COMM1110 Evidence-Based Problem Solving
Due date: Week 5: 11.59am, Friday 15th March
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You are a consultant at Solution-X, a leading consulting firm well-regarded for its innovative
and comprehensive problem-solving solutions that blend analytical scrutiny, statistical
insights, and ethical considerations.
We’ve partnered with GreenMart, a retail supermarket chain facing a pressing issue: a
notable increase in food waste, especially in the fresh food (Fruit and Vegetable)
section. GreenMart is eager to delve into the root causes of this waste surge and
seeks actionable recommendations to tackle the problem head-on.
GreenMart’s fresh food section, brimming with fruits, veggies, dairy, meat, seafood,
and bakery delights. Yet, a rising trend in food waste threatens to dampen the
excitement. Whether it’s items nearing expiry, facing damage, falling short of quality
standards, or spoiling due to storage mishaps, the waste is both a financial setback
and an environmental headache.
Now, GreenMart isn’t just about profits; they’re deeply committed to operational
efficiency, reducing their environmental footprint, and championing sustainability.
1. Investigate the factors contributing to the rise in food waste in GreenMartÂ’s fresh
food section.
2. Develop and present well-considered and actionable recommendations to
GreenMart to assist them in implementing effective strategies to reduce food
waste.
1
Your Role and Responsibilities
Solution-X has formed a team of consultants and business analysts to provide thorough
analysis and actionable recommendations to GreenMart. At the project’s end, we’ll compile a
comprehensive report. Your role, assigned by the team lead, is crucial to crafting practical
solutions. Let’s get started on making a insightful business analysis report.
Your Tasks:
Assessment 3: Preliminary Analysis Pack (25%):
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Prepare a preliminary business analysis report for an internal meeting on the rise in food
waste at GreenMart’s fresh food section. Use analytical, statistical, and ethical tools to
understand the drivers behind this increase. This analysis will guide discussions and shape
future solutions.
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Focus Areas:
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Analytical Toolbox: Identify potential factors and drivers contributing to the food
waste problem.
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Statistical Toolbox: Examine the data provided by GreenMart to identify food waste
trends and patterns. This analysis will aid in pinpointing the potential causes of the
issues, directing more detailed analysis, and focusing solution development on key
issues to prioritise your problem-solving effort.
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Ethics Toolbox: Identify any ethical dilemmas associated with food waste
• Word limit: 1,500 words (excluding graphs, figures, and reference list). An additional 10% buffer
(1,500 + 150 words) will be applied if you exceed the word count.
• Structure and Format: An introduction or executive summary is NOT required. You should
structure your responses to directly answer each question in the Initial Analysis Pack. Write in a
business report style, utilizing formal language, clear headings, and subheadings to organize your
responses to each question. The clarity, coherence, and organization of your report are crucial,
and each section should be well-integrated to offer comprehensive insights into the addressed
questions.
• Referencing Style: Please use the Harvard referencing style for any sources cited in your report
(see The ‘In-Text’ or Harvard method for more information).
2
Guidelines for your Business Report
Section 1: Scoping the Problem Using the Analytical Toolbox (40%):
This section is approximately 600 words (guide only, not a word limit).
1) Define the Problem: Define the problem concisely to provide clarity on the main issue
requiring resolution for this assignment.
2) Scope the Problem: Utilize the 5Ws framework (What, Where, When, Who, Why) to frame
and scope the problem. For each ‘W’, formulate questions to explore various dimensions
of the problem and identify evidence required to substantiate the answers. Choose only
two ‘Ws’ for your report.
Instruction: Use the table below to organise your questions, evidence, and types of
evidence. You are required to provide at least three points for two ‘W’s (you can choose
any 2 “W” s from the 5 W).
Please integrate the 5W table provided directly into your report and type out your response
as text. All content within the table will count towards the 1,500- word limit, so avoid using
screenshots
2ws
W..
Questions to Explore the Problem Identified Evidence
1.
1.
2.
2.
3.
3.
1.
1.
2.
2.
3.
3.
W..
Type of Evidence
1.
2.
3.
1.
2.
3.
3) Break Down the Problem Using a Logic Tree: Construct a logic tree to systematically
analyse the increase in food waste at GreenMart, dividing the problem into its parts and
sub-parts to pinpoint specific areas of concern and contributing drivers.
Instruction:
a) Include a clearly labelled logic tree in your submission. The tree needs to meet the
Mutually Exclusive, Collectively Exhaustive (MECE) Requirements.
Instructions for creating a clear logic tree using PowerPoint are available on our
course Moodle page (Week 2’s folder). Ensure all details in your logic tree are
clearly visible. Marks may be deducted if your tutor cannot read the details due to
blurriness. Attach your logic tree as an image to your report. The logic tree image
will NOT count towards the 1,500- word limit.
b) Prioritisation: Determine and justify which branches and/or sub-branches should
be prioritized for further analysis. Ensure coherence between the logic tree and
provide explanation to detail your analytical process, providing a clear rationale for
your choices.
3
Section 2: Gaining Insights Using the Statistical Toolbox (40%):
This section is approximately 600 words (guide only, not a word limit).
Context:
After presenting your logic tree and having a detailed discussion with GreenMart, it has
been identified that a substantial portion of the increase in food waste is due to an
abundance of freshly packed fruits and vegetables reaching their expiration dates before
being sold. This insight has refined the focus of your investigation, necessitating a more
targeted analysis to comprehend the waste generated from these specific items.
GreenMart has shared a dataset with you, concentrating on these two food items. A
detailed description of the dataset is provided on page 6.
Order Details: Each record in the Excel dataset represents a single order, comprising 150
pre-packed fruits and vegetable items. The dataset provides insights into the quantities
wasted due to items remaining unsold before their expiration date
GreenMart Food Waste Allowance Target: GreenMartÂ’s food waste allowance percentage for
fruit is capped at 6.67%, implying that in any given order of 150 pre-packed fruit items, a
maximum of 10 items should be wasted due to reaching expiration before being sold. The
waste percentage for vegetable is capped at 12% (a maximum of 18 Items per order).
GreenMart’s Operational Protocols: When orders arrive at the GreenMart retail store, they are
initially placed in the storage area before being stocked on the shelves for sale. Operational
protocols with specific targets for shelving fresh food items are implemented to optimize the
availability of fresh products to customers while minimizing waste due to expiration.
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For fruit: Target is to have the items on the shelf for at least 7 days before the expiry
date, given an expiration date of 12 days post-arrival at the storage area.
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For vegetable: Target is to have the items on the shelf for at least 5 days before the
expiry date, given an expiration date of 8 days post-arrival at the storage area.
Statistical Toolbox Analysis Instructions:
1) Analyse Food Waste:
a) Summary Statistics: Calculate the mean, and standard deviation of food waste
(variable “Quantity_Wasted”) for fruits and vegetables. Then, compare these
results with GreenMartÂ’s food waste allowance target
b) Monthly Analysis: Create pivot tables in Excel to conduct a monthly analysis
of fruits and vegetables waste, using the variable “Order_Arrival_Date” to
determine the order month. Choose an appropriate visual representation you
see fit to showcase this result in your report.
2) Investigate Logistic Issues and Shelf Time
Management at GreenMart suspects that logistic issues may be causing delays in
moving items from storage to the shelves. This delay could reduce the display time of
food items, contributing to increased food waste due to items reaching their expiration
dates before being sold.
4
a) Create a new variable: Create a new column named “Shelf_Duration” to
calculate the shelf time (in days) of each order. This variable represents the
duration each order stays on the shelf before expiration
Shelf_Duration = Expiration_Date_Of_Order – Inventory_Replenishment_Date
b) Summary Statistics and Monthly Analysis: Calculate the summary statistics
of “Shelf_Duration” for fruits and vegetables separately. Then, perform a
monthly analysis and choose a suitable diagram to present it in your report.
3) Analyse Number of Orders, Prices, and Additional Insights
a) Order and Price Analysis: Select suitable statistical analysis tools and
visualizations (diagrams) to examine the trends in the number of orders and
prices for fruits and vegetables over time.
b) Create another new column: Now, you’re required to create a new column in
your Excel file. This column can contain any information you consider relevant,
ensuring that it’s solely based on your existing Excel data. Clearly explain the
rationale behind creating this new column and how it can help you address the
food waste issue. Furthermore, include a screenshot displaying only the first
10-15 rows of this new column. Insert the screenshot into your report
alongside your explanation for this question. The screenshot does not count
towards the word count.
Instruction: Include clear tables or graphs to display the results of each statistical analysis
part (1-3). Ensure they are well-labelled and easy to read. Provide a summary of the main
findings from your analysis above, highlighting key insights obtained. Emphasize their
relevance to helping you solve the food waste issue. (Note: Tables, Diagrams, or Graphs
in this section are NOT in the word count)
Section 3: Ethical Dilemmas with the Ethics Toolbox (20%)
This section is approximately 300 words (guide only, not a word limit).
Select a stakeholder impacted by GreenMart’s food waste issue. Stakeholders may include
GreenMart, residents and consumers, the Local council, or Regulatory Agencies like ACCC,
waste management companies, or product manufacturers.
Consider one ethical dilemma faced by your chosen stakeholder due to the increase in
food waste. Reflect on the various ethical concerns and challenges related to food waste
at GreenMart. Assess the potential harm to individuals or entities, such as the
environment, and elaborate on your reasoning (Please refer to our tutorial materials from
Week 4 for additional details and support).
Instruction: Ensure clarity and conciseness in your explanation, focusing on the ethical
implications and considerations of the identified dilemma within the context of
GreenMart’s food waste issue.
For this section, you are NOT required to apply the full 7-step Ethical Decision-making
Framework; your task is merely to identify one potential ethical dilemma related to the
food waste issue at GreenMart, considering the perspective of your chosen stakeholder.
5
You can access and download your personalised dataset for Assessment 3 through
the COMM1110 R-Shiny website using the following link:
Click this link to download your data – https://comm1110.shinyapps.io/comm1110/
Steps to Download Your Personal Excel Data
1. Open the provided link above and then click the “Project Data” button.
2. Enter your student ID (without the “z”) and click “Load Project Data” to access
your personalized dataset.
3. Once your data loads, download it by clicking “Download Data” (Note: It will be
in CSV format).
4. Open the downloaded CSV file and save it as an “Excel Workbook (.xlsx)” before
conducting any analysis. This ensures that your work can be properly saved.
Important Notes
• The COMM1110 R-Shiny website is only used for downloading data set.
• Each student is provided with a personalized Excel file containing 500 orders.
• Follow the provided steps diligently to download your personalized Excel file.
Then, apply the Excel skills you learnt from tutorials and online weekly Excel
questions to analyze the dataset contained within your downloaded Excel file.
• Numeric Variable Errors: If the R- Shiny App displays errors related to non-numeric
variables, please ignore these error messages. Simply download your Excel data
file.
• If you have any issues with downloading your personal Excel file from the above
link, please contact our Course email at [email protected]
6
Dataset Overview:
Each student will receive a personalised dataset consisting of 500 records, collected over the
span of the 1/01/2023 to 31/12/2023. Each observation in the dataset represents detailed
information about individual food orders at GreenMart.
Variables:
The dataset encompasses 8 variables, each providing different insights into the food waste
issue at GreenMart. Here is a brief overview of each variable included in the dataset:
Variable Name
Description
Example
Values
Order_ID
A unique identifier for each order.
43E4X6VIY
Order_Type
The type of food item in the order.
Fruit or
Vegetable
Price
The Selling Price at which GreenMart sells
the item (Fruit and Vegetable) to their
consumers.
$28.46
Order_Arrival_Date
The date the order arrives at the GreenMart
store (storage area).
*Note: Multiple orders can arrive at the
same date.
2/11/2023
Inventory_Replenishment_Date
The date the order is moved to the shelf for
sale.
4/12/2023
Expiration_Date_Of_Order
The expiration date of the food items in the
order.
11/01/2023
Quantity_Ordered
The total quantity of food items ordered in
each order.
150
Quantity_Wasted
The total quantity of pre-packed food items
wasted in this order due to not being sold
before expiration.
11
PLANNING ASSISTANCE (Use of AI tool such as ChatGPT)
You may use AI software for initial idea generation, but your final submission must be
substantially your own work. Only occasional AI-generated words or phrases are allowed.
Keep copies of initial prompts for verification. Submission of AI- generated content will be
considered academic misconduct and subject to penalties.
Resources:
7
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Get individual feedback on you draft: https://www.student.unsw.edu.au/feedback-hub
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Study support (academic skills, English, etc.): https://www.student.unsw.edu.au/studysupport-and-education-support-advisors
Criteria
3
Fail
Pass
Credit
Distinction
High Distinction
1. Analytical
Problem- Solving
40%
Does not define or scope the
problem accurately. The
logic tree is missing or
inaccurately constructed,
showing a lack of
understanding of the
problem.
Defines and scopes the
problem with minor
errors or omissions.
The logic tree is
present but may lack
full MECE compliance.
Clearly defines and
accurately scopes the
problem using the 5Ws
framework. Constructs a
coherent logic tree that
is largely MECE
compliant.
Clearly defines, accurately
scopes the problem, and
constructs a fully MECE
compliant logic tree.
Provides clear insights
derived from the logic tree.
2. Statistical
Problem- Solving
40%
Does not apply or
inaccurately applies
statistical tools. Visual
representation is unclear or
inappropriate, and insights
are missing or irrelevant.
Applies statistical tools
with minor errors or
omissions. Visual
representation is clear,
but insights may be
superficial.
Accurately applies
statistical tools, uses
appropriate visual
representation, and
generates relevant
insights.
Accurately and insightfully
applies statistical tools,
uses sophisticated visual
representation, and
generates deep, relevant
insights.
3. Ethical Dilemma
Identification
20%
Provides a partial or limited
description of an ethical
dilemma, which may not
constitute a real dilemma or
the links with ethics are
unclear.
Provides an adequate
description of a
generally appropriate
ethical dilemma with
some focus on relevant
details and
stakeholders.
Provides a sound
description of an
appropriate and wellspecified ethical
dilemma with solid
focus on relevant details
and stakeholders.
Provides clear and succinct
descriptions of an
appropriate and wellspecified ethical dilemma
with clear focus on relevant
details and stakeholders.
Defines, scopes the problem
meticulously, and
constructs a sophisticated
logic tree that is fully MECE
compliant. Derives nuanced
insights and prioritises
branches effectively with
sound justification.
Accurately and insightfully
applies statistical tools,
uses innovative visual
representation, and
generates novel, profound
insights, demonstrating a
deep understanding of the
data and its implications.
Provides a clear, succinct,
and compelling description
of a clearly specified and
appropriate ethical dilemma
with a very clear focus on
relevant details,
stakeholders, and the
ethical implications inherent
to the identified dilemma.
Order_ID
Order_Type Price
Order_Arrival_Date
Inventory_Replenishment_Date
Expiration_Date_Of_Order
Quantity_Ordered
4E2UCV1QB fruit
24.24 16/12/2023 20/12/2023 28/12/2023
150
86KQZGGLW vegetable
19.8 25/3/2023 25/3/2023 2/4/2023
150
57T6V3S85 vegetable
17.22 7/5/2023
8/5/2023
15/5/2023
150
QTY8HDM2C fruit
22.67 7/9/2023
15/9/2023 19/9/2023
150
T9SQ7C2I5 fruit
18.41 20/7/2023 31/7/2023 1/8/2023
150
UEX9LVISB vegetable
36.38 1/9/2023
7/9/2023
9/9/2023
150
NDJPZYJ9P vegetable
33.38 22/8/2023 23/8/2023 30/8/2023
150
56Y4G6VP5 fruit
21.9 22/8/2023 2/9/2023
3/9/2023
150
WIBB1U78Z fruit
23.05 29/11/2023 3/12/2023 11/12/2023
150
6QNL0LMAL vegetable
19.88 26/4/2023 30/4/2023 4/5/2023
150
KKOUWHPAL fruit
23.34 14/11/2023 22/11/2023 26/11/2023
150
C4D17BBR0 fruit
15.33 25/7/2023 29/7/2023 6/8/2023
150
KNVS0PX2L fruit
7.53 28/2/2023 11/3/2023 12/3/2023
150
AWR0AHKIW fruit
18.71 10/10/2023 21/10/2023 22/10/2023
150
YISXFI3WA fruit
27.07 12/11/2023 23/11/2023 24/11/2023
150
8A3BTORXC vegetable
28.2 16/7/2023 23/7/2023 24/7/2023
150
SFF9VMX3J fruit
8.32 1/2/2023
7/2/2023
13/2/2023
150
DOJ0EJEJV fruit
10.47 11/3/2023 17/3/2023 23/3/2023
150
8XUVJ7IHA vegetable
36.45 22/11/2023 22/11/2023 30/11/2023
150
GL7PVTXJ4 vegetable
33.63 11/10/2023 15/10/2023 19/10/2023
150
M12VR78Z6 vegetable
15.24 28/1/2023 4/2/2023
5/2/2023
150
HWY9UNXVD fruit
18.34 4/7/2023
13/7/2023 16/7/2023
150
7L3F0SMFA fruit
13.25 18/4/2023 28/4/2023 30/4/2023
150
8FRWMK8J5 vegetable
19.33 31/3/2023 3/4/2023
8/4/2023
150
G90KQVGND vegetable
21.03 13/5/2023 16/5/2023 21/5/2023
150
UEVTLJMOA vegetable
15.26 1/2/2023
6/2/2023
9/2/2023
150
HCUCN9EWY fruit
23.12 24/10/2023 1/11/2023 5/11/2023
150
RI22OMM0U fruit
25.09 10/8/2023 14/8/2023 22/8/2023
150
TYJIWFS58 fruit
13.94 27/2/2023 6/3/2023
11/3/2023
150
QI9GBZQ6C fruit
14.3 9/4/2023
15/4/2023 21/4/2023
150
F3CCPCXSE fruit
13.95 1/6/2023
9/6/2023
13/6/2023
150
Q5CEUBGD1 fruit
21.95 6/11/2023 15/11/2023 18/11/2023
150
KP322RQ31 vegetable
17.14 8/4/2023
9/4/2023
16/4/2023
150
2Q9DWO4JT fruit
19.72 16/7/2023 24/7/2023 28/7/2023
150
9PU0VY2V1 fruit
26.37 6/8/2023
11/8/2023 18/8/2023
150
OXLWJN944 vegetable
35.53 6/11/2023 6/11/2023 14/11/2023
150
CEMR1PL1J fruit
9.47 5/1/2023
12/1/2023 17/1/2023
150
G816ZIS8J vegetable
19.87 15/6/2023 22/6/2023 23/6/2023
150
ETCUDH7XP fruit
13.01 2/1/2023
9/1/2023
14/1/2023
150
V42DQ0TJT vegetable
31.03 19/8/2023 23/8/2023 27/8/2023
150
Q1UDF6PVR fruit
CQVV1RRQT vegetable
5EGYXSR11 vegetable
O7VLGNX1Q vegetable
DZ9WWQIYY vegetable
FI05PZV2I
fruit
J813SR3OV fruit
5BCBU9A5G fruit
EY2VMN529 fruit
IA8QHCO9Z fruit
YGXGZXBH1 vegetable
7UXEHHH5H fruit
M9CDPANGK vegetable
XLQLE34H8 fruit
HIATIUR5I vegetable
HSNS52WTS vegetable
U8DD1VSVL fruit
CFHZROKX5 fruit
789SL8KC5 fruit
40LE6ZO7T fruit
0R30YLPNF vegetable
3GNI8LBDZ vegetable
AYQ3ZFSL2 vegetable
HCFLSFE7C vegetable
HVMPRG84I vegetable
34R66RADL fruit
3X7B0PQAQ vegetable
3GMKUDPCF fruit
2V2G12432 fruit
DKHDVQIF9 fruit
4N2OWRLLK vegetable
LIWIIKVB2 fruit
7EC2IK7D1 fruit
V97KZXAAU fruit
NIE69MJY5 fruit
V4OAOUK85 fruit
Q13NIN29Z vegetable
WHPLDJVMG fruit
PK3U7LQJT fruit
9CGC6C0DG vegetable
HA9Q6E13D vegetable
10.63 13/6/2023
34.69 2/11/2023
13.99 21/3/2023
28.27 25/7/2023
17.05 9/4/2023
23.63 8/12/2023
10.4 22/6/2023
12.78 25/6/2023
13.26 31/3/2023
11.76 3/2/2023
18.26 21/6/2023
11.27 14/3/2023
29.87 21/11/2023
9.3 30/12/2022
17.06 23/3/2023
18.21 8/4/2023
27.3 22/11/2023
10.18 25/1/2023
9.79 19/1/2023
17.8 20/7/2023
22.02 17/6/2023
36.21 7/11/2023
17.85 26/6/2023
15.82 19/4/2023
18.7 13/4/2023
9.76 28/1/2023
36.15 29/11/2023
17.17 29/7/2023
11.62 20/6/2023
21.59 27/8/2023
28.55 15/11/2023
22 27/8/2023
22.1 9/8/2023
13.53 3/2/2023
23.62 19/10/2023
22.58 7/12/2023
31.13 11/12/2023
8.76 17/3/2023
22.14 10/9/2023
17.18 27/3/2023
16.32 21/2/2023
20/6/2023
7/11/2023
28/3/2023
28/7/2023
14/4/2023
14/12/2023
29/6/2023
3/7/2023
8/4/2023
13/2/2023
28/6/2023
23/3/2023
28/11/2023
9/1/2023
27/3/2023
15/4/2023
2/12/2023
30/1/2023
25/1/2023
24/7/2023
23/6/2023
10/11/2023
27/6/2023
26/4/2023
13/4/2023
3/2/2023
3/12/2023
3/8/2023
28/6/2023
2/9/2023
19/11/2023
1/9/2023
15/8/2023
9/2/2023
28/10/2023
17/12/2023
16/12/2023
25/3/2023
18/9/2023
1/4/2023
26/2/2023
25/6/2023
10/11/2023
29/3/2023
2/8/2023
17/4/2023
20/12/2023
4/7/2023
7/7/2023
12/4/2023
15/2/2023
29/6/2023
26/3/2023
29/11/2023
11/1/2023
31/3/2023
16/4/2023
4/12/2023
6/2/2023
31/1/2023
1/8/2023
25/6/2023
15/11/2023
4/7/2023
27/4/2023
21/4/2023
9/2/2023
7/12/2023
10/8/2023
2/7/2023
8/9/2023
23/11/2023
8/9/2023
21/8/2023
15/2/2023
31/10/2023
19/12/2023
19/12/2023
29/3/2023
22/9/2023
4/4/2023
1/3/2023
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
7CJ4OAOBT fruit
DDTBPI9NV fruit
XY90XILKW vegetable
QDC8NLT9A fruit
IW59NNJ7M vegetable
BX1HM7EUWfruit
UX5EAFZIN fruit
KPOUMSDO2 fruit
GX3979U5L fruit
HSSJNK2MD fruit
QQXJSPHU4 fruit
1UOR7TAOY vegetable
9F8B5LI8B fruit
JJW6WHEAX vegetable
7ON0CBJBV fruit
SHVIU69U4 vegetable
NHEQMOG33fruit
F75C633O5 fruit
SP6Z0KI1O fruit
36MV8BJD0 fruit
1YZ8FZ71Z vegetable
N7QBNVJPL vegetable
KQ4B3775C fruit
QZD1XUL2U vegetable
F6A4N9W0S fruit
I7QETJ0U8 fruit
KGFT6N12G fruit
2OA9J3N3Y vegetable
EL25D3JI8 vegetable
8HXQ7WOJC fruit
0W7EIMIKV fruit
RW4662RGF vegetable
EQ9D2CHZV vegetable
RME0X2M0Z vegetable
ZO321YSI7 fruit
M5HDQFSNN vegetable
DIESRB13K fruit
6EODB4QZA fruit
IH40QEVVY fruit
3MY579V32 vegetable
J9WSD7A6H vegetable
21.43 29/8/2023
13.57 31/1/2023
16.43 1/6/2023
21.87 4/8/2023
18.28 30/1/2023
19.34 24/7/2023
26.02 9/9/2023
24.26 20/9/2023
11.53 21/6/2023
10.41 20/2/2023
9.92 4/3/2023
24.59 5/7/2023
11.98 30/4/2023
20.28 20/4/2023
25.65 4/10/2023
19.23 24/5/2023
9.37 19/6/2023
25.18 25/9/2023
24.07 9/12/2023
23.64 16/8/2023
17.17 21/3/2023
20.27 27/6/2023
22.34 15/11/2023
36.33 12/12/2023
12.41 19/3/2023
10.7 3/2/2023
12.51 24/4/2023
29.74 20/11/2023
20.7 25/3/2023
18.74 9/7/2023
11.02 5/5/2023
29.23 30/6/2023
25.6 30/6/2023
19.49 21/4/2023
13.28 23/2/2023
17.5 4/1/2023
13.45 6/5/2023
8 20/2/2023
9.78 2/1/2023
17.72 3/5/2023
13.76 11/3/2023
4/9/2023
6/2/2023
5/6/2023
12/8/2023
2/2/2023
3/8/2023
19/9/2023
26/9/2023
29/6/2023
2/3/2023
14/3/2023
8/7/2023
6/5/2023
23/4/2023
14/10/2023
30/5/2023
27/6/2023
3/10/2023
16/12/2023
24/8/2023
21/3/2023
3/7/2023
25/11/2023
19/12/2023
30/3/2023
10/2/2023
5/5/2023
21/11/2023
30/3/2023
20/7/2023
12/5/2023
30/6/2023
3/7/2023
24/4/2023
4/3/2023
5/1/2023
14/5/2023
2/3/2023
13/1/2023
10/5/2023
11/3/2023
10/9/2023
12/2/2023
9/6/2023
16/8/2023
7/2/2023
5/8/2023
21/9/2023
2/10/2023
3/7/2023
4/3/2023
16/3/2023
13/7/2023
12/5/2023
28/4/2023
16/10/2023
1/6/2023
1/7/2023
7/10/2023
21/12/2023
28/8/2023
29/3/2023
5/7/2023
27/11/2023
20/12/2023
31/3/2023
15/2/2023
6/5/2023
28/11/2023
2/4/2023
21/7/2023
17/5/2023
8/7/2023
8/7/2023
29/4/2023
7/3/2023
12/1/2023
18/5/2023
4/3/2023
14/1/2023
11/5/2023
19/3/2023
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
5ONUCJ6RJ fruit
YX5RUJV99 vegetable
B2JDTKU5P vegetable
ONYAC9YMC fruit
N6P9TS2IA fruit
K37QWD7CJ fruit
JSG7PGCAD vegetable
O54ITSRAL vegetable
57U9RU2BN fruit
85FRYVWOQ vegetable
40CVS84XE fruit
OMO4YES2R fruit
KV438BRPU fruit
F74OQ1BDQ fruit
NN53JIXVS fruit
41U8YMDPH fruit
GYAKYZWCP vegetable
CRSIW0DRF fruit
W5MM3MDO9
vegetable
ZNDLCZJIW fruit
HKKX6QO3D vegetable
00CN77YUG fruit
EIM9KWX0B vegetable
ZYED9E2H5 fruit
2OQJSZQFI vegetable
MPXQ0ZX20 fruit
SHG5Z0SAT fruit
5SUK1FCPB fruit
G3FGGYDJC fruit
EBVL9FOIG fruit
U6AOF8CI4 vegetable
WLHPEAG9Wvegetable
Y1X14T60G vegetable
CTR1Y0CEM vegetable
8L2V63GQO fruit
BTM73PZ52 vegetable
0FH57TBLZ vegetable
5OTX81Q98 fruit
HMDVTCQDK fruit
G6TOLZWO9 fruit
KJFFYN5OU vegetable
13.59 14/6/2023
36.38 10/8/2023
35.2 21/12/2023
9.65 30/5/2023
11.47 7/5/2023
14.55 9/4/2023
33.16 31/8/2023
21.38 13/2/2023
8.44 3/3/2023
33.94 9/10/2023
9.7 31/1/2023
25.4 18/11/2023
10.9 6/3/2023
11.67 23/6/2023
11.94 5/6/2023
27.07 26/10/2023
18.02 1/3/2023
24.51 12/12/2023
17.72 14/6/2023
11.07 18/4/2023
16.74 3/6/2023
10.94 7/2/2023
34.25 14/11/2023
23.87 27/8/2023
32.62 28/12/2022
24.21 24/11/2023
11.14 1/5/2023
23.07 11/9/2023
22.78 3/12/2023
26.62 27/11/2023
27.31 11/8/2023
31.81 25/11/2023
18.31 11/6/2023
19.9 18/6/2023
12.4 10/4/2023
36.39 17/9/2023
35.88 27/11/2023
10.28 19/3/2023
8.27 30/12/2022
11.61 27/5/2023
30.25 29/10/2023
19/6/2023
12/8/2023
21/12/2023
3/6/2023
16/5/2023
17/4/2023
31/8/2023
18/2/2023
14/3/2023
14/10/2023
7/2/2023
28/11/2023
14/3/2023
29/6/2023
10/6/2023
3/11/2023
8/3/2023
21/12/2023
21/6/2023
25/4/2023
7/6/2023
17/2/2023
18/11/2023
1/9/2023
3/1/2023
30/11/2023
7/5/2023
22/9/2023
7/12/2023
6/12/2023
16/8/2023
26/11/2023
16/6/2023
20/6/2023
14/4/2023
22/9/2023
28/11/2023
30/3/2023
4/1/2023
7/6/2023
1/11/2023
26/6/2023
18/8/2023
29/12/2023
11/6/2023
19/5/2023
21/4/2023
8/9/2023
21/2/2023
15/3/2023
17/10/2023
12/2/2023
30/11/2023
18/3/2023
5/7/2023
17/6/2023
7/11/2023
9/3/2023
24/12/2023
22/6/2023
30/4/2023
11/6/2023
19/2/2023
22/11/2023
8/9/2023
5/1/2023
6/12/2023
13/5/2023
23/9/2023
15/12/2023
9/12/2023
19/8/2023
3/12/2023
19/6/2023
26/6/2023
22/4/2023
25/9/2023
5/12/2023
31/3/2023
11/1/2023
8/6/2023
6/11/2023
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
JM7S717KB fruit
74EKS2CER fruit
B18LV4VZD fruit
GT8TYCIY2 vegetable
DM7K6N0SH fruit
HIO8BIJH8 fruit
XXZSBDVVH fruit
88XYESZVN vegetable
4VRR3F72E fruit
PZ4NR48DQ fruit
N716NC4GD fruit
C59SXPQPH fruit
32D9W3EEV fruit
9O553LVW2 vegetable
O00YUSCTW fruit
YEILXX1WM fruit
O6FV8LIY9 fruit
LBBYVJ57P fruit
XZ0363N9X vegetable
W0CSG4P1E fruit
HXW4OFE6G fruit
0LMMVR1D1 fruit
4XFMNATNK vegetable
WX2MIDLJW vegetable
QT2Z3RCJ5 fruit
PJN8LVEF3 vegetable
I04S1RQDL fruit
58Z18HXB7 fruit
89IQII0FD
fruit
54MVIHACN fruit
DVNBXZV3N vegetable
1N3RQB9K0 fruit
7S19CP379 fruit
UBHKKPIM5 vegetable
8YPEFMGKA vegetable
S0Z95W21Z fruit
UV09I7X7A fruit
E7VR94AIB vegetable
5OCCIXHDP fruit
EI344GEEL fruit
N7N54RZCP vegetable
9.93 20/1/2023
11.58 16/4/2023
24.11 21/8/2023
17.21 2/5/2023
25.37 1/11/2023
15.84 20/7/2023
12.07 21/2/2023
36.28 15/11/2023
25.98 3/12/2023
19.97 12/7/2023
26.19 2/12/2023
13.51 8/5/2023
9.66 5/3/2023
16.38 7/5/2023
8.28 10/5/2023
11.72 19/5/2023
21.51 1/9/2023
23.5 17/11/2023
35.23 18/12/2023
13.4 2/5/2023
23.81 20/12/2022
19.47 19/7/2023
35.25 3/10/2023
13.05 20/2/2023
10.33 3/6/2023
26.75 11/7/2023
12.53 12/4/2023
14.71 25/2/2023
9.29 3/1/2023
11.84 2/4/2023
29.92 26/9/2023
12.66 13/4/2023
26.26 7/12/2023
18.45 20/5/2023
31.11 29/9/2023
10.41 12/6/2023
22.57 1/11/2023
33.59 8/8/2023
10.23 19/2/2023
9.82 8/1/2023
30.72 10/11/2023
31/1/2023
25/4/2023
28/8/2023
3/5/2023
8/11/2023
25/7/2023
4/3/2023
20/11/2023
11/12/2023
16/7/2023
8/12/2023
16/5/2023
12/3/2023
10/5/2023
19/5/2023
25/5/2023
8/9/2023
23/11/2023
19/12/2023
7/5/2023
30/12/2022
25/7/2023
3/10/2023
20/2/2023
14/6/2023
13/7/2023
18/4/2023
5/3/2023
7/1/2023
13/4/2023
27/9/2023
21/4/2023
11/12/2023
27/5/2023
30/9/2023
19/6/2023
9/11/2023
9/8/2023
25/2/2023
19/1/2023
10/11/2023
1/2/2023
28/4/2023
2/9/2023
10/5/2023
13/11/2023
1/8/2023
5/3/2023
23/11/2023
15/12/2023
24/7/2023
14/12/2023
20/5/2023
17/3/2023
15/5/2023
22/5/2023
31/5/2023
13/9/2023
29/11/2023
26/12/2023
14/5/2023
1/1/2023
31/7/2023
11/10/2023
28/2/2023
15/6/2023
19/7/2023
24/4/2023
9/3/2023
15/1/2023
14/4/2023
4/10/2023
25/4/2023
19/12/2023
28/5/2023
7/10/2023
24/6/2023
13/11/2023
16/8/2023
3/3/2023
20/1/2023
18/11/2023
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
7842W4G86 fruit
Z3JQG763B fruit
U282XHP8K fruit
1XW3RG6EP vegetable
TU14LN4J7 vegetable
X5LB92YW9 fruit
0AH1RJKOG vegetable
RZD4426TD vegetable
L2TSQF8OH vegetable
4KHAZO9WE fruit
8626DBUPJ fruit
GBKSF3VSK fruit
EBGE2NLWV fruit
LA85V6J2N vegetable
9FYTTGWD5 fruit
M7B6FFIJY fruit
IPTKQSXFI fruit
N6WVVJWA9 fruit
XCKGRA9ZR vegetable
KQABM6BLH vegetable
F2DZ1QWH8 fruit
TBWGY8J2Z vegetable
U5TP6FX69 fruit
7P2DLA9OE fruit
QD3J6JCY3 fruit
FM1NW20S2 vegetable
LCSDA2JJT fruit
NV9XRVBFA fruit
58HBSVRRN fruit
X26SH7KQ4 fruit
YALVHVW64 fruit
VOW7I2SW1 vegetable
MIS1ZK4L2 vegetable
K4H0QQI2B fruit
5G01FJN50 fruit
H9D1RB7EP fruit
391B2FGM3 fruit
OFGO7VSE6 fruit
PRPDFPPVM fruit
TS98D6M01 fruit
2SWYUZV7C vegetable
10.8 23/2/2023
19.13 12/7/2023
11.15 24/2/2023
32.67 28/11/2023
20.5 15/6/2023
18.2 26/10/2023
33.66 6/10/2023
19.26 4/1/2023
36.18 26/12/2022
21.78 23/11/2023
21.23 22/8/2023
22.81 2/12/2023
13.72 13/2/2023
18.34 30/4/2023
21.28 6/11/2023
28.7 2/12/2023
22.62 29/12/2022
13.72 10/2/2023
16.1 12/2/2023
18.36 4/1/2023
11.77 13/2/2023
33.12 31/10/2023
8.59 15/5/2023
26.8 3/12/2023
9.8 8/6/2023
14.47 28/1/2023
29 18/12/2023
24.99 29/11/2023
15.7 21/5/2023
21.05 21/11/2023
11.76 20/4/2023
18.51 4/4/2023
14.63 13/1/2023
24.67 3/12/2023
19.15 24/8/2023
22.5 9/10/2023
12.79 24/5/2023
20.88 19/7/2023
22.39 22/8/2023
11.79 16/3/2023
29.97 11/8/2023
5/3/2023
18/7/2023
2/3/2023
4/12/2023
19/6/2023
30/10/2023
12/10/2023
8/1/2023
2/1/2023
2/12/2023
27/8/2023
6/12/2023
20/2/2023
2/5/2023
11/11/2023
13/12/2023
8/1/2023
14/2/2023
12/2/2023
9/1/2023
19/2/2023
7/11/2023
23/5/2023
7/12/2023
16/6/2023
28/1/2023
26/12/2023
7/12/2023
30/5/2023
30/11/2023
30/4/2023
6/4/2023
14/1/2023
7/12/2023
1/9/2023
18/10/2023
31/5/2023
26/7/2023
1/9/2023
25/3/2023
12/8/2023
7/3/2023
24/7/2023
8/3/2023
6/12/2023
23/6/2023
7/11/2023
14/10/2023
12/1/2023
3/1/2023
5/12/2023
3/9/2023
14/12/2023
25/2/2023
8/5/2023
18/11/2023
14/12/2023
10/1/2023
22/2/2023
20/2/2023
12/1/2023
25/2/2023
8/11/2023
27/5/2023
15/12/2023
20/6/2023
5/2/2023
30/12/2023
11/12/2023
2/6/2023
3/12/2023
2/5/2023
12/4/2023
21/1/2023
15/12/2023
5/9/2023
21/10/2023
5/6/2023
31/7/2023
3/9/2023
28/3/2023
19/8/2023
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
150
SNT65Y5XQ vegetable
678BPTF9O fruit
PEQ9JZCPX vegetable
0JV5BWPJ8 fruit
PBFTEX7OR fruit
TJLDTY60E fruit
ZJO4S7D75 fruit
MXAVCIMO7 fruit
O45BCA09W vegetable
A7AUV5SXS fruit
MFKZPX5BS vegetable
M7SN9A6CN fruit
Q1R5QD6JV vegetable
KAVML469V fruit
69NUK1T9X vegetable
X90Z6O9XV fruit
WALPS2BNS fruit
X2ZICS1F6 vegetable
47A39MNJF fruit
G6Z96BXM7 vegetable
BJNO8KAO9 fruit
L94C3B8EQ vegetable
HA8LK847S fruit
EIRW3JHYC fruit
5Y9L3VFAD fruit
QNSRZKE0H fruit
MJCHY08Z3 fruit
RO2I25FHN fruit
TKJIM5ZJP vegetable
Q8J6EW5QH vegetable
CBEWVRNOZ vegetable
ZTYRS6GGQ fruit
60UO475GU fruit
1CEKHPPQ6 fruit
Q8JHDDMYK fruit
ZJOIMFJ2S fruit
MO7LDXHPX fruit
9DO1AP0OV vegetable
PJACK8618 vegetable
ZILNKOULV fruit
MAX48X01D fruit
29.8 31/8/2023
7.55 26/1/2023
35.31 10/9/2023
20.53 28/7/2023
10.44 25/2/2023
22.62 16/9/2023
21.22 22/7/2023
12.73 24/6/2023
32.72 8/11/2023
23.12 10/10/2023
12.94 14/1/2023
24.47 23/8/2023
34.81 19/12/2023
8.61 14/3/2023
18.58 21/3/2023
20.97 27/9/2023
18.68 11/8/2023
35.13 18/12/2023
9.81 16/3/2023
15.75 1/1/2023
11.67 18/4/2023
16.92 15/1/2023
19.9 23/8/2023
17.5 29/7/2023
13.85 26/5/2023
23.81 14/11/2023
11.34 31/1/2023
12.53 13/5/2023
19.98 3/6/2023
18.21 5/2/2023
16.64 10/2/2023
9.2 4/1/2023
11.72 20/5/2023
9.25 5/1/2023
9.76 16/3/2023
17.13 6/7/2023
24.44 2/10/2023
19.94 29/5/2023
17.07 19/2/2023
22.25 12/8/2023
27.09 23/11/2023
31/8/2023
3/2/2023
15/9/2023
