Class 10th Science CBSE Solution
In Text Questions-pg-190- What is meant by the power of accommodation of the eye?
- A person with a myopic eye cannot see objects beyond 1.2m distinctly. What should be the…
- What are the far point and near point of the human eye with normal vision?…
- A student has difficulty in reading the blackboard while sitting in the last row. What…
Exercise-pg-197- The human eye can focus objects at different distances by adjusting the focal length of…
- The human eye forms the image of an object at its:A. cornea B. iris C. pupil D. retina…
- The least distance of distinct vision for a young adult with normal vision is about:A. 25m…
- The change in focal length of an eye-lens is caused by the action of the:A. pupil B.…
- A person needs a lens of power, -5.5 dioptres for correcting his distant vision. For…
- The far point of a myopic person is 80 cm in front of the eye. What is the nature and…
- Make a diagram to show how hypermetropia is corrected.
- The near point of a hypermetropic eye is 1m. What is the nature and power of the lens…
- Why is a normal eye not able to see clearly the objects placed closer than 25 cm?…
- Why does the sky appear dark instead of blue to an astronaut?
- What is meant by the power of accommodation of the eye?
- A person with a myopic eye cannot see objects beyond 1.2m distinctly. What should be the…
- What are the far point and near point of the human eye with normal vision?…
- A student has difficulty in reading the blackboard while sitting in the last row. What…
- The human eye can focus objects at different distances by adjusting the focal length of…
- The human eye forms the image of an object at its:A. cornea B. iris C. pupil D. retina…
- The least distance of distinct vision for a young adult with normal vision is about:A. 25m…
- The change in focal length of an eye-lens is caused by the action of the:A. pupil B.…
- A person needs a lens of power, -5.5 dioptres for correcting his distant vision. For…
- The far point of a myopic person is 80 cm in front of the eye. What is the nature and…
- Make a diagram to show how hypermetropia is corrected.
- The near point of a hypermetropic eye is 1m. What is the nature and power of the lens…
- Why is a normal eye not able to see clearly the objects placed closer than 25 cm?…
- Why does the sky appear dark instead of blue to an astronaut?
In Text Questions-pg-190
Question 1.What is meant by the power of accommodation of the eye?
Answer:The ability of an eye to focus the distant objects as well as the nearby objects and forming the images on the retina by changing the focal length of the eye lens is called accommodation.
Question 2.A person with a myopic eye cannot see objects beyond 1.2m distinctly. What should be the type of the corrective lens used to restore proper vision?
Answer:The person can use concave lens (negative power) to improve the vision.
Question 3.What are the far point and near point of the human eye with normal vision?
Answer:The far point of human eye with normal vision is at infinity and the near point is 25 cm distance from the eye.
Question 4.A student has difficulty in reading the blackboard while sitting in the last row. What could be the defect the child is suffering from? How can it be corrected?
Answer:Since the child cannot see the blackboard writing clearly, he is suffering from 'myopia' or 'short-sightedness' i.e. he can see closer things with naked eye but not distant things. Myopia can be corrected by using spectacles with concave lenses of appropriate power.
What is meant by the power of accommodation of the eye?
Answer:
The ability of an eye to focus the distant objects as well as the nearby objects and forming the images on the retina by changing the focal length of the eye lens is called accommodation.
Question 2.
A person with a myopic eye cannot see objects beyond 1.2m distinctly. What should be the type of the corrective lens used to restore proper vision?
Answer:
The person can use concave lens (negative power) to improve the vision.
Question 3.
What are the far point and near point of the human eye with normal vision?
Answer:
The far point of human eye with normal vision is at infinity and the near point is 25 cm distance from the eye.
Question 4.
A student has difficulty in reading the blackboard while sitting in the last row. What could be the defect the child is suffering from? How can it be corrected?
Answer:
Since the child cannot see the blackboard writing clearly, he is suffering from 'myopia' or 'short-sightedness' i.e. he can see closer things with naked eye but not distant things. Myopia can be corrected by using spectacles with concave lenses of appropriate power.
Exercise-pg-197
Question 1.The human eye can focus objects at different distances by adjusting the focal length of the eye-lens. This is due to:
A. presbyopia
B. accommodation
C. near-sightedness
D. far-sightedness
Answer:Accommodation is the property of human eye to adjust the focal length of our eyes at different distances. Thus, option (b) is correct.
Question 2.The human eye forms the image of an object at its:
A. cornea
B. iris
C. pupil
D. retina
Answer:The image formation spot in our eye is retina. Thus, option (d) is correct.
Question 3.The least distance of distinct vision for a young adult with normal vision is about:
A. 25m
B. 2.5 cm
C. 25 cm
D. 2.5 m
Answer:25 cm is the least distance of distinct vision for a young adult with normal vision.
Question 4.The change in focal length of an eye-lens is caused by the action of the:
A. pupil
B. retina
C. ciliary muscles
D. iris
Answer:ciliary muscles cause the change in focal length in our eyes.
Question 5.A person needs a lens of power, -5.5 dioptres for correcting his distant vision. For correcting his near vision, he needs a lens of power +1.5 dioptres. What is the focal length of the lens required for correcting
(i) distant vision, and
(ii) near vision?
Answer:(i) For distant vision:
Power of lens, P = -5.5 D
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![](data:image/png;base64,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)
Thus, the focal length of the lens required for correcting distant vision is, -18.2 cm.
Note: The negative sign of the length tells us that it is a concave lens.
(ii) For near vision:
Power of lens, P = + 1.5 D
![](data:image/png;base64,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)
![](data:image/png;base64,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)
So, Focal length, f = + 66.66 cm (or + 66.7 cm)
Thus, the focal length of the lens required for correcting near vision is + 66.7 cm.
Note: The positive sign of focal length tells us that it is a convex lens.
Question 6.The far point of a myopic person is 80 cm in front of the eye. What is the nature and power of the lens required to correct the problem?
Answer:The defect called myopia is corrected by using a concave lens. We will now calculate the focal length of the concave lens required in this case. The far point of the myopic person is 80 cm. This means that this person can see the distant object (kept at infinity) clearly if the image of this distant object is formed at his far point.
Object distance, u = ∞ (infinity)
Image distance, v = -80 cm (Far point, in front of lens)
And, Focal length, f=? (To be calculated)
Putting these values in the lens formula:
![](data:image/gif;base64,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)
We get
![](data:image/gif;base64,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)
or ![](data:image/gif;base64,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)
or f = -80 cm
Thus, the focal length of the required concave lens is 80 cm. We will now calculate its power. Please note that the focal length, f= -80 cm = -0.8 m.
![](data:image/gif;base64,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)
![](data:image/gif;base64,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)
So, the power of concave lens required is -1.25D
Question 7.Make a diagram to show how hypermetropia is corrected.
Answer:(a) The hyper-metropic correction is shown below by using convex lens correction.
![](data:image/png;base64,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)
Question 8.The near point of a hypermetropic eye is 1m. What is the nature and power of the lens required to correct this defect? Assume that the near point of the normal eye is 25 cm.
Answer:The eye defect called Hypermetropia is corrected by using convex lens spectacles.
We will first calculate the focal length of the convex lens required in this case. For hypermetropic eye can see the nearby object kept at 25 cm (at the near point if normal eye) clearly if the image of this object is formed at its own near the point which is 1 meter here. So, in this case :
![](data:image/jpeg;base64,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)
Object distance, u = -25 cm (Normal near point)
Image distance, v = -1 m (Near point of this defective eye) = -100 cm
Focal length, f=? (To be calculated)
Putting these values in the lens formula,
![](data:image/png;base64,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)
By putting in values
We get : ![](data:image/png;base64,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)
Or, ![](data:image/png;base64,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)
![](data:image/png;base64,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)
Power of Lens needs to be calculated,
Given by P=![](data:image/png;base64,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)
∴ We convert 33.3 cm into meter i.e 0.33m
P= ![](data:image/png;base64,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)
= +3.0 D
Thus, the power of the convex lens required is +3.0 diopters.
Question 9.Why is a normal eye not able to see clearly the objects placed closer than 25 cm?
Answer:A normal eye sees objects with the help of converging eye lens. The ciliary muscles contact and expand thereby changing the converging power of the lens. The near point of our eyes is 25 cm i.e. our eyes can see clearly with minimum distance of 25 cm. But, when the distance between the object and our eyes is less than 25 cm, the ciliary muscles are unable to focus sharply. Thus, we cannot see with naked eye and need the support of any external device to see the object with distance less than 25 cm
Question 10.Why does the sky appear dark instead of blue to an astronaut?
Answer:The sky appears dark instead of blue to an astronaut because, there is no atmosphere in the outer space so there is no scattering of light. And because there is no scattering of light so no color is scattered. Thus, the sky appears dark to the astronaut.
The human eye can focus objects at different distances by adjusting the focal length of the eye-lens. This is due to:
A. presbyopia
B. accommodation
C. near-sightedness
D. far-sightedness
Answer:
Accommodation is the property of human eye to adjust the focal length of our eyes at different distances. Thus, option (b) is correct.
Question 2.
The human eye forms the image of an object at its:
A. cornea
B. iris
C. pupil
D. retina
Answer:
The image formation spot in our eye is retina. Thus, option (d) is correct.
Question 3.
The least distance of distinct vision for a young adult with normal vision is about:
A. 25m
B. 2.5 cm
C. 25 cm
D. 2.5 m
Answer:
25 cm is the least distance of distinct vision for a young adult with normal vision.
Question 4.
The change in focal length of an eye-lens is caused by the action of the:
A. pupil
B. retina
C. ciliary muscles
D. iris
Answer:
ciliary muscles cause the change in focal length in our eyes.
Question 5.
A person needs a lens of power, -5.5 dioptres for correcting his distant vision. For correcting his near vision, he needs a lens of power +1.5 dioptres. What is the focal length of the lens required for correcting
(i) distant vision, and
(ii) near vision?
Answer:
(i) For distant vision:
Power of lens, P = -5.5 D
Thus, the focal length of the lens required for correcting distant vision is, -18.2 cm.
Note: The negative sign of the length tells us that it is a concave lens.
(ii) For near vision:
Power of lens, P = + 1.5 D
So, Focal length, f = + 66.66 cm (or + 66.7 cm)
Thus, the focal length of the lens required for correcting near vision is + 66.7 cm.
Note: The positive sign of focal length tells us that it is a convex lens.
Question 6.
The far point of a myopic person is 80 cm in front of the eye. What is the nature and power of the lens required to correct the problem?
Answer:
The defect called myopia is corrected by using a concave lens. We will now calculate the focal length of the concave lens required in this case. The far point of the myopic person is 80 cm. This means that this person can see the distant object (kept at infinity) clearly if the image of this distant object is formed at his far point.
Object distance, u = ∞ (infinity)
Image distance, v = -80 cm (Far point, in front of lens)
And, Focal length, f=? (To be calculated)
Putting these values in the lens formula:
We get
or
or f = -80 cm
Thus, the focal length of the required concave lens is 80 cm. We will now calculate its power. Please note that the focal length, f= -80 cm = -0.8 m.
So, the power of concave lens required is -1.25D
Question 7.
Make a diagram to show how hypermetropia is corrected.
Answer:
(a) The hyper-metropic correction is shown below by using convex lens correction.
Question 8.
The near point of a hypermetropic eye is 1m. What is the nature and power of the lens required to correct this defect? Assume that the near point of the normal eye is 25 cm.
Answer:
The eye defect called Hypermetropia is corrected by using convex lens spectacles.
We will first calculate the focal length of the convex lens required in this case. For hypermetropic eye can see the nearby object kept at 25 cm (at the near point if normal eye) clearly if the image of this object is formed at its own near the point which is 1 meter here. So, in this case :
Image distance, v = -1 m (Near point of this defective eye) = -100 cm
Focal length, f=? (To be calculated)Putting these values in the lens formula,
We get :
Or,
Power of Lens needs to be calculated,
Given by P=
∴ We convert 33.3 cm into meter i.e 0.33m
P=
= +3.0 D
Thus, the power of the convex lens required is +3.0 diopters.
Question 9.
Why is a normal eye not able to see clearly the objects placed closer than 25 cm?
Answer:
A normal eye sees objects with the help of converging eye lens. The ciliary muscles contact and expand thereby changing the converging power of the lens. The near point of our eyes is 25 cm i.e. our eyes can see clearly with minimum distance of 25 cm. But, when the distance between the object and our eyes is less than 25 cm, the ciliary muscles are unable to focus sharply. Thus, we cannot see with naked eye and need the support of any external device to see the object with distance less than 25 cm
Question 10.
Why does the sky appear dark instead of blue to an astronaut?
Answer:
The sky appears dark instead of blue to an astronaut because, there is no atmosphere in the outer space so there is no scattering of light. And because there is no scattering of light so no color is scattered. Thus, the sky appears dark to the astronaut.