### Apache Airflow version

2.2.0b1 (beta snapshot)

### Operating System

Mac OSX 11.5.2

### Versions of Apache Airflow Providers

_No response_

### Deployment

Docker-Compose

### Deployment details

_No response_

### What happened

In the tree view, the status color for deferred is very difficult to distinguish from up_for_reschedule and is generally not very distinct. I can’t imagine it’s good for people with colorblindness either.

### What you expected to happen

I expect the status colors to form a distinct palette. While there is already some crowding in the greens, I don't want to see it get worse with the new status.

### How to reproduce

Make a deferred task and view in tree view.

### Anything else

I might suggest something in the purple range like [BlueViolet #8A2BE2](https://www.color-hex.com/color/8a2be2)


### Are you willing to submit PR?

- [X] Yes I am willing to submit a PR!

### Code of Conduct

- [X] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)

airflow/settings.py
"""
    This setting allows altering task instances before they are queued by
    the Airflow scheduler.
    To define task_instance_mutation_hook, add a ``airflow_local_settings`` module
    to your PYTHONPATH that defines this ``task_instance_mutation_hook`` function.
    This could be used, for instance, to modify the task instance during retries.
    :param task_instance: task instance to be mutated
    :type task_instance: airflow.models.taskinstance.TaskInstance
    """
def pod_mutation_hook(pod):
    """
    This setting allows altering ``kubernetes.client.models.V1Pod`` object
    before they are passed to the Kubernetes client by the ``PodLauncher``
    for scheduling.
    To define a pod mutation hook, add a ``airflow_local_settings`` module
    to your PYTHONPATH that defines this ``pod_mutation_hook`` function.
    It receives a ``Pod`` object and can alter it where needed.
    This could be used, for instance, to add sidecar or init containers
    to every worker pod launched by KubernetesExecutor or KubernetesPodOperator.
    """
def configure_vars():