a program to breed the Canola plant in the year 1970, first in Victoria then in New South Wales and Western Australia in the year 1973 (Colton, 2007). These breeding centres were developed with the aim of developing highly productive Canola plant with low glucosinolates and erucic acid concentration that were also resistant to the Blackleg disease attack (Colton, 2007). In 1978, the first Canola variety suitable for growth in Australia known as Wesreo was developed by the breeding centre in the Western Australia. In 1979, Wesway variety then came up. The name Canola was a Canadian term but in Australia it is used to refer to the Canola varieties with glucosinolates level below 40Mmoles and less than 2 percent of the erucic acid. By the year 1983, all the three breeding centres in New South Wales, Western Australia and in Victoria had each developed a variety suitable for its own environment. For this reason, the Canola industry begun to recover and had fully re-emerged by the year 1999.
The Canola industry has continued to grow with a notable change after 2016. The production value has changed from $658.6 million in the year 2007 to $1782.4 million in 2015, according to the Australian Bureau of Statistics. The leading state in the Canola production is Western Australia State with its total value being approximately $866.2 million. The second best state in the Canola production is New South Wales with a value of $488.5 million followed by Victoria with a value of $263.6 million. (Australian Bureau of Statistics, 2016).
Literature Review:
Previous Research:
Due to the substantial growth of the industry and the increasing number of varieties grown in the country, more research needs to be done in order to provide growers with useful information that will help them and also benefit other stakeholders. The research would also be very crucial in ensuring that the production per unit area of a given unit area of production has been maximised.
With previous research it was difficult to find resources that explicitly discuss the production of Canola plant. The could be because the Canola plant is used in crop rotation programmes with other crops as a break crop, we only found a few studies showing the effect of different Canola densities to the yield of intercropped wheat crop. The only conspicuous Canola study was on the effect of Canola planting density and harvesting time on the yield of the intercropped wheat. This research was carried out in Canada. The necessity of conducting the study came up after the Canola plant intercropped with wheat developed resistance to pesticides and herbicides. This therefore led to the Canola plant being classified and viewed as a weed.
This research was done thrice in 3 different years within a time period of 5 years. The soil used during the experiment was the black silt loam whose organic level matter was about 10 percent and a 6.0 value of PH. The planting was done on virgin land and fertilizer application was don as informed by the soil tests carried out and the recommendations for growing of wheat. The size of plots used for the experiment were 1.8 by 3 metres with 4 replicates. In every year, there were two experiment carried out with and 23cm intra-row spacing at a depth of 2,5cm of the Park wheat. The planting saw to it that the wheat density per m2 was approximately 220 plants. The Canola plant were then planted between the rows of the wheat at a depth of 1cm on the same day when the wheat was planted apart from the first experiment where the Canola was sworn 3 days prior to the planting of the wheat.
Study Justification:
Doing this research project will help to determine whether or not it is possible to increase the planting density of the Canola crop in a given production area by determining the effects of increasing the Canola crop planting density on the production of the intercropped wheat crop per a given unit area of production. The research will also determine the other necessary requirements for growing on the Canola crop that will ensure maximization of output in a given area of production. It was found that there is a need for this type of study when trying to find other resources relating to it. Only relatively similar studies could be found on canola density, but nothing that was the same as what this research project was trying to find. When reading “The Effect of density and time of removal of volunteer canola on yield loss of wheat” (O’Donovan, 2007). The author found it hard to information on their research. This is because the initial trial had considered the Canola plant as a weed on cereal crop farm.
The results from this research project would also help to give relevant information if it necessitates to provide alternate Canola management practices in order to optimize canola production per given unit area such as increasing the planting rate.
Statement of research questions.
The hypothesis for the project states that; “In a plot that is set up with a larger population of Canola, it would be expected that the yield for each plant will be lower than a plot that is set up with a lower population of plants. The reason for this is because the quantity of available nutrients in the soil will be less for each plant in the denser plot, thus pushing each plant to compete against each other for nutrients.”
Research Questions:
- How will crop density affect the overall yield?
- How will crop density affect the yield for individual plants?
- Will there be a change in pest resistance?
- Will the Plants be healthier/unhealthier if they are sown at a higher rate?
- How will crop density affect the overall yield?
For this question it was estimated that increasing the number of plants would give each plot a higher yield to a point. It seemed logical that planting at a high enough density would be unhealthy for the plants and give them a poor yield because they would all be competing for nutrients in the same space, however this didn’t seem to be the case because the higher density treatments all grew for the most part, better than the lower density treatments.
How will crop density affect the yield for individual wheat crops in any given treatment plot? It was hypothesised that the yield for each individual plant would decrease as the number of Canola plants per plot increases, due to the competition for soil nutrients. When actually comparing the plants, they all appeared to have the same size seed pods and the high density treatments also did not seem in any way deficient of nutrients.
Will there be a change in pest resistance? It was hypothesised for the trial that an increase in the number of Canola plants per treatment per plot would increase the pest resistance capacity of the intercropped wheat, which would be related to a higher number of plants making it difficult for weeds to grow against the Canola. Having a higher density may also help protect the plants closer to the centre of the plot from insects, as it could make them more difficult to reach. It was found that there was almost no insect damage to the entire trial within the duration. Weeds were also mostly not an issue, except in one replicate of the 30 and 90 plant treatment where vetch and rye grass were present.
Will the Plants be healthier/unhealthier if they are sown at a higher rate? The result appeared to be pretty much the same as the first question, in that as the density was increased, the individual health of the plant seemed to be better. This went against the initial assumption for the trial.
Materials and Methods:
Materials:
The materials that were used to undergo this research project included; 650 TT canola seedlings, A Paddock, Tape Measure, Stationary (Pencil, Paper etc.), 48 pegs (12 plots with 4 pegs per plot), Hammer, Camera and an Oven. The Canola variety that was used was 650 TT Canola. It was a suitable choice because it grew well in the Victorian climate and it would be tolerant to Triazine based herbicides.
Methods:
The method that used was to first set up a plot and count the number of plants between the stakes. Based on judgment it was decided which replicate would be used from matching the closest replicate to the number of plants counted and then pulling out as few extras as possible. This method was continued in a straight line with a 1m gap between all the plots until they were all set-up in an almost random order. Each stake was then labelled and 10 plants were measured in each plot. The heights were gathered for each plant and put into an excel spreadsheet that would be updated with data every fortnight. If the plant growth had plateaued data would be recorded once every 4 weeks. 8 measurements had been planned to be completed before the harvest.
Timeline:
To complete the practical component of the research project, the plots were set-up on the 17th of August, with a predicted harvest time of December 11. This date was calculated and organised with the extended assignment submission dates that began on December 20. From the set-up date 10 plants from each plot were measured at random, with the mean for their height calculated in cm. At the end of the practical component, all the data will be compiled and organised into the relevant formats.
Proposed schedule:
Semester 1:
Week 1- Investigate project idea, brief literature search and research hypothesis.
Week 2- Continue and complete the investigation project idea, brief literature search and research hypothesis.
Calculate the budget for the research project.
Week 3-11- Formulate project proposal and plan.
Week 12-13- Organise where the plots need to be placed and gather the materials.
Semester 2:
Week 1-Continue to plan and organise materials
Week 2- Continue to plan and organise materials
Week 3- Continue to plan and organise materials
Week 4- Take test for soil nutrients.
Week 5- Set-up plots and take the first measurement. Also test for soil nutrients.
Week 6- Create excel spreadsheet to display results.
Week 7- Take 2nd plant height measurements.
Week 8- Work on spreadsheet and other data.
Week 9- Take 3rd plant height measurements.
Week 10- Work on spreadsheet and other data.
Week 11- Take 4th plant height measurements.
Week 12- Work on spreadsheet and other data.
October 12th- Take 5th plant height measurements.
October 26th- Take 6th plant height measurements.
November 11th- Take 7th plant height measurements.
November 25th- Take 8th and final plant measurements, and then harvest.
Research Budget:
The buying of the materials used to carry out the research was not done each time the research was being carried out. This is because the material that was obtained during the first time of the research were reused in the subsequent times. The plants for the trial were supplied for free from the Yan Yean farm. 48 stakes for the plots were purchased from a Bunnings warehouse for $85. The cost of travel was to be considered, but didn’t have a significant impact on the budget as the farm was a less than 10km drive.
Total budget is around $100.
Data collection sheets:
Plot Size→ |
30 Plants |
60 Plants |
90 Plants |
120 Plants | ||||||||
Week: ? |
Height |
Height |
Height |
Height | ||||||||
Plant No. 1 | ||||||||||||
Plant No. 2 | ||||||||||||
Plant No. 3 | ||||||||||||
Plant No. 4 | ||||||||||||
Plant No. 5 | ||||||||||||
Plant No. 6 | ||||||||||||
Plant No. 7 | ||||||||||||
Plant No. 8 | ||||||||||||
Plant No. 9 | ||||||||||||
Pant No. 10 | ||||||||||||
Comments: |
Excel spreadsheet for data collation and future data analysis:
The sheet above will be individually recorded in an excel spreadsheet and this final spreadsheet will find the averages across all the measurements. Graphs will also be drawn up from the data collected to get a different representation of the data.
Plot Size→ |
30 Plants |
60 Plants |
90 Plants |
120 Plants | ||||||||
Overall |
Height (Average) |
Standard deviation |
Height (Average) |
Standard deviation |
Height (Average) |
Standard deviation |
Height (Average) |
Standard deviation | ||||
Plant No. 1 | ||||||||||||
Plant No. 2 | ||||||||||||
Plant No. 3 | ||||||||||||
Plant No. 4 | ||||||||||||
Plant No. 5 | ||||||||||||
Plant No. 6 | ||||||||||||
Plant No. 7 | ||||||||||||
Plant No. 8 | ||||||||||||
Plant No. 9 | ||||||||||||
Pant No. 10 |
Results:
When undertaking the practical component of the research project there was a fair amount of difficulty encountered that limited the results that were able to be collected. Despite this there was enough data with the plant height measurements to compile a graph showing a visual representation of how well each treatment performed in the category.
On the graph below, (Fig 2) all of the treatments are lined up for comparison. For this graph the lines are measured by calculating the total average height for each treatment over the course of the trial. It can be seen that the 120 plant treatment (blue line) that has the highest plant density has shown the best results from the trail.
On the last measurement treatment 120’s average height was between 2.5-4.63cm higher than the other treatments, making it the best performer from the trial and giving it an on average height advantage of 2.77%. This was found to be quite a significant difference because it was predicted that the height would level out and perform the worst overall when the plants went into maturity, which was actually the case for treatment 30. Treatment 60 performed the 2nd best, followed by treatment 90. This was a surprise after seeing treatment 120 grow so well, 90 should’ve performed 2nd best. There were also significant differences within the results, with a p-value of <0.0001 being found. Standard deviation between results was also quite significant.
Despite 120 having a clear height advantage, data couldn’t be collected that would display the total and average yield for the trial, which would’ve been the most conclusive data to use. However after observing the plants growing so well out in the paddock it would also seem to that treatment 120 would not only have the largest yield per square metre, but would be very likely to also have the highest yield per individual plant.
Discussion:
When the results were taken, low densities of around 25 Canola plants per square metre were found to have little or no impact on the yield of Wheat. Higher numbers of Canola plants were found to have negative effects on the Wheats yield.
With the constant changing varieties of Canola, more testing on how well it grows at different densities needs to be done. This can be quite difficult because the environmental conditions vary quite a lot across Australia. However, all the other growth parameters may be maintained and all the other factors held constant as much as possible and only varying the Canola plant variety. This will help discover or get the effects of different variety of canola plant on the yield of the intercropped wheat crop. The other factors can be maintained by ensuring that the soil nutrients across all the plots are uniformly distributed, the water distribution across all the plots should also be distributed uniformly and also the height of the Canola plants maintained at a uniform height.
There were a couple of extra factors that should be taken into account with the results of the research project. These factors could have a strong effect on the results that were obtained and may also help to explain the reason for these results.
One factor is the surface area of the leaves. The surface area may affect the rate that moisture evaporates from the soil. For example higher density plots will have a higher surface area of leaves that can block the heat and sunlight from reaching the soil. If the surface area is great enough, this may assist in reducing the amount of moisture that evaporates from the soil, making it easier for the plants growing to obtain water and other nutrients through their root systems. The leaf surface area may also have an effect on the soil management. This is because it reduces the force at which the splash rain water hits the ground thus reducing the effect of loss of soil through slash erosion. This may have given treatments with higher plant densities an advantage over lower density treatments in the trial undertaken for this research project.
Another factor is the available nutrients in the soil. The soil nutrient report for paddock 5 is shown in figure 3 below. Upon examining the nutrient levels in the soil Organic Carbon, Phosphorus, Sulphur, Calcium, Sodium, Aluminium, Boron and Manganese were optimal. The Calcium and Manganese cation levels were also optimal, which helped with the structure of the soil. The soil was found to be acidic, but shouldn’t have had much of a negative impact on plant growth. Zinc and Copper levels were slightly high, but also shouldn’t have had a negative impact on growth.
Though these soil levels were found in the paddock that was being used for the trial, the exact levels of nutrients vary in the soil across different locations of the paddock. For example if the paddock was on a slope than the nutrient levels will change along the gradient. This can also be caused by rainfall moving the available nutrients through the soil.
Annual rainfall around the trial was also obtained from the Bureau of Meteorology. This data is shown in figure 4 below and is from the same year of the trial. When the total annual rainfall for 2017 was compared with the recommend sowing rate/rainfall ration from the Department of Agriculture (Figure 5 below), the recommended sowing rate for the trial was 40-60 plant per square metre. This recommendation was a useful resource to have because it would change the previously recommended sowing rate of 25-30 to 40-60. Despite having a treatment of 60 plants available for measurement, treatment 120 (that was twice the optimal amount found) performed much better than the treatment with 60 plants. Another interesting analysis that was found was the treatment with 60 plants performing slightly better than the treatment with 90 plants. Optimal sowing rate may be the reason that this has occurred.
Month |
Jan |
Feb |
Mar |
Apr |
May |
Jun |
Jul |
Aug |
Sept |
Oct |
Nov |
Dec |
Total Annual Rainfall |
Rainfall (mm) |
18.0 |
44.2 |
90.4 |
93.2 |
21.4 |
16.8 |
33.6 |
61.8 |
40.8 |
28.6 |
20.8 |
92.8 |
562.4mm |
Figure 4; Yan Yean annual rainfall data from 2017 (Bureau of Meteorology, 2018)
Rainfall zone |
Hybrid |
Open pollinated |
Low (250-325mm) |
20-25 |
30-40 |
Medium (325-450mm) |
25-40 |
35-50 |
High (450-550mm) |
30-40 |
40-60 |
Figure 5; Suggested target crop density for canola (plants/m2); use the higher target density to combat weeds (Department of Agriculture and Food, 2016)
Conclusions and Potential Relevance:
With the constant changing varieties of Canola, more testing on how well it grows at different densities needs to be done. This can be quite difficult because the environmental conditions vary quite a lot across Australia. The production of the crop per treatment plot increases with increase in density of the crop up to a given crop density at which the crop yield begin to decrease. The crop yield also changes with change in the soil nutrients in each of the plots. High soil fertility with well-balanced macro and micro nutrients leads to a high crop yield. The height of the Canola plant also has an effect on the crop yield.
The experimental results on the effect of each of the research parameters, that is, crop height, plant density per treatment plot, the surface area of leaves and the soil nutrients are crucial in ensuring high production per plot. This is because after of realization of the required plant requirement, these parameters would be provided in order to maximise the yield per unit area of production. This will ensure increased profits per given area of production. This would also help to streamline the production procedures as one would be sure of what is required to be done in the crop production in order to ensure high crop yields per given area of production. It would also be beneficial in undertaking a research regarding other different factors that affect the crop yield. This will help that crop production will include all the required requirements. Finding information on the plant yield would be the best focus of future trials, and would show the most conclusive data.
Acknowledgments:
Nicola Cooley for supervising and helping arrange the trial location.
Sylvana Iacuone guidance and support.
Melissa Jackson for helping with data collection, and guidance and support.
Yan Yean Farm allowing me to use paddock 5 for the trial.
References:
Australian Bureau of Statistics, 2016, Value of Agricultural Commodities Produced, Australia, 2014-15, viewed 10 May 2017
Bunnings, 2017, Lattice Makers 50 x 25 x 450mm Hardwood Garden Stake - 10 Pack, viewed 10 May 2017
Bureau of Meteorology, 2018, Monthly rainfall (Yan Yean), viewed 23 January 2018
Burrill, P 2012, Better Canola – Module 8: Safe Storage
Canola Council, 2013, Crop Rotation, Canola Council of Canada, Canada, viewed 26 August 2016
Colton, B 2007, Canola in Australia - The First 30 Years, viewed 10 May 2017
Daniel, R 2011, Choosing Rotation Crops - fact sheet, Grains Research & Development Corporation, Australia, viewed 26 August 2016
Department of Agriculture and Food, 2016, Canola Seeding Rate Information, viewed 26 August 2016, <https://www.agric.wa.gov.au/canola/canola-seeding-rate-information>
Farm Trader, 2017, Canola Seed For Sale, viewed 10 May 2017
Holden, S, 2010, Growing Canola, Agriculture Victoria, Melbourne, viewed 26 August 2016
McCaffery, D 2009, Canola - Best Practice Management Guide for South-eastern Australia, Grains Research & Development Corporation, New South Wales, viewed 26 August 2016
-McInnis, A, 2004, The Transformation of Rapeseed Into Canola: A Cinderella Story, PDF, viewed 30 October 2018
Norton, R, Canola in Rotations, Australian Oil Seeds, viewed 26 August 2016
NuSeed, 2017, ATR Bonito – A Top Performer, viewed 10 May 2017
O’Donovan, J 2007, Effect of density and time of removal of volunteer canola (Brassica rapa L.) on yield loss of wheat (Triticum aestivum L.)
Pioneer Canola, 2017, Planning Weed Management in Canola Rotations
Statistics Canada, 2009, Canola: a Canadian success story
Buy AGR3RP1 Applied Research Project For Pod Producing Crop Answers Online
Talk to our expert to get the help with AGR3RP1 Applied Research Project For Pod Producing Crop Answers to complete your assessment on time and boost your grades now
The main aim/motive of the management assignment help services is to get connect with a greater number of students, and effectively help, and support them in getting completing their assignments the students also get find this a wonderful opportunity where they could effectively learn more about their topics, as the experts also have the best team members with them in which all the members effectively support each other to get complete their diploma assignments. They complete the assessments of the students in an appropriate manner and deliver them back to the students before the due date of the assignment so that the students could timely submit this, and can score higher marks. The experts of the assignment help services at urgenthomework.com are so much skilled, capable, talented, and experienced in their field of programming homework help writing assignments, so, for this, they can effectively write the best economics assignment help services.