National Test Programme - testing actions for sustainable farming phase one: survey report

2. Survey Answer Analysis

2.1 Survey Analysis - Overview

All figures below are a combination farmers and crofters who have completed the survey. A total of 803 farmers and 174 crofters completed the survey, which included 106 reactive volunteers. 125 respondents are Women in Agriculture and 84 participants identified as a Young Farmer (<41 years in age).

Not all questions were answered by each participant as the survey was designed to allow livestock and mixed enterprises to answer all sections whilst businesses which are solely arable answered the carbon audit, soil analysis, nutrient management, manure analysis and biodiversity sections. This means when analysing the answers of the survey we must take into account that each question will not have 977 respondents. As the business type was one of the stratification methods in which the target for the survey was based, the enterprise types provided by the respondents was cross checked with the Agricultural Census 2021 data to ensure the information supplied correlated with the Census. As part of the survey, respondents were allowed to pick as many enterprise types as they deemed fit to describe their business. The census data categorised each business by its predominant enterprise type (more than two thirds of the business).

Figure 6 shows the percentage of respondents undertaking actions covered in the survey i.e. specific audits, analysis or plans (Table 6 highlights the raw data of survey responses).

Table 6: Total responses for each action covered in the survey.

Action Type	Yes	No	Total
Carbon Audit	372	451 *154 respondents intend to undertake a Carbon Audit in 2022 but have not yet done so at the time of completing the survey.	977
Soil Testing	713	264	977
Nutrient Management Plan	365	612	977
Manure Analysis	110	867	977
Forage Analysis	445	459	904
Feed Ration Plan	492	411	903
Animal Health and Welfare Plan	716	186	902
Breeding Plan	435	464	899
Biodiversity Audit	278	699	977

Figure 7 presents the geographic spread of survey respondents across Scotland. Each business type is represented by a different coloured shape. Cereal and Mixed farms which took part in the survey are found mostly in the eastern area of Scotland whilst Specialist Sheep and Specialist Cattle businesses are located across Scotland, though they are characteristic of the Highland & Islands. As part of the stratification methodology, Scotland was divided into five NUTS2 regions. Table 7 and Table 8 break down the total number of respondents by NUTS2 region against business type and SLR banding.

Table 7: Total number of respondents by region and business type. The total response rate (denominator) for each business type can be seen in blue under the business type title in brackets.

Business Type	Eastern Scotland	Highlands & Islands	North East Scotland	South Scotland	West Central Scotland
Cereal (51)	26	4	11	9	1
	51.0%	7.8%	21.6%	17.6%	2.0%
Dairy (43)	3	7	0	30	3
	7.0%	16.3%	0%	69.8%	7.0%
General Cropping (81)	49	10	13	8	1
	60.5%	12.3%	16.0%	9.9%	1.2%
General Cropping - Forage (39)	4	15	7	13	0
	10.3%	38.5%	17.9%	33.3%	0.0%
Lowland Cattle & Sheep (58)	17	8	15	18	0
	29.3%	13.8%	25.9%	31.0%	0.0%
Mixed (115)	36	27	33	19	0
	23.2%	17.4%	21.3%	12.3%	0.0%
Other Cattle & Sheep (LFA) (95)	17	38	4	34	2
	17.9%	40.0%	4.2%	35.8%	2.1%
Specialist Cattle (LFA) (255)	18	109	24	96	8
	7.1%	42.7%	9.4%	37.6%	3.1%
Specialist horticulture & permanent crops (8)	3	4	1	0	0
	37.5%	50.0%	12.5%	0.0%	0.0%
Specialist Pigs (3)	0	0	1	2	0
	0.0%	0.0%	33.3%	66.7%	0.0%
Specialist Poultry (2)	0	1	0	1	0
	0.0%	50.0%	0.0%	50.0%	0.0%
Specialist Sheep (LFA) (210)	20	126	10	50	4
	9.5%	60.0%	4.8%	23.8%	1.9%
Unknown Business Type (17)	0	10	3	3	1
	0.0%	58.8%	17.6%	17.6%	5.9%
Total (977)[12]	193	359	122	283	19
	19.8%	36.7%	12.5%	29.0%	1.9%

Table 8: Total number of respondents by region and SLR band. The total response rate (denominator) for each SLR band can be seen in blue under the SLR band in brackets.

SLR Band	Eastern Scotland	Highlands & Islands	North East Scotland	South Scotland	West Central Scotland
0 - <0.25 FTE (Extremely Small) (174)	11	107	19	36	1
	6.3%	61.5%	10.9%	20.7%	0.6%
0.25 - <1 FTE (Very Small) (155)	21	73	29	26	6
	13.5%	47.1%	18.7%	16.8%	3.9%
1 - <2 FTE (Small) (130)	31	51	12	33	3
	23.8%	39.2%	9.2%	25.4%	2.3%
2 - <3 FTE (Medium) (99)	19	31	16	29	4
	19.2%	31.3%	16.2%	29.3%	4.0%
3 - <5 FTE (Large) (155)	38	41	17	58	1
	24.5%	26.5%	11.0%	37.4%	0.6%
5 or more FTE (Very Large) (251)	73	48	26	100	4
	29.1%	19.1%	10.4%	39.8%	1.6%
Unknown SLR (13)[13]	0	8	3	1	0
	0.0%	61.5%	23.1%	7.7%	0.0%
Total (977) 13	193	359	122	283	19
	19.8%	36.7%	12.5%	29.0%	1.9%

Figure 8 and Figure 9 identify the different business types across Scotland that conduct management actions outlined in this survey. The total response rate (denominator) for each business type can be seen in brackets under each of the business type titles along the vertical axis (Table 9 highlights the raw data of survey responses).

Soil Testing and Animal Health and Welfare Plans appear to be the most common practices across all enterprise types. Manure Analysis is the least common practice across all enterprise types. Specialised business types appear to undertake less management actions in comparison to businesses that focus on dairy or mixed enterprises.

Table 9: Total number of the different business types that undertake management actions outlined in the survey. The total response rate (denominator) for each business type can be seen in blue under the business type title in brackets.

Business Type	Carbon Audit	Soil Testing	Nutrient Management Plan	Manure Analysis	Forage Analysis	Feed Ration Plan	Animal Health & Welfare Plan	Breeding Plan	Biodiversity Audit
Cereal (51)	19	48	33	10	9	10	17	6	16
	37.3%	94.1%	64.7%	19.6%	17.6%	19.6%	33.3%	11.8%	31.4%
Dairy (43)	31	38	30	13	42	38	40	34	10
	72.1%	88.4%	69.8%	30.2%	97.7%	88.4%	93.0%	79.1%	23.3%
General Cropping (81)	26	79	57	13	12	17	26	12	27
	32.1%	97.5%	70.4%	16.0%	14.8%	21.0%	32.1%	14.8%	33.3%
General Cropping - Forage (39)	5	17	8	1	2	2	8	4	10
	12.8%	43.6%	20.5%	2.6%	5.1%	5.1%	20.5%	10.3%	25.6%
Lowland Cattle & Sheep (58)	17	45	19	5	29	31	51	33	10
	29.3%	77.6%	32.8%	8.6%	50.0%	53.4%	87.9%	56.9%	17.2%
Mixed (115)	64	98	66	19	79	81	100	61	45
	55.7%	85.2%	57.4%	16.5%	68.7%	70.4%	87.0%	53.0%	39.1%
Other Cattle & Sheep (LFA) (95)	45	69	27	6	52	52	88	47	38
	47.4%	72.6%	28.4%	6.3%	54.7%	54.7%	92.6%	49.5%	40.0%
Specialist Cattle (LFA) (255)	128	204	99	29	183	172	233	137	63
	50.2%	80.0%	38.8%	11.4%	71.8%	67.5%	91.4%	53.7%	24.7%
Specialist horticulture & permanent crops (8)	0	5	2	0	0	0	2	2	1
	0.0%	62.5%	25.0%	0.0%	0.0%	0.0%	25.0%	25.0%	12.5%
Specialist Pigs (3)	1	3	2	3	1	3	3	2	0
	33.3%	100.0%	66.7%	100.0%	33.3%	100.0%	100.0%	66.7%	0.0%
Specialist Poultry (2)	1	1	1	1	0	1	1	0	2
	50.0%	50.0%	50.0%	50.0%	0.0%	50.0%	50.0%	0.0%	100.0%
Specialist Sheep (LFA) (210)	33	100	19	9	35	82	140	94	55
	15.7%	47.6%	9.0%	4.3%	16.7%	39.0%	66.7%	44.8%	26.2%
Unknown Business Type (17)	2	6	2	1	1	3	7	3	1
	11.8%	35.3%	11.8%	5.9%	5.9%	17.6%	41.2%	17.6%	5.9%
Total (977)	372	713	365	110	445	492	716	435	278
	38.1%	73.0%	37.4%	11.3%	45.5%	50.4%	73.3%	44.5%	28.5%

Figure 10 below identifies the percentage of businesses with a small to large Standard Labour Requirement (SLR) banding that conduct the various management actions outlined in the survey. The total response rate (denominator) for each SLR banding can be seen in brackets under each of the SLR band titles along the vertical axis (Table 10 highlights the raw data of survey responses).

Soil Testing and Animal Health and Welfare Plans appear to be the most common practices across all SLR bands. Manure Analysis is the least common practice across all SLR bands. There is a trend between management actions taken and the size of the business. The smaller the enterprise as measured by labour input the less likely the business is to undertake management actions, the bigger the enterprise as measured by labour input the more likely the business is to undertake management actions. Although undertaking a Biodiversity Audit appears to be of equal importance no matter the size of the business.

Table 10: The SLR bandings of the businesses that undertake management actions outlined in the survey. The total response rate (denominator) for each businesses SLR banding can be seen in blue under the business type title in brackets.

SLR Band	Carbon Audit	Soil Testing	Nutrient Management Plan	Manure Analysis	Forage Analysis	Feed Ration Plan	Animal Health & Welfare Plan	Breeding Plan	Biodiversity Audit
0 - <0.25 FTE (Extremely Small) (174)	9	37	12	3	11	29	50	36	26
	8.6%	35.2%	11.4%	2.9%	10.5%	27.6%	47.6%	34.3%	24.8%
0.25 - <1 FTE (Very Small) (155)	54	120	56	20	61	82	129	77	51
	29.2%	64.9%	30.3%	10.8%	33.0%	44.3%	69.7%	41.6%	27.6%
1 - <2 FTE (Small) (130)	36	95	36	7	47	56	98	54	41
	27.5%	72.5%	27.5%	5.3%	35.9%	42.7%	74.8%	41.2%	31.3%
2 - <3 FTE (Medium) (99)	47	84	48	13	52	61	85	46	25
	44.8%	80.0%	45.7%	12.4%	49.5%	58.1%	81.0%	43.8%	23.8%
3 - <5 FTE (Large) (155)	82	157	77	22	113	106	138	86	58
	45.3%	86.7%	42.5%	12.2%	62.4%	58.6%	76.2%	47.5%	32.0%
5 or more FTE (Very Large) (251)	141	213	133	44	159	152	208	131	77
	54.9%	82.9%	51.8%	17.1%	61.9%	59.1%	80.9%	51.0%	30.0%
Unknown SLR (13)	3	7	3	1	2	6	8	5	0
	23.1%	53.8%	23.1%	7.7%	15.4%	46.2%	61.5%	38.5%	0.0%
Total (977)	372	713	365	110	445	492	716	435	278
	38.1%	73.0%	37.4%	11.3%	45.5%	50.4%	73.3%	44.5%	28.5%

Each bar in Figure 11 below shows the estimated percentage share by farm size of all carbon audits undertaken by a given farm type. The total number of carbon audits (denominator) for each farm type is shown in brackets along the vertical axis. For example, of the 19 reported carbon audits undertaken by cereal farms, 26% were undertaken by very large cereal farms. This does not, however, necessarily imply that 26% of very large cereal farms undertake carbon audits. Table 11 shows the supporting data values.

Table 11: The business types and SLR bandings of respondents who have undertaken a carbon audit. The total response rate (denominator) for each businesses type can be seen in blue under the business type title in brackets.

Business Type	0 - <0.25 FTE (Extremely Small)	0.25 - <1 FTE (Very Small)	1 - <2 FTE (Small)	2 - <3 FTE (Medium)	3 - <5 FTE (Large)	5 or more FTE (Very Large)	Unknown SLR
Cereal (19)	0	2	5	4	3	5	0
	0.0%	10.5%	26.3%	21.1%	15.8%	26.3%	0.0%
Dairy (31)	0	1	2	1	3	24	0
	0.0%	3.2%	6.5%	3.2%	9.7%	77.4%	0.0%
General Cropping (26)	0	1	3	3	10	9	0
	0.0%	3.8%	11.5%	11.5%	38.5%	34.6%	0.0%
General Cropping - Forage (5)	3	1	0	1	0	0	0
	60.0%	20.0%	0.0%	20.0%	0.0%	0.0%	0.0%
Lowland Cattle & Sheep (17)	0	2	3	4	2	6	0
	0.0%	11.8%	17.6%	23.5%	11.8%	35.3%	0.0%
Mixed (64)	0	4	4	11	17	28	0
	0.0%	6.3%	6.3%	17.2%	26.6%	43.8%	0.0%
Other Cattle & Sheep (LFA) (45)	0	0	5	6	16	18	0
	0.0%	0.0%	11.1%	13.3%	35.6%	40.0%	0.0%
Specialist Cattle (LFA) (128)	4	15	13	20	31	45	0
	3.0%	12.9%	11.9%	15.8%	19.8%	36.6%	0.0%
Specialist horticulture & permanent crops (0)	0	0	0	0	0	0	0
	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%
Specialist Pigs (1)	0	0	0	0	0	1	0
	0.0%	0.0%	0.0%	0.0%	0.0%	100.0%	0.0%
Specialist Poultry (1)	0	0	0	0	0	1	0
	0.0%	0.0%	0.0%	0.0%	0.0%	100.0%	0.0%
Specialist Sheep (LFA) (33)	1	8	6	1	4	13	0
	3.0%	24.2%	18.2%	3.0%	12.1%	39.4%	0.0%
Unknown Business Type (2)	0	0	0	0	0	0	2
	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%	100.0%
Total (372)	8	34	41	51	86	150	2
	2.2%	9.1%	11.0%	13.7%	23.1%	40.3%	0.5%

Each bar in Figure 12 below shows the estimated percentage share by farm size of all soil testing analysis undertaken by a given farm type. The total number of soil testing analyses (denominator) for each farm type is shown in brackets along the vertical axis. For example, of the 48 reported soil testing analyses undertaken by cereal farms, 17% were undertaken by very large cereal farms. This does not, however, necessarily imply that 17% of very large cereal farms undertake soil testing. Table 12 shows the supporting data values.

Table 12: The business types and SLR bandings of respondents who have undertaken soil testing. The total response rate (denominator) for each businesses type can be seen in blue under the business type title in brackets.

Business Type	0 - <0.25 FTE (Extremely Small)	0.25 - <1 FTE (Very Small)	1 - <2 FTE (Small)	2 - <3 FTE (Medium)	3 - <5 FTE (Large)	5 or more FTE (Very Large)	Unknown SLR
Cereal (48)	6	9	11	10	4	8	0
	12.5%	18.8%	22.9%	20.8%	8.3%	16.7%	0.0%
Dairy (38)	1	1	4	2	5	25	0
	2.6%	2.6%	10.5%	5.3%	13.2%	65.8%	0.0%
General Cropping (79)	0	8	14	8	21	28	0
	0.0%	10.1%	17.7%	10.1%	26.6%	35.4%	0.0%
General Cropping - Forage (17)	13	1	1	1	1	0	0
	76.5%	5.9%	5.9%	5.9%	5.9%	0.0%	0.0%
Lowland Cattle & Sheep (45)	4	11	10	8	6	6	0
	8.9%	24.4%	22.2%	17.8%	13.3%	13.3%	0.0%
Mixed (98)	0	8	12	13	25	40	0
	0.0%	8.2%	12.2%	13.3%	25.5%	40.8%	0.0%
Other Cattle & Sheep (LFA) (69)	1	4	6	9	20	29	0
	1.4%	5.8%	8.7%	13.0%	29.0%	42.0%	0.0%
Specialist Cattle (LFA) (204)	6	31	22	29	52	64	0
	2.9%	15.2%	10.8%	14.2%	25.5%	31.4%	0.0%
Specialist horticulture & permanent crops (5)	0	0	0	1	1	3	0
	0.0%	0.0%	0.0%	20.0%	20.0%	60.0%	0.0%
Specialist Pigs (3)	0	0	1	0	0	2	0
	0.0%	0.0%	33.3%	0.0%	0.0%	66.7%	0.0%
Specialist Poultry (1)	0	0	0	0	0	1	0
	0.0%	0.0%	0.0%	0.0%	0.0%	100.0%	0.0%
Specialist Sheep (LFA) (100)	24	26	15	5	7	23	0
	24.0%	26.0%	15.0%	5.0%	7.0%	23.0%	0.0%
Unknown Business Type (6)	0	0	0	0	0	0	6
	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%	100.0%
Total (713)	55	99	96	86	142	229	6
	7.7%	13.9%	13.5%	12.1%	19.9%	32.1%	0.8%

Each bar in Figure 13 below shows the estimated percentage share by farm size of all nutrient management plans undertaken by a given farm type. The total number of nutrient management plans (denominator) for each farm type is shown in brackets along the vertical axis. For example, of the 33 reported nutrient management plans undertaken by cereal farms, 21% were undertaken by very large cereal farms. This does not, however, necessarily imply that 21% of very large cereal farms undertake nutrient management plans. Table 13 shows the supporting data values.

Table 13: The business types and SLR bandings of respondents who have undertaken a nutrient management plan. The total response rate (denominator) for each businesses type can be seen in blue under the business type title in brackets.

Business Type	0 - <0.25 FTE (Extremely Small)	0.25 - <1 FTE (Very Small)	1 - <2 FTE (Small)	2 - <3 FTE (Medium)	3 - <5 FTE (Large)	5 or more FTE (Very Large)	Unknown SLR
Cereal (33)	2	8	6	6	4	7	0
	6.1%	24.2%	18.2%	18.2%	12.1%	21.2%	0.0%
Dairy (30)	0	0	4	2	3	21	0
	0.0%	0.0%	13.3%	6.7%	10.0%	70.0%	0.0%
General Cropping (57)	0	5	8	6	14	24	0
	0.0%	8.8%	14.0%	10.5%	24.6%	42.1%	0.0%
General Cropping - Forage (8)	6	0	1	1	0	0	0
	75.0%	0.0%	12.5%	12.5%	0.0%	0.0%	0.0%
Lowland Cattle & Sheep (19)	1	6	3	3	4	2	0
	5.3%	31.6%	15.8%	15.8%	21.1%	10.5%	0.0%
Mixed (66)	1	5	6	8	17	29	0
	1.5%	7.6%	9.1%	12.1%	25.8%	43.9%	0.0%
Other Cattle & Sheep (LFA) (27)	0	1	4	3	8	11	0
	0.0%	3.7%	14.8%	11.1%	29.6%	40.7%	0.0%
Specialist Cattle (LFA) (99)	1	16	10	19	19	34	0
	1.0%	16.2%	10.1%	19.2%	19.2%	34.3%	0.0%
Specialist horticulture & permanent crops (2)	0	0	0	0	0	2	0
	0.0%	0.0%	0.0%	0.0%	0.0%	100.0%	0.0%
Specialist Pigs (2)	0	0	1	0	0	1	0
	0.0%	0.0%	50.0%	0.0%	0.0%	50.0%	0.0%
Specialist Poultry (1)	0	0	0	0	0	1	0
	0.0%	0.0%	0.0%	0.0%	0.0%	100.0%	0.0%
Specialist Sheep (LFA) (19)	2	5	0	2	3	7	0
	10.5%	26.3%	0.0%	10.5%	15.8%	36.8%	0.0%
Unknown Business Type (2)	0	0	0	0	0	0	2
	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%	100.0%
Total (365)	13	46	43	50	72	139	2
	3.6%	12.6%	11.8%	13.7%	19.7%	38.1%	0.5%

Each bar in Figure 14 below shows the estimated percentage share by farm size of all manure analysis undertaken by a given farm type. The total number of manure analyses (denominator) for each farm type is shown in brackets along the vertical axis. For example, of the 10 reported manure analyses undertaken by cereal farms, 20% were undertaken by very large cereal farms. This does not, however, necessarily imply that 20% of very large cereal farms undertake manure analysis. Table 14 shows the supporting data values.

Table 14: The business types and SLR bandings of respondents who have undertaken manure analysis. The total response rate (denominator) for each businesses type can be seen in blue under the business type title in brackets.

Business Type	0 - <0.25 FTE (Extremely Small)	0.25 - <1 FTE (Very Small)	1 - <2 FTE (Small)	2 - <3 FTE (Medium)	3 - <5 FTE (Large)	5 or more FTE (Very Large)	Unknown SLR
Cereal (10)	0	2	2	2	2	2	0
	0.0%	20.0%	20.0%	20.0%	20.0%	20.0%	0.0%
Dairy (13)	0	0	2	1	1	9	0
	0.0%	0.0%	15.4%	7.7%	7.7%	69.2%	0.0%
General Cropping (13)	0	2	3	1	2	5	0
	0.0%	15.4%	23.1%	7.7%	15.4%	38.5%	0.0%
General Cropping - Forage (1)	0	0	0	1	0	0	0
	0.0%	0.0%	0.0%	100.0%	0.0%	0.0%	0.0%
Lowland Cattle & Sheep (5)	0	0	2	2	1	0	0
	0.0%	0.0%	40.0%	40.0%	20.0%	0.0%	0.0%
Mixed (19)	0	1	0	2	2	14	0
	0.0%	5.3%	0.0%	10.5%	10.5%	73.7%	0.0%
Other Cattle & Sheep (LFA) (6)	0	0	0	1	1	4	0
	0.0%	0.0%	0.0%	16.7%	16.7%	66.7%	0.0%
Specialist Cattle (LFA) (29)	2	2	2	5	9	9	0
	6.9%	6.9%	6.9%	17.2%	31.0%	31.0%	0.0%
Specialist horticulture & permanent crops (0)	0	0	0	0	0	0	0
	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%
Specialist Pigs (3)	0	0	1	0	0	2	0
	0.0%	0.0%	33.3%	0.0%	0.0%	66.7%	0.0%
Specialist Poultry (1)	0	0	0	0	0	1	0
	0.0%	0.0%	0.0%	0.0%	0.0%	100.0%	0.0%
Specialist Sheep (LFA) (9)	2	3	1	1	1	1	0
	22.2%	33.3%	11.1%	11.1%	11.1%	11.1%	0.0%
Unknown Business Type (1)	0	0	0	0	0	0	1
	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%	100.0%
Total (110)	4	10	13	16	19	47	1
	3.6%	9.1%	11.8%	14.5%	17.3%	42.7%	0.9%

Each bar in Figure 15 below shows the estimated percentage share by farm size of all forage analysis undertaken by a given farm type. The total number of forage analyses (denominator) for each farm type is shown in brackets along the vertical axis. For example, of the 9 reported forage analyses undertaken by cereal farms, 11% were undertaken by very large cereal farms. This does not, however, necessarily imply that 11% of very large cereal farms undertake forage analysis. Table 15 shows the supporting data values.

Table 15: The business types and SLR bandings of respondents who have undertaken forage analysis. The total response rate (denominator) for each businesses type can be seen in blue under the business type title in brackets.

Business Type	0 - <0.25 FTE (Extremely Small)	0.25 - <1 FTE (Very Small)	1 - <2 FTE (Small)	2 - <3 FTE (Medium)	3 - <5 FTE (Large)	5 or more FTE (Very Large)	Unknown SLR
Cereal (9)	0	1	3	2	2	1	0
	0.0%	11.1%	33.3%	22.2%	22.2%	11.1%	0.0%
Dairy (42)	0	1	4	3	5	29	0
	0.0%	2.4%	9.5%	7.1%	11.9%	69.0%	0.0%
General Cropping (12)	0	0	3	1	5	3	0
	0.0%	0.0%	25.0%	8.3%	41.7%	25.0%	0.0%
General Cropping - Forage (2)	2	0	0	0	0	0	0
	100.0%	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%
Lowland Cattle & Sheep (29)	2	6	5	5	5	6	0
	6.9%	20.7%	17.2%	17.2%	17.2%	20.7%	0.0%
Mixed (79)	0	4	7	11	21	36	0
	0.0%	5.1%	8.9%	13.9%	26.6%	45.6%	0.0%
Other Cattle & Sheep (LFA) (52)	1	1	3	6	16	25	0
	1.9%	1.9%	5.8%	11.5%	30.8%	48.1%	0.0%
Specialist Cattle (LFA) (183)	5	18	18	32	51	59	0
	2.7%	9.8%	9.8%	17.5%	27.9%	32.2%	0.0%
Specialist horticulture & permanent crops (0)	0	0	0	0	0	0	0
	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%
Specialist Pigs (1)	0	0	0	0	0	1	0
	0.0%	0.0%	0.0%	0.0%	0.0%	100.0%	0.0%
Specialist Poultry (0)	0	0	0	0	0	0	0
	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%
Specialist Sheep (LFA) (35)	6	6	7	1	4	11	0
	17.1%	17.1%	20.0%	2.9%	11.4%	31.4%	0.0%
Unknown Business Type (1)	0	0	0	0	0	0	1
	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%	100.0%
Total (445)	16	37	50	61	109	171	1
	3.6%	8.3%	11.2%	13.7%	24.5%	38.4%	0.2%

Each bar in Figure 16 below shows the estimated percentage share by farm size of all feed ration plans undertaken by a given farm type. The total number of feed ration plans (denominator) for each farm type is shown in brackets along the vertical axis. For example, of the 10 reported feed ration plans undertaken by cereal farms, 20% were undertaken by very large cereal farms. This does not, however, necessarily imply that 20% of very large cereal farms undertake feed ration plans. Table 16 shows the supporting data values.

Table 16: The business types and SLR bandings of respondents who have undertaken a feed ration plan. The total response rate (denominator) for each businesses type can be seen in blue under the business type title in brackets.

Business Type	0 - <0.25 FTE (Extremely Small)	0.25 - <1 FTE (Very Small)	1 - <2 FTE (Small)	2 - <3 FTE (Medium)	3 - <5 FTE (Large)	5 or more FTE (Very Large)	Unknown SLR
Cereal (10)	0	1	4	1	2	2	0
	0.0%	10.0%	40.0%	10.0%	20.0%	20.0%	0.0%
Dairy (38)	0	1	4	1	5	27	0
	0.0%	2.6%	10.5%	2.6%	13.2%	71.1%	0.0%
General Cropping (17)	0	1	3	1	6	6	0
	0.0%	5.9%	17.6%	5.9%	35.3%	35.3%	0.0%
General Cropping - Forage (2)	1	0	1	0	0	0	0
	50.0%	0.0%	50.0%	0.0%	0.0%	0.0%	0.0%
Lowland Cattle & Sheep (31)	3	6	6	7	3	6	0
	9.7%	19.4%	19.4%	22.6%	9.7%	19.4%	0.0%
Mixed (81)	1	6	7	12	20	35	0
	1.2%	7.4%	8.6%	14.8%	24.7%	43.2%	0.0%
Other Cattle & Sheep (LFA) (52)	2	3	7	6	13	21	0
	3.8%	5.8%	13.5%	11.5%	25.0%	40.4%	0.0%
Specialist Cattle (LFA) (172)	8	25	16	26	45	52	0
	4.7%	14.5%	9.3%	15.1%	26.2%	30.2%	0.0%
Specialist horticulture & permanent crops (0)	0	0	0	0	0	0	0
	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%
Specialist Pigs (3)	0	0	1	0	0	2	0
	0.0%	0.0%	33.3%	0.0%	0.0%	66.7%	0.0%
Specialist Poultry (1)	0	0	0	0	0	1	0
	0.0%	0.0%	0.0%	0.0%	0.0%	100.0%	0.0%
Specialist Sheep (LFA) (82)	23	26	12	3	6	12	0
	28.0%	31.7%	14.6%	3.7%	7.3%	14.6%	0.0%
Unknown Business Type (3)	0	0	0	0	0	0	3
	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%	100.0%
Total (492)	38	69	61	57	100	164	3
	7.7%	14.0%	12.4%	11.6%	20.3%	33.3%	0.6%

Each bar in Figure 17 below shows the estimated percentage share by farm size of all animal health and welfare plans undertaken by a given farm type. The total number of animal health and welfare plans (denominator) for each farm type is shown in brackets along the vertical axis. For example, of the 17 reported animal health and welfare plans undertaken by cereal farms, 18% were undertaken by very large cereal farms. This does not, however, necessarily imply that 18% of very large cereal farms undertake animal health and welfare plans. Table 17 shows the supporting data values.

Table 17: The business types and SLR bandings of respondents who have undertaken an animal health and welfare plan. The total response rate (denominator) for each businesses type can be seen in blue under the business type title in brackets.

Business Type	0 - <0.25 FTE (Extremely Small)	0.25 - <1 FTE (Very Small)	1 - <2 FTE (Small)	2 - <3 FTE (Medium)	3 - <5 FTE (Large)	5 or more FTE (Very Large)	Unknown SLR
Cereal (17)	1	3	4	4	2	3	0
	5.9%	17.6%	23.5%	23.5%	11.8%	17.6%	0.0%
Dairy (40)	0	1	4	2	4	29	0
	0.0%	2.5%	10.0%	5.0%	10.0%	72.5%	0.0%
General Cropping (26)	0	2	4	2	9	9	0
	0.0%	7.7%	15.4%	7.7%	34.6%	34.6%	0.0%
General Cropping - Forage (8)	6	0	1	0	0	1	0
	75.0%	0.0%	12.5%	0.0%	0.0%	12.5%	0.0%
Lowland Cattle & Sheep (51)	5	13	11	8	6	8	0
	9.8%	25.5%	21.6%	15.7%	11.8%	15.7%	0.0%
Mixed (100)	3	10	12	12	24	39	0
	3.0%	10.0%	12.0%	12.0%	24.0%	39.0%	0.0%
Other Cattle & Sheep (LFA) (88)	1	9	12	12	22	32	0
	1.1%	10.2%	13.6%	13.6%	25.0%	36.4%	0.0%
Specialist Cattle (LFA) (233)	10	44	29	35	50	65	0
	4.3%	18.9%	12.4%	15.0%	21.5%	27.9%	0.0%
Specialist horticulture & permanent crops (2)	0	0	1	0	0	1	0
	0.0%	0.0%	50.0%	0.0%	0.0%	50.0%	0.0%
Specialist Pigs (3)	0	0	1	0	0	2	0
	0.0%	0.0%	33.3%	0.0%	0.0%	66.7%	0.0%
Specialist Poultry (1)	0	0	0	0	0	1	0
	0.0%	0.0%	0.0%	0.0%	0.0%	100.0%	0.0%
Specialist Sheep (LFA) (140)	43	33	23	5	11	25	0
	30.7%	23.6%	16.4%	3.6%	7.9%	17.9%	0.0%
Unknown Business Type (7)	0	0	0	0	0	0	7
	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%	100.0%
Total (716)	69	115	102	80	128	215	7
	9.6%	16.1%	14.2%	11.2%	17.9%	30.0%	1.0%

Each bar in Figure 18 below shows the estimated percentage share by farm size of all breeding plans undertaken by a given farm type. The total number of breeding plans (denominator) for each farm type is shown in brackets along the vertical axis. For example, of the 6 reported breeding plans undertaken by cereal farms, 17% were undertaken by very large cereal farms. This does not, however, necessarily imply that 17% of very large cereal farms undertake breeding plans. Table 17 shows the supporting data values.

Table 18: The business types and SLR bandings of respondents who have undertaken a breeding plan. The total response rate (denominator) for each businesses type can be seen in blue under the business type title in brackets.

Business Type	0 - <0.25 FTE (Extremely Small)	0.25 - <1 FTE (Very Small)	1 - <2 FTE (Small)	2 - <3 FTE (Medium)	3 - <5 FTE (Large)	5 or more FTE (Very Large)	Unknown SLR
Cereal (6)	1	0	3	0	1	1	0
	16.7%	0.0%	50.0%	0.0%	16.7%	16.7%	0.0%
Dairy (34)	0	1	4	1	4	24	0
	0.0%	2.9%	11.8%	2.9%	11.8%	70.6%	0.0%
General Cropping (12)	0	1	2	1	2	6	0
	0.0%	8.3%	16.7%	8.3%	16.7%	50.0%	0.0%
General Cropping - Forage (4)	3	0	0	0	0	1	0
	75.0%	0.0%	0.0%	0.0%	0.0%	25.0%	0.0%
Lowland Cattle & Sheep (33)	4	7	9	5	2	6	0
	12.1%	21.2%	27.3%	15.2%	6.1%	18.2%	0.0%
Mixed (61)	4	5	6	6	14	26	0
	6.6%	8.2%	9.8%	9.8%	23.0%	42.6%	0.0%
Other Cattle & Sheep (LFA) (47)	0	3	4	5	12	23	0
	0.0%	6.4%	8.5%	10.6%	25.5%	48.9%	0.0%
Specialist Cattle (LFA) (137)	8	23	12	19	33	42	0
	5.8%	16.8%	8.8%	13.9%	24.1%	30.7%	0.0%
Specialist horticulture & permanent crops (2)	0	0	1	0	0	1	0
	0.0%	0.0%	50.0%	0.0%	0.0%	50.0%	0.0%
Specialist Pigs (2)	0	0	0	0	0	2	0
	0.0%	0.0%	0.0%	0.0%	0.0%	100.0%	0.0%
Specialist Poultry (0)	0	0	0	0	0	0	0
	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%
Specialist Sheep (LFA) (94)	31	30	12	2	7	12	0
	33.0%	31.9%	12.8%	2.1%	7.4%	12.8%	0.0%
Unknown Business Type (3)	0	0	0	0	0	0	3
	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%	100.0%
Total (435)	51	70	53	39	75	144	3
	11.7%	16.1%	12.2%	9.0%	17.2%	33.1%	0.7%

Each bar in Figure 19 below shows the estimated percentage share by farm size of all biodiversity audits undertaken by a given farm type. The total number of biodiversity audits (denominator) for each farm type is shown in brackets along the vertical axis. For example, of the 16 reported biodiversity audits undertaken by cereal farms, 13% were undertaken by very large cereal farms. This does not, however, necessarily imply that 13% of very large cereal farms undertake biodiversity audits. Table 19 shows the supporting data values.

Table 19: The business types and SLR bandings of respondents who have undertaken a biodiversity plan. The total response rate (denominator) for each businesses type can be seen in blue under the business type title in brackets.

Business Type	0 - <0.25 FTE (Extremely Small)	0.25 - <1 FTE (Very Small)	1 - <2 FTE (Small)	2 - <3 FTE (Medium)	3 - <5 FTE (Large)	5 or more FTE (Very Large)	Unknown SLR
Cereal (16)	1	5	4	2	2	2	0
	6.3%	31.3%	25.0%	12.5%	12.5%	12.5%	0.0%
Dairy (10)	0	0	2	0	1	7	0
	0.0%	0.0%	20.0%	0.0%	10.0%	70.0%	0.0%
General Cropping (27)	0	3	4	2	6	12	0
	0.0%	11.1%	14.8%	7.4%	22.2%	44.4%	0.0%
General Cropping - Forage (10)	7	1	0	1	0	1	0
	70.0%	45.5%	0.0%	0.0%	9.1%	0.0%	0.0%
Lowland Cattle & Sheep (10)	1	2	3	1	1	2	0
	10.0%	20.0%	30.0%	10.0%	10.0%	20.0%	0.0%
Mixed (45)	2	0	5	5	12	21	0
	4.4%	0.0%	11.1%	11.1%	26.7%	46.7%	0.0%
Other Cattle & Sheep (LFA) (38)	1	3	4	4	9	17	0
	2.6%	7.9%	10.5%	10.5%	23.7%	44.7%	0.0%
Specialist Cattle (LFA) (63)	4	17	7	9	13	13	0
	6.3%	27.0%	11.1%	14.3%	20.6%	20.6%	0.0%
Specialist horticulture & permanent crops (1)	0	0	0	0	0	1	0
	0.0%	0.0%	0.0%	0.0%	0.0%	100.0%	0.0%
Specialist Pigs (0)	0	0	0	0	0	0	0
	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%
Specialist Poultry (0)	0	0	0	0	0	0	0
	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%
Specialist Sheep (LFA) (55)	17	11	8	1	5	13	0
	30.9%	20.0%	14.5%	1.8%	9.1%	23.6%	0.0%
Unknown Business Type (1)	0	0	0	0	0	0	1
	0.0%	0.0%	0.0%	0.0%	0.0%	0.0%	100.0%
Total (276)	33	42	37	25	49	89	1
	12.0%	15.2%	13.4%	9.1%	17.8%	32.2%	0.4%

2.2 Business Overview Questions

This section breaks down the results of each question within the survey. Not all questions were answered by each respondent as the survey was designed to allow livestock and mixed enterprises to answer all sections whilst business which are solely arable/horticulture answered the carbon audit, soil analysis, nutrient management, manure analysis and biodiversity sections. This means when analysing the answers of the survey it must be taken into account that not all of the questions will have 977 responses.

2.2.1 Land Permanently Owned by the Occupier

95.2% (930) of the respondents permanently or partially own the land they occupy (Figure 20). The areas range from 1 ha to 106745 ha in size.

2.2.2 Land rented on a full or seasonal tenancy (365 days or more)

31.8% (311) of the respondents rented land on a full tenancy (Figure 21) with areas ranging from 1 ha to 14054 ha in size.

37.4% (365) of the respondents rent seasonally with areas (Figure 22) ranging from 1 ha to 4243 ha in size.

2.2.3 Types of enterprises

The majority of the survey respondents have a primarily livestock enterprise, accounting for 48.7% (476) of businesses (Figure 23). Respondents who have a primarily arable enterprise account for 7.8% (76) of the total number of participants.

Beef (58%) and Sheep (64.9%) are the predominant enterprise types, closely followed by Arable farming (37.2%) (Figure 24 and Table 20).

Other common enterprises identified that were not included in the list provided as part of the survey include woodlands/forestry (27 respondents), horses/livery (11 respondents) and hay production (8 respondents) (Figure 25 and Table 20).

Table 20: Enterprises of the respondents of the survey.

Enterprise Type	Total Respondents	Percentage (Denominator 977)
Beef	567	58.0%
Sheep	634	64.9%
Dairy	67	6.9%
Poultry	62	6.3%
Pig	34	3.5%
Deer	7	0.7%
Arable	364	37.3%
Horticulture	36	3.7%
Diversified	114	11.7%
Forage Crops	2	0.2%
Permanent Grass	6	0.6%
Hay Production	8	0.8%
Goats	4	0.4%
Bees	5	0.5%
Horses/Livery	11	1.1%
Woodlands/Forestry	27	2.8%

2.2.4 Identify of the Respondents

The majority of the respondents identified themselves as farmers, accounting for 82.2% (803) (Figure 26).

2.2.5 Maintenance of Farm Records

Although there is a large number of respondents who use paper records (656), only 20.6% (202) of the total business surveyed use paper records solely (Figures 27, 28 and Table 21). 32.9% (321) of the business only use electronic methods to maintain their farm records and 46.5% (454) of business use a means of both electronic and paper record keeping.

Table 21: Methods used to maintain farm records.

Participant	Total Respondents	Percentage (Denominator 977)
Paper records	656	67.1%
Own computer records	571	58.4%
Mobile phone applications (Apps)	116	11.9%
Bespoke farm computer software package	349	35.7%

2.2.6 Who maintains the Business Records?

61.9% (605) of the respondents keep their own records while 38.1% (372) obtain assistance from other sources such as a family member (20.5%, 200) or an agent (16.8%, 164) (Figures 29, 30 and Table 22). Other sources that the respondents highlighted as being a source for keeping business records included accountants/book keepers (1.7%, 17) and farm secretaries (0.7%, 7) (Figure 31 and Table 22).

Table 22: Other sources of business record keeping.

Business Record Keeping Source	Total Respondents	Percentage (Denominator 977)
Agent	164	16.8%
Employee	63	6.4%
Family member	200	20.5%
Friend	7	0.7%
Agronomist	1	0.1%
Contractor	3	0.3%
Trust/Network Organisations	2	0.2%
RPID	5	0.5%
Farm Secretary	7	0.7%
Accountant	17	1.7%

2.3 Carbon Audit

2.3.1 Businesses undertaking carbon audits

372 of the respondents have had a carbon audit on their business accounting for 38.1% of the total number of respondents (Figure 32). Whilst the majority of the participants have not carried out a Carbon Audit 61.9% (605), reasons for not carrying out a carbon audit can be found in section 2.3.5. 15.8% (154) of respondents are planning on carrying out an audit in 2022 (Figure 32).

Out of the 372 respondents who have conducted a carbon audit, The majority of respondents 70.2% (261) have only conducted one carbon audit in the last five years (Figure 33 and Table 23) and so highlighting that this is becoming a more prominent practice within the agricultural sector. There appears to be a drop in participants undergoing a carbon audit between 2020 and 2021 but this may reflect changes due to the Covid-19 Pandemic, or potentially that the farmers that are more likely to carry out the carbon audit have done it in more recent years.

Table 23: Year in which a carbon audit was undertaken for a business.

Year of Carbon Audit	Total Respondents	Percentage (Denominator 372)
2022	55	14.8%
2021	116	31.2%
2020	137	36.8%
2019	100	26.9%
2018	56	15.1%
Earlier than 2018	61	16.4%

2.3.2 Carbon audit tools

The most popular carbon audit tool used by the respondents is AgreCalc accounting for 65.6% (244). It was however pointed out that AgreCalc is designed for large farms and mono cultures and that improving the software for smaller and more diverse farms would be a huge improvement (Figure 34 and Table 24).

Other carbon audit tools used by the respondents included Farm Carbon Toolkit, Alltech and Intellync. 4.3% (16) of the respondents did not know what tools were used as they had an agency or commercial company (SRUC, SAC, Sainsbury’s, Arla) complete the carbon audit for them.

Table 24: Types of carbon tools used by respondents.

Carbon Audit tool	Total Respondents	Percentage (Denominator 372)
AgreCalc	244	65.6%
Cool Farm Tool	11	3.0%
Solagro (JRC) Carbon Calculator	1	0.3%
I do not know	97	26.1%
Other	29	7.8%

2.3.3 Who did the carbon audit?

Results indicate that 80.7% (300) of participants use an outside source to carry out a carbon audit (Figure 35).

2.3.4 Why businesses undertook a carbon audit?

According to the respondents, the primary reason for 48.4% (180) of the respondents to have completed a carbon audit was due to it being part of the Beef Efficiency Scheme (48.4%, 180) closely followed 34.1% (127) by the funding was available at the time to have the carbon audit done (Figure 36 and Table 25).

1.6% (6) of respondents also pointed out that they completed a carbon audit because of the Scottish Farm Business Survey also out of their own interest as noting it was necessary to apply for organic status.

Table 25: Reasons as to why respondents have undertaken a carbon audit.

Carbon Audit Reasons	Total Respondents	Percentage (Denominator 372)
Business efficiency	110	29.6%
Baseline for business	100	26.9%
Funding was available to have it done	127	34.1%
Recommended to do it	59	15.9%
As part of the Beef Efficiency Scheme (BES)	180	48.4%
A requirement of the buyer(s) of my product(s)	48	12.9%
To reduce greenhouse gas emissions	59	15.9%
Other	33	8.9%

2.3.5 The reason why businesses have not undertaken a carbon audit

A large quantity of the respondents (605) who have not completed a carbon audit, 54% (327), state that they do not know enough about the process. 28.1% (170) due to time, closely followed with 26.4% (160) of respondents stating cost (Figure 37 and Table 26). Respondents noted that the carbon tools currently on the market do not always match their enterprises (for example, crofts, bogs, deer and renewables) making it difficult to get accurate readings. These is also a belief as there is no carbon audit standardisation that the tools currently on the market do not account for carbon accurately. Others state that they feel that the agricultural industry is being unfairly targeted when there are bigger carbon culprits across Scotland.

Table 26: Reasons as to why respondents have not undertaken a carbon audit.

Reason for not undertaking carbon audit	Total Respondents	Percentage (Denominator 605)
I do not have all the information required by a carbon audit tool	129	21.3%
I do not have the necessary equipment	89	14.7%
I do not think it is relevant to my business	114	18.8%
A carbon audit is not required by the buyer(s) of my product(s)	146	24.1%
I do not know enough about it	327	54.0%
Cost	160	26.4%
Time	170	28.1%
It is not part of my quality assurance scheme	94	15.5%
I do not see the benefit in doing a carbon audit	75	12.4%
I do not think it can accurately calculate my carbon footprint	107	17.7%
I have not been in business long enough	20	3.3%
Other	79	13.1%

2.3.6 Changes to businesses as a result of a carbon audit

Figure 38 shows that just 51.6% (192) of the participants that have conducted a carbon audit in the past have not made any changes suggested to them in their carbon audit. Further insight into why participants of the survey are not carrying out these audit suggestions can be found in section 2.3.12.

2.3.7 The energy efficiency changes respondents implemented/intend to implement following a carbon audit

Those who have implemented/or intend to implement energy efficiency changes following a carbon audit (180), 55.6% (100) noted the biggest change was/would be to the assessment of the efficiency of working practices. 47.2% (85) stated the reduction of energy lighting and a further 47.2% (85) noted the assessment of the efficiency of existing vehicles, fixed equipment and machinery (Figure 39 and Table 27).

Respondents also noted that there were no collection systems in Northern Scotland for the recycling of agricultural plastics.

Table 27: Energy efficiency changes after a carbon audit.

Energy Efficiency Changes	Total Respondents	Percentage (Denominator 180)
Assess efficiency of existing vehicle, fixed equipment and machinery (e.g. assess capacity/sizing of systems, regular and rigorous maintenance, renew inefficient equipment)	85	47.2%
Assess efficiency of working practices (e.g. tillage, passes)	100	55.6%
Carry out a renewable energy feasibility study (e.g. consider installing wind turbine or micro-hydro scheme, solar panels, heat pumps)	51	28.3%
Installed renewable energy generation	28	15.6%
Heat recovery systems	7	3.9%
Improve building infrastructure	37	20.6%
Reduce energy lighting	85	47.2%
Fuel efficiency	64	35.6%
Waste management	53	29.4%
Recycling materials	70	38.9%
Monitor electricity usage	76	42.2%
Not applicable (N/A)	6	3.3%
Other	20	11.1%

2.3.8 The technology efficiency changes respondents implemented/intend to implement following a carbon audit

Those who have implemented/or intend to implement technology efficiency changes following a carbon audit (180), 38.3% (69), noted the biggest change was/would be the use of precision technology. While a further 38.3% (69) have implemented/or intend to implement the use of EID equipment (Figure 40 and Table 28).

Table 28: Technology efficiency changes after a carbon audit.

Technology Efficiency Changes	Total Respondents	Percentage (Denominator 180)
Use of EID equipment (Electronic Identification)	69	38.3%
Precision technology	69	38.3%
Enhanced Software	20	11.1%
Automated processes	11	6.1%
Make more use of modern control systems (e.g. use temperature and ventilation sensors/controls, log and evaluate data)	13	7.2%
Not applicable (N/A)	52	28.9%
Other	9	5.0%

2.3.9 The crop and soil efficiency changes respondents implemented/intend to implement following a carbon audit

Those who have implemented/or intend to implement crop and soil changes following a carbon audit (180), 70% (126) noted the biggest change was/would be livestock manure efficiency. 56.7% (102) stated the efficient use of inputs and 49.4% (89) noted inorganic fertiliser efficiency (Figure 41 and Table 29). Respondents noted that soil sampling was also practiced as well as plant tissue analysis.

Table 29: Crop and soil management changes after a carbon audit.

Crop and Soil Management Changes	Total Respondents	Percentage (Denominator 180)
Inorganic fertiliser efficiency	89	49.4%
Livestock manure efficiency	126	70.0%
Nutrient Management plans	81	45.0%
Soil protection	65	36.1%
Efficient use of inputs	102	56.7%
Not applicable (N/A)	13	7.2%
Other	16	8.9%

2.3.10 The livestock management changes respondents implemented/intend to implement following a carbon audit

Those who have implemented/or intend to implement livestock changes following a carbon audit (180), 55.6% (100) noted the biggest change was/would be breeding and fertility improvements. 53.9% (97) stated animal health measures including disease control and 48.9% (88) noted feeding regime improvements (Figure 42 and Table 30). Respondents noted that they implemented better grazing management and replaced livestock more suited to the environment in which the business is based. ‘Other’ answers highlight the conversion to organic farming.

Table 30: Livestock management changes after a carbon audit.

Livestock Management Changes	Total Respondents	Percentage (Denominator 180)
Animal health measures including disease control	97	53.9%
Breeding & fertility improvements	100	55.6%
Performance benchmarking	70	38.9%
Feeding regime improvements	88	48.9%
Use of methane reducing feed additives	22	12.2%
Faster finishing of livestock	48	26.7%
Other livestock management improvements	38	21.1%
Not applicable (N/A)	20	11.1%
Other	14	7.8%

2.3.11 Proportion changes proposed by the audit were implemented

49.4% (89) of respondents have implemented over half of the changes proposed by the carbon audit. 27.2% (49) respondents have implemented less than quarter of the changes proposed by the carbon audit (Figure 43).

2.3.12 Reasons why actions have not been implemented following a carbon audit

Out of the 192 respondents who did not implement actions following a carbon audit 29.7% (57) noted that there were no recommendations for change to their holding (Figure 44 and Table 31).

Table 31: Reasons as to why respondents have not undertaken changes after a carbon audit.

Reasons for not making changes after a carbon audit	Total Respondents	Percentage (Denominator 192)
Implementation cost of recommended measures was too high	24	12.5%
Specialised advice and training was not available	13	6.8%
Measures recommended were not relevant to my enterprise	36	18.8%
Actions do not fit with my business cycle/plan	33	17.2%
Lack of time	24	12.5%
Not considered a business priority to date	50	26.0%
No recommendations for change	57	29.7%
Other	47	24.5%

2.4 Soil Testing

2.4.1 Businesses undertaking soil testing

Of the total respondents (977), 73% (713) state that they carry out soil testing for their enterprise (Figure 45).

2.4.2 Why businesses carry out soil testing

Out of the 713 respondents who stated that they do soil testing, 66.9% (477) of these respondents carry out soil testing to reduce input costs. 66.5% (474) noted that soil testing aids in the targeted use of inorganic fertiliser could be considered another cost saving measure (Figure 46 and Table 32).

Table 32: Reasons as to why respondents undertake soil testing.

Reasons for soil testing	Total Respondents	Percentage (Denominator 713)
Reduce input costs	477	66.9%
Targeted use for organic manure	298	41.8%
Targeted use of inorganic fertiliser	474	66.5%
Informs decision making on crop rotations	267	37.4%
Advised to do so by my consultant	94	13.2%

2.4.3 Soil testing measurements

pH accounts for 98.9% (705) of the soil testing measurements taken by the participants of this survey, with only 41.2% (294) of respondents conducting organic matter analysis (Figure 47 and Table 33).

Table 33: Soil testing measurements undertaken.

Soil testing measurements	Total Respondents	Percentage (Denominator 713)
pH	705	98.9%
Organic matter	294	41.2%
Chemistry (Phosphate/Potassium)	617	86.5%
Trace elements (Magnesium, Zinc etc.)	493	69.1%

2.4.4 The frequency of which businesses take soil testing measurements

In most cases pH, Organic matter, Chemistry and Trace element measurements are taken across a sample of fields over a 4-5 year cycle with only three respondents doing pH, trace element and organic matter analysis every 6 months (Figure 48 and Table 34).

Respondents have noted that they take the measurements normally when reseeding their fields or changing the crop type. Others also mentioned that in addition to the measurements included in this survey they also undertake plant tissue analysis and analysis of the soil microbiology.

Table 34: Frequency of soil testing.

Soil Testing Measurements (Denominator 713)	Every 6 months	Annually	Every second year	4-5 year cycle
pH	1	39	85	577
	0.14%	5.47%	11.92%	80.93%
Organic matter	1	19	40	301
	0.14%	2.66%	5.61%	42.22%
Chemistry (Phosphate/Potassium)	0	38	66	529
	0.00%	5.33%	9.26%	74.19%
Trace elements (Magnesium, Zinc etc.)	1	32	57	428
	0.14%	4.49%	7.99%	60.03%

2.5 Nutrient Management Plan

Out of the 365 (37.4%) respondents who stated that they have a nutrient management plan, 49% (179) use an advisor to complete the plan, while 51% (186) complete the plan themselves (Figure 49 and 50).

The method used predominantly to record a nutrient management plan by the respondents is paper accounting for 40.8% (149) of respondents followed 29.3% (107) who use the SRUC Technical Notes. 20.5% (75) of the respondents use paper records only to record their nutrient management plan (Figure 51 and Table 35).

Other system used by the respondents included RHIZA, Muddy Boots, National Milk Records (NMR), Scottish Agronomy and SOYL along with Nitrogen Vulnerable Zones (NVZ) plans in collaboration with Scottish Agencies (SRUC and SAC).

Table 35: The system used by respondents.

Nutrient Management Plan System	Total Respondents	Percentage (Denominator 365)
Planet	36	9.9%
SRUC Technical Notes (Scotland's Rural College)	107	29.3%
Farm business software	27	7.4%
Paper plan/record	149	40.8%
I do not know	59	16.2%
Other	28	7.7%

A Nutrient Management Plan is a requirement for farms located within a Nitrate Vulnerable Zone (NVZ). Out of the 365 businesses who responded “Yes” to carrying out a Nutrient Management Plan, 54.8% (200) are located within a NVZ (Figure 52).

2.6 Soil Management

In terms of soil management, the most common practice conducted by 53.9% (527) of respondents is keeping pH at an optimum level. 52.1% (509) target the use of organic manure (Figure 53 and Table 36).

54.2% (529) of respondents have never integrated pulses/legumes into cropping. 53.1% (519) have never used catch or cover crops and 52.8% (516) have never used nitrification inhibitors (Figure 53). 37.6% (367) of the respondents do not know enough about the use of nitrification inhibitors while 19% (186) do not know enough about visual evaluation of soil structure (VESS).

Table 36: Soil management practices undertaken.

Soil Management Practices (Denominator 977)	I don't know enough about it	I have never done it	Occasionally	Regularly
Use of precision technology	143	424	188	222
	14.6%	43.4%	19.2%	22.7%
Visual evaluation of soil structure (VESS)	186	323	265	203
	19.0%	33.1%	27.1%	20.8%
Introduce multi-species grass swards e.g. chicory, plantain, clover mix etc.	77	398	245	257
	7.9%	40.7%	25.1%	26.3%
Minimise tillage e.g. direct drilling/min till or over-seeding practices	61	47	292	217
	6.2%	4.8%	29.9%	22.2%
Use of catch and cover crops	99	519	220	139
	10.1%	53.1%	22.5%	14.2%
Use of Nitrification inhibitors	367	516	73	21
	37.6%	52.8%	7.5%	2.1%
Reduced use of pesticides	48	197	315	417
	4.9%	20.2%	32.2%	42.7%
Rotate crops to build nutrients and soil structure	38	354	184	401
	3.9%	36.2%	18.8%	41.0%
Integrate pulses/legumes into cropping	96	529	173	179
	9.8%	54.1%	17.7%	18.3%
Targeted use of inorganic fertiliser	50	233	196	498
	5.1%	23.8%	20.1%	51.0%
Targeted use for organic manure	43	212	213	509
	4.4%	21.7%	21.8%	52.1%
Reduced use of inorganic nutrient inputs	88	157	332	400
	9.0%	16.1%	34.0%	40.9%
Continuous soil cover	154	196	173	454
	15.8%	20.1%	17.7%	46.5%
Keeping pH at an optimum level	55	152	243	527
	5.6%	15.6%	24.9%	53.9%

2.7 Manure Analysis

2.7.1 Business undertaking manure analysis

11% of the total respondents complete manure analysis (Figure 54). Reasons for participants not undertaking manure analysis can be found in section 2.7.5.

2.7.2 Most common type of manure analysis

The most common type of manure analysis according to the 110 respondents who do undertake manure analysis is farm yard manure accounting for 55.5% (61) of the respondents (Figure 55).

2.7.3 Why businesses carry out manure analysis

The main reason for 73.6% (81) of respondents to carry out manure analysis is to help them target the use of applications (Figure 56 and Table 37). Others made note that they had to do manure analysis as it was a requirement of their organic farming scheme. Others noted that they had to have their manure analysed to meet the PAS110 analysis requirements.

Table 37: Reasons as to why respondents carry out many analysis.

Reasons for Manure Analysis	Total Respondents	Percentage (Denominator 110)
Target use of applications	81	73.6%
Cut costs	56	50.9%
Reduce fertiliser use	76	69.1%
Other	12	10.9%

2.7.4 The changes made by businesses as a result of the manure analysis.

Since conducting manure analysis, 70% (77) of the respondents have reduced the amount of chemical fertiliser applied to their land followed, 51.8% (57) have changed the organic manure application rates (Figure 57 and Table 38). Respondents noted that the main change for their business has been the switch in focus from chemical nutrition to biological, others stated it was necessary to make changes to become more organic.

Table 38: Changes made by respondents as a result of manure analysis.

Changes made after Manure Analysis	Total Respondents	Percentage (Denominator 110)
Reduced chemical fertiliser application	77	70.0%
Changed organic manure application rates	57	51.8%
Use slurry additives/inoculants	11	10.0%
Low emission manure and slurry spreading	18	16.4%
No action taken	14	12.7%
Other	5	4.5%

2.7.5 Why businesses have not carried out manure analysis

Of the 867 respondents who stated that they do not carry out manure analysis, 36.1% (313) of them do not see the need in manure analysis while 28.5% (247) do not believe it is relevant to their business (Figure 58).

5.7% (49) of respondents have stated that their farms do not produce enough manure to merit getting it tested while 1.5% (13) had never heard of manure analysis before encountering it in this survey. On a positive note, 1.4% (12) mentioned that they plan on performing manure analysis in the future (Figure 59 and Table 39).

Table 39: Reasons as to why respondents do not carry out manure analysis.

Reasons as to why respondents do not carry out Manure Analysis	Total Respondents	Percentage (Denominator 867)
Cost	194	22.4%
Time	136	15.7%
Export it	8	0.9%
Difficult to interpret results	110	12.7%
Not relevant to my business	247	28.5%
I do not see the need to do it	313	36.1%
Considers manure analysis to be variable and inaccurate	11	1.3%
Does not use manure on their farm	29	3.3%
Does not produce enough farm yard manure	49	5.7%
Do not know enough about the process	12	1.4%
Did not realise it was something they could do	13	1.5%
Plan on performing manure in the future	12	1.4%
Never considered carrying manure analysis out	22	2.5%
Use published figures from agencies	12	1.4%
Other	206	23.8%

2.8 Forage Analysis

2.8.1 Businesses undertaking forage analysis

As seen in the graph below 49.2% (445) of the participants who have livestock enterprises undertake forage analysis for their business (Figure 60). Reasons as to why producers have not undertaken forage analysis can be found in section 2.8.4.

2.8.2 The types of forage analysis undertaken by businesses

91.2% (406) of the respondents use analysis techniques on their silage (Figure 61 and Table 40).

Table 40: Types of forage analysed.

Forage Analysis Type	Total Respondents	Percentage (Denominator 445)
Silage	406	91.2%
Hay	51	11.5%
Haylage	89	20.0%
Whole crop cereals	51	11.5%
Straw	7	1.6%

2.8.3 Changes made to business as a result of forage analysis

53.5% (238) respondents noted that they decreased the volume of concentrates per head after conducting forage analysis. 40.2% (179) have changed the volume of forage feed. 20.2% (90) of the respondents noted that they have not taken any actions after receiving the results of the forage analysis (Figure 62 and Table 41).

Many respondents noted that the results they receive from forage analysis will dictate what actions they undertake that year – it differs year upon year. Others noted that they undertake forage analysis every year and change winter rations according to the results – therefore at times concentrate use goes up, sometimes it reduces, sometimes it stays the same. It depends on both the analysis results and the stock being fed.

Table 41: Changes made after forage analysis.

Forage Changes	Total Respondents	Percentage (Denominator 445)
Increased volume of concentrates per head	139	31.2%
Decreased volume of concentrates per head	238	53.5%
Changed volume of forage fed	179	40.2%
No action taken	90	20.2%
Other	52	11.7%

2.8.4 Why some businesses do not carry out forage analysis

The majority of respondents (459) have not carried out forage analysis as 35.7% (164) do not believe it is relevant to their business while 30.7% (141) do not see the need in doing the analysis (Figure 63 and Table 42).

Respondents noted that examining their livestock performance or considering their weights are enough of an indicator as to whether the forage is of good quality along with helping the respondent determine how much feed to supply the livestock with. Others stated that their business is too small for it to be worth the cost. 1.3% (6) stated that they did not know enough about the process while others are considering undertaking forage analysis in the future.

Table 42: Reasons as to why respondents have not undertaken forage analysis.

Reasons for not making changes after forage analysis	Total Respondents	Percentage (Denominator 459)
Cost	87	19.0%
Difficult to interpret results	28	6.1%
Only purchase small amounts of forage	81	17.6%
I do not see the need to do this	141	30.7%
Not relevant to my business	164	35.7%
Other	87	19.0%

2.9 Feed Ration Plan

2.9.1 Businesses undertaking a feed ration plan

Out of the 903 respondents who answered this section of the survey, 54.5% (492) have undertaken a feed ration plan (Figure 64). Reasons as to why businesses have not undertaken a feed ration plan can be found in section 2.9.5.

2.9.2 Business types undertaking feed ration plans

71.8% (353) of respondents who carry out feed ration plans (492) undertake it for their beef followed by 51.8% (255) who undertake it for their sheep (Figure 65 and Table 43). Respondents also noted that they carry out feed ration plans for their horses as well bees.

Table 43: Enterprise types of respondents that undertake a feed ration plan.

Enterprise Type	Total Respondents	Percentage (Denominator 492)
Beef	353	71.7%
Sheep	255	51.8%
Dairy	57	11.6%
Poultry	9	1.8%
Pig	10	2.0%
Deer	3	0.6%
Other	5	1.0%

2.9.3 Who created the feed ration plan and how often is it reviewed

55.7% (274) of the respondents create their own feed ration plan followed by 48.8% (240) who get assistance from a feed representative (Figure 66 and Table 44). 48% (236), of the respondents carry out reviews of their feed ration plan each year, while 30.7% (151) update their plan on a more continuous basis (Figure 67 and Table 45).

Table 44: Enterprise types of respondents that undertake a feed ration plan.

Who created the feed ration plan	Total Respondents	Percentage (Denominator 492)
Self	274	55.7%
Feed Representative	240	48.8%
Independent Nutritionist	72	14.6%
Consultant	59	12.0%

Table 45: Frequency at which feed ration plan reviews are undertaken.

Feed Ration Plan Occurrence	Total Respondents	Percentage (Denominator 492)
Annually	236	48.0%
Every six months	24	4.9%
Summer/Winter	40	8.1%
Stage of lactation	6	1.2%
Calving/lambing	22	4.5%
Continuously	151	30.7%
Growth stage	13	2.6%

2.9.4 Actions made by a business as a result of a feed ration plan

60.8% (299) of respondents noted that they implemented continuous monitoring after initially completing a feed ration plan. 56.1% (276) reduced concentrates usage per head (Figure 68 and Table 46). 5.1% (25) of the respondents noted that they take no action after completing of a feed ration plan (Figure 68 and Table 46).

Table 46: Actions implemented after feed ration plan.

Feed Ration Plan Actions	Total Respondents	Percentage (Denominator 492)
Reduced concentrate usage per head	276	56.1%
Increased concentrate usage per head	148	30.1%
Continual monitoring	299	60.8%
Use methane reducing feed additives	37	7.5%
No action taken	25	5.1%
Other	28	5.7%

2.9.5 Why businesses do not carry out feed ration plans

Of the 411 respondents have not carried out a feed plan, 42.3% (174) did not believe it is relevant to their business and 39.2.% (161) do not see the need in doing the analysis (Figure 69 and Table 47).

Many of the respondents stated that they rely on body condition scoring of animals appropriate for the time of year. Others noted that they do not have the relevant equipment for weighing and dispensing feed while others are Pasture for Life certified and therefore do not give feed to their livestock.

Table 47: Reasons as to why respondents have not carried out a feed ration plan.

Reasons why respondents have not undertaken a feed ration plan	Total Respondents	Percentage (Denominator 411)
Cost	52	12.7%
I do not see the need to do this	161	39.2%
Not relevant to my business	174	42.3%
Other	88	21.4%

2.10 Animal Health and Welfare Plan

2.10.1 Businesses undertaking an animal health and welfare plan

Out of the 902 respondents who answered this section of the survey, 79.4% (716) have an animal health and welfare plan (Figure 70). Reasons as to why participants have not undertaken an animal health and welfare plan can be found in section 2.10.7.

2.10.2 Businesses with an accredited animal health and welfare plan

76.8% (550) of the accredited animal health and welfare plans used by the respondents (716) is Quality Meat Scotland (Figure 71 and Table 48). 16.2% (116) of the respondents do not have an accredited plan at present but a small group of these respondents are currently awaiting approval to join Quality Meat Scotland.

Other animal health and welfare accredited plans used by the respondents included Pasture for Life, Demeter and Organic Association, Quality Assured Farm Venison, High Health Herdcare, Biobest, SAHPS: The Animal Health Planning System and Marks and Spencer’s Accredited Scheme via Scotbeef.

Table 48: Accredited plan used by respondents.

Animal health and welfare plan accreditation	Total Respondents	Percentage (Denominator 716)
Scottish Organic Producers Association (SOPA)	29	4.1%
Quality Meat Scotland	550	76.8%
Premium Cattle Health Scheme	97	13.5%
Red Tractor Scheme	71	9.9%
British Lion Eggs	3	0.4%
Linking Environment and Farming (LEAF) Marque	11	1.5%
Scottish Quality Wild Venison Assurance Scheme	5	0.7%
Soil Association	14	2.0%
Organic Assurance Scheme	7	1.0%
No - I do not have an accredited plan	116	16.2%
Other	49	6.8%

2.10.3 Who created the animal health and welfare plan?

76.1% (545) of animal health and welfare plans (716) are created by the respondents vet (Figure 72 and Table 49). 20.7% (148) of the respondents create their animal health and welfare plan without the assistance of a vet or advisor.

Table 49: Reasons to why respondents have carried out an animal health and welfare plan.

Who created the animal health & welfare plan	Total Respondents	Percentage (Denominator 716)
Self	359	50.1%
Advisor	48	6.7%
Vet	545	76.1%

2.10.4 Why businesses carry out an animal health and welfare plan

A large majority of the respondents (716) create an animal health and welfare plan because 77% (551) believe it to be good practice (Figure 73 and Table 50). Respondents have stated that the plan is very useful as it ensures that the health and welfare of the animals within the business are maintained or else improved throughout the year. 77.2% (553) of respondents also have noted that an animal health and welfare plan is required as part of their assurance schemes.

Table 50: Reasons to why respondents have carried out an animal health and welfare plan.

Reasons for animal health and welfare plan	Total Respondents	Percentage (Denominator 716)
A requirement of the buyer(s) of my product(s)	173	24.2%
Requirement for assurance scheme	553	77.2%
Good practice	551	77%
Other	30	4.2%

2.10.5 Reviews of animal health and welfare plan

78.5% (562) of respondents review their animal health and welfare plans on a yearly basis (Figure 74 and Table 51).

Table 51: Frequency at which respondents have carried out an animal health and welfare plan.

Animal health and welfare plan occurrence	Total Respondents	Percentage (Denominator 716)
Over a year	89	12.4%
Annually	562	78.5%
6 months	30	4.2%
3 months	15	2.1%
Monthly	20	2.8%

2.10.6 Actions businesses carry out due to an animal health and welfare plan

Due to having an animal health and welfare plan, 83.5% (598) of the respondents treat their livestock to control parasites. 74.3% (532) administer mineral and trace elements and 74.3% (532) also vaccinate for disease (Figure 75 and Table 52).

30.2% (216) of respondents have never benchmarked livestock performance. 28.2% (202) have never given their livestock treatments to reduce mastitis. 5.9% (42) do not know enough about benchmark livestock performance and 4.5% (32) do not know enough about health screening (Figure 75).

Table 52: Actions undertaken after animal health and welfare plan.

Animal health and welfare plan practices (Denominator 716)	Regularly	Occasionally	I have never done it	I don't know enough
Monitor antibiotic use	513	132	65	6
	71.6%	18.4%	9.1%	0.8%
Test for disease	371	269	74	2
	51.8%	37.6%	10.3%	0.3%
Vaccinate for disease	532	134	48	2
	74.3%	18.7%	6.7%	0.3%
Health screening	326	231	127	32
	45.5%	32.3%	17.7%	4.5%
Actions to reduce lameness	519	148	46	3
	72.5%	20.7%	6.4%	0.4%
Treatment to reduce mastitis	194	307	202	13
	27.1%	42.9%	28.2%	1.8%
Treatments to control parasites	598	110	7	3
	83.5%	15.4%	1.0%	0.4%
Administer mineral & trace element supplements	532	142	39	3
	74.3%	19.8%	5.4%	0.4%
Benchmark livestock performance	244	214	216	42
	34.1%	29.9%	30.2%	5.9%

2.10.7 Why businesses do not have an animal health and welfare plan

45.2% (84) of respondents have not carried out an animal health and welfare plan (186) due to it not being required for their business. 31.2% (58) have not carried out a plan because they do not see the need for one (Figure 76 and Table 53). 9.1% (17) of respondents do state that although they do monitor the health and wellbeing of their livestock they do not have a formal plan.

Table 53: Reasons as to why respondents have not carried out an animal health and welfare plan.

Reason for not undertaking a animal health and welfare plan	Total Respondents	Percentage (Denominator 186)
Cost	23	12.4%
Time	13	7.0%
Not required for my business	84	45.2%
I do not see the need for this	50	26.9%
Other	58	31.2%

2.10.8 Actions businesses carry out due to having an animal health and welfare plan but have not documented

Although the respondents do not have a formal animal health and welfare plan, 52.7% (98) regularly preform treatments to control parasites, 49.5% (92) administer mineral & trace element supplements and 45.2% (84) undertake actions to reduce lameness (Figure 77 and Table 54).

60.8% (113) of respondents have never benchmarked livestock performance. 59.1% (110) have never given treatments to reduce mastitis and 55.9% (104) have never had a health screening for their livestock (Figure 77 and Table 52). 12.9% (24) of respondents and 10.2% (19) do not know enough about benchmarking livestock performance or health screening respectively (Figure 77 and Table 54).

Table 54: Actions undertaken after animal health and welfare plan which have not been documented.

Animal health and welfare plan practices - not documented (Denominator 186)	Regularly	Occasionally	I have never done it	I don't know enough
Monitor antibiotic use	58	30	85	11
	31.2%	16.1%	45.7%	5.9%
Test for disease	29	49	93	13
	15.6%	26.3%	50.0%	7.0%
Vaccinate for disease	72	37	67	8
	38.7%	19.9%	36.0%	4.3%
Health screening	41	20	104	19
	22.0%	10.8%	55.9%	10.2%
Actions to reduce lameness	84	37	54	9
	45.2%	19.9%	29.0%	4.8%
Treatment to reduce mastitis	18	43	110	13
	9.7%	23.1%	59.1%	7.0%
Treatments to control parasites	98	23	55	8
	52.7%	12.4%	29.6%	4.3%
Administer mineral & trace element supplements	92	27	56	9
	49.5%	14.5%	30.1%	4.8%
Benchmark livestock performance	26	21	113	24
	14.0%	11.3%	60.8%	12.9%

2.11 Breeding Plan

2.11.1 Businesses undertaking a breeding plan

Out of the 900 respondents who answered this section of the survey, 48.3% (435) have undertaken a breeding plan (Figure 78). Reasons as to why businesses have not undertaken a breeding plan can be found in section 2.11.5.

2.11.2 Who created the breeding plan and how often is it reviewed

92.2% (401) of the respondents create their own breeding plan. 7.8% (34) get assistance from an advisor (Figure 79). 66.9% (291) of the respondents carry out reviews of their breeding plan each year (Figure 80 and Table 55).

Table 55: Frequency at which respondents carry out a review of their breeding plan.

Breeding plan occurrence	Total Respondents	Percentage (Denominator 435)
Over a year	61	14.0%
Annually	291	66.9%
6 months	42	9.7%
3 months	23	5.3%
Monthly	18	4.1%

2.11.3 Reasons businesses have created a breeding plan

84.1% (366) of the respondents have created a breeding plan to improve livestock performance while 71.3% (310) state that a plan improves business efficiency (Figure 81 and Table 56). Respondents also noted have a breeding plan helped with safety and the ease of handling livestock along with improving food conversion and reducing the age to slaughter.

Table 56: Reasons to why respondents carry out a breeding plan.

Reason for breeding plan	Total Respondents	Percentage (Denominator 435)
To improve livestock genetics	271	62.3%
To improve livestock health	290	66.7%
To improve livestock performance	366	84.1%
Business efficiency	310	71.3%
Other	22	5.1%

2.11.4 Actions businesses carry out due to having a breeding plan

Due to having a breeding plan, 83.9% (365) of respondents regularly breed their own replacements. 76.1% (331) regularly have pregnancy scans conducted on their livestock and 64.6% (281) use body condition scoring (Figure 82 and Table 57).

79.8% (347) of the respondents have never used sexed semen in livestock production and 75.9% (330) have never taken the pelvic measure of their cattle. 15.6% (68) and 6.2% (27) of respondents do not know enough about breeding livestock for lower emissions or taking the pelvic measure of cattle respectively.

Respondents also noted the importance of choosing the suitability of cows going to which type of bull or breed of bull and therefore size, previous calving history, general health and maternal instincts should also be considered.

Table 57: Actions undertaken by respondents after breeding plan.

Breeding plan practices - documented (Denominator 435)	Regularly	Occasionally	I have never done it	I don't know enough
Semen testing sires	72	131	228	4
	16.6%	30.1%	52.4%	0.9%
Pregnancy scanning	331	60	44	0
	76.1%	13.8%	10.1%	0.0%
Body condition scoring	281	106	43	5
	64.6%	24.4%	9.9%	1.1%
Weight monitoring	218	114	103	0
	50.1%	26.2%	23.7%	0.0%
Breeding for lower emissions	22	31	314	68
	5.1%	7.1%	72.2%	15.6%
Breed own replacements	365	52	17	1
	83.9%	12.0%	3.9%	0.2%
Use Estimated Breeding Values for stock selection	158	122	136	19
	36.3%	28.0%	31.3%	4.4%
Stricter culling regime	275	125	34	1
	63.2%	28.7%	7.8%	0.2%
Breeding for increased growth rate	247	105	79	4
	56.8%	24.1%	18.2%	0.9%
Increasing breeding percentage rates	265	90	71	9
	60.9%	20.7%	16.3%	2.1%
Reducing age at first calving	148	76	196	15
	34.0%	17.5%	45.1%	3.4%
Reducing calving interval	179	71	168	17
	41.1%	16.3%	38.6%	3.9%
Pelvic measure of cattle	35	43	330	27
	8.0%	9.9%	75.9%	6.2%
Using sexed semen in livestock production	43	24	347	21
	9.9%	5.5%	79.8%	4.8%

2.11.5 Why businesses do not have a breeding plan

Of the 464 respondents that do not have a breeding plan, 38.6% (179) of respondents carry out actions related to a breeding plan but have not documented the processes (Figure 83 and Table 58). 31.3% (145) respondents have noted that a breeding plan is not relevant to their business, this is normally due to the business not being large enough or the business not having livestock (Figure 83). Although 23.3% (108) of respondents note that they do not see the need to do a breeding plan and 1.1% (5) state that they never thought about doing a breeding plan.

Table 58: Reasons as to why respondents have not carried out a breeding plan.

Reason for not undertaking a breeding plan	Total Respondents	Percentage (Denominator 464)
Cost	38	8.2%
Time	56	12.1%
Lack labour	31	6.7%
I do not see the need to do this	108	23.3%
Carry out actions but not documented	179	38.6%
Not relevant to my business	145	31.3%
Other	67	14.4%

2.11.6 Actions businesses carry out but have not documented

Although the respondents do not have a formal breeding plan, 57.6% (268) regularly breed their own replacements and 44.3% (206) undertake pregnancy scanning of their livestock (Figure 84 and Table 59).

86.7% (403) of respondents have never used sexed semen in livestock production and 86% (400) have never taken the pelvic measure of their cattle. 81.7% (380) of respondents have never breed livestock for lower emissions. 12.9% (60) of respondents do not know enough about breeding livestock for lower emissions. While 8.4% (39) and 7.5% (35) do not know enough about Estimated Breeding Values for stock selection or taking pelvic measure of their cattle respectively (Figure 84).

Table 59: Actions undertaken by respondents but have not documented.

Breeding plan practices - Not documented (Denominator 464)	Regularly	Occasionally	I have never done it	I don't know enough
Semen testing sires	33	81	335	16
	7.1%	17.5%	72.2%	3.4%
Pregnancy scanning	206	70	180	9
	44.4%	15.1%	38.8%	1.9%
Body condition scoring	139	128	186	12
	30.0%	27.6%	40.1%	2.6%
Weight monitoring	108	123	223	11
	23.3%	26.5%	48.1%	2.4%
Breeding for lower emissions	12	13	380	60
	2.6%	2.8%	81.9%	12.9%
Breed own replacements	268	62	125	10
	57.8%	13.4%	26.9%	2.2%
Use Estimated Breeding Values for stock selection	70	81	275	39
	15.1%	17.5%	59.3%	8.4%
Stricter culling regime	138	144	171	12
	29.7%	31.0%	36.9%	2.6%
Breeding for increased growth rate	112	105	227	21
	24.1%	22.6%	48.9%	4.5%
Increasing breeding percentage rates	123	98	219	25
	26.5%	21.1%	47.2%	5.4%
Reducing age at first calving	54	80	304	27
	11.6%	17.2%	65.5%	5.8%
Reducing calving interval	81	70	287	27
	17.5%	15.1%	61.9%	5.8%
Pelvic measure of cattle	12	18	400	35
	2.6%	3.9%	86.2%	7.5%
Using sexed semen in livestock production	13	15	403	34
	2.8%	3.2%	86.9%	7.3%

2.12 Biodiversity

2.12.1 Businesses undertaking a biodiversity audits

Out of the total number of respondents (977), 28.5% (278) have undertaken a biodiversity audit (Figure 85). Reasons as to why businesses have not undertaken a breeding plan can be found in section 2.12.3.

2.12.2 Reasons why businesses have undertaken a biodiversity audit

60.8% (169) of the respondents (278) who have undertaken a biodiversity audit state the reason for doing so was because it was a requirement for a Agri-environment scheme they were taking part in (Figure 86 and Table 60). 55.4% (154) have also noted that they undertook the audit to better assess and understand what biodiversity they have on their business.

In addition, respondents have also noted that they undertook the biodiversity audit out of their own personal interest. Others stated that they did the audit as it was a requirement of the Scottish Quality Crops assurance scheme and/or have land that are parts of Sites of Special Scientific Interest (SSSI) and are audited regularly.

Table 60: Reasons why respondents have undertaken a biodiversity audit.

Reason for biodiversity audit	Total Respondents	Percentage (Denominator 278)
To assess and understand what biodiversity is on the farm	154	55.4%
To identify measures to improve biodiversity	111	39.9%
Requirement for an Agri-environment scheme	169	60.8%
For the buyer(s) of my product(s)	28	10.1%
Other	55	19.8%

2.12.3 Why businesses have not carried out a biodiversity audit

The main reason 55.9% (391) of respondents have not undertaken a biodiversity audit is because they do not know what it involves, 46.1% (322) do not how to do one and 37.9% (265) do not know where to find help if they did wish to conduct an audit (Figure 87 and Table 61). Others have also stated that they had never heard of a biodiversity audit before taking the survey. Some respondents have noted that they do not have the time to conduct a biodiversity audit. Others have mentioned that they visually monitor and do try to encourage biodiversity but do not document their findings.

Table 61: Reasons why respondents have not undertaken a biodiversity audit.

Reasons for not undertaking biodiversity audit	Total Respondents	Percentage (Denominator 699)
I do not know what it involves	391	55.9%
I do not know how to do one	322	46.1%
I do not know where to go to get help to do one	265	37.9%
Cost	206	29.5%
I do not see the need to do this	182	26.0%
Not relevant to my business	116	16.6%
Other	109	15.6%

2.12.4 Reasons businesses would potentially undertake a biodiversity audit in the future

Although 79.4% (573) of respondents (722) have noted that financial assistance and 61.4% (443) of respondents have stated that training in how to undertake a basic biodiversity audit would encourage them to undertake a biodiversity audit (Figure 88 and Table 62). Many respondents commented that unless there was a good reason, a better understanding and a benefit to the business as to why a biodiversity audit should be taken they would continue to resist conducting an audit.

Table 62: Reasons why respondents would potentially undertake a biodiversity audit in the future.

Reasons for undertaking biodiversity audit in future	Total Respondents	Percentage (Denominator 722)
Financial assistance	573	79.4%
Training in how to undertake a basic biodiversity audit	443	61.4%
Technology to record data on site	262	36.3%
Other	100	13.9%

2.12.5 Additional steps to support biodiversity and why undertake them

80% (782) of respondents are taking additional steps to support the creation, enhancement or preservation of suitable habitats on their land (Figure 89).

83.9% (656) of respondents have undertaken additional steps to support the creation, enhancement or preservation of suitable habitats on their land is because they wish to support biodiversity. 30.8% (241) have undertaken these additional tasks due to it being part of an Agri-environment scheme (Figure 90 and Table 63). The majority of the respondents stated that they had a responsibility to support their local biodiversity and they had a genuine interest in biodiversity and wish to improve it as best they could.

Table 63: Reasons why respondents have undertaken additional steps for biodiversity.

Reasons for additional steps for biodiversity	Total Respondents	Percentage (Denominator 782)
To support biodiversity	656	83.9%
Part of an agri-environment scheme	241	30.8%
For the buyer(s) of my product(s)	68	8.7%
Other	160	20.5%

2.12.6 Organic Certification

Only 5.9% (46) of the respondents are certified as organic (Figure 91).

2.12.7 Encouraging biodiversity within farming businesses

Out of the 782 respondents who answered this question, 77.8% (608) of respondents maintain field and water habitat margins on a regular basis. 67% (524) identify and do not alter permanent natural habitats and 56.4% (441) consider wildlife needs when crop/grassland use planning (Figure 92 and Table 64).

57% (446) of respondents have never done training sessions or workshops on local biodiversity issues. While 7.2% (56) do not know enough about what training sessions or workshop are available. Peatland/wetland restoration and preservation does not apply to 63.4% (496) of the respondents as their businesses are not based within these particular types of land forms.

Respondents have also mentioned the use of bird and owl boxes, control of foxes and crows, maintenance of dry stone dykes, tick prevention measures, aerial bracken control and regular shepherding to ensure even grazing of rough pasture.

Table 64: Actions undertaken by respondents to aid biodiversity on their land.

Actions taken to aid biodiversity (Denominator 782)	Regularly	Occasionally	I have never done it	I don't know enough	Not applicable (N/A)
Identify and do not alter permanent natural habitats	524	169	30	24	35
	67.0%	21.6%	3.8%	3.1%	4.5%
Maintain field and water habitat margins	608	110	24	11	29
	77.7%	14.1%	3.1%	1.4%	3.7%
To reduce the use of pesticides or to reduce target areas for pesticide use	441	204	30	3	104
	56.4%	26.1%	3.8%	0.4%	13.3%
Small scale woodland creation	219	259	207	21	76
	28.0%	33.1%	26.5%	2.7%	9.7%
Peatland/wetland preservation	201	146	172	36	227
	25.7%	18.7%	22.0%	4.6%	29.0%
Peatland/wetland restoration	47	69	346	51	269
	6.0%	8.8%	44.2%	6.5%	34.4%
Attend training sessions or workshops on local diversity issues	51	180	446	56	49
	6.5%	23.0%	57.0%	7.2%	6.3%
Leave stubbles or other crop cover in place over winter	295	130	103	12	242
	37.7%	16.6%	13.2%	1.5%	30.9%
Prevent damage resulting from livestock having free access to the water environment	358	199	89	12	124
	45.8%	25.4%	11.4%	1.5%	15.9%
Consider wildlife needs when crop/grassland use planning	392	269	58	16	47
	50.1%	34.4%	7.4%	2.0%	6.0%

2.12.8 Businesses not carrying out additional steps for biodiversity and why?

The main reason respondents (195) have not carried out additional steps to support the creation, enhancement or preservation of suitable habitats on their land is because 52.3% (102) feel that there is not enough information about the topic (Figure 93 and Table 65). 28.2% (55) of respondents have also stated that they are concerned that the measures are too costly. 27.7% (54) feel that the measures may impact production on the holding and 24.6% (48) feel it will have a detrimental impact on the business with the time taken to undertake these measures being a main concern. Others noted they were happy with the biodiversity currently on their land and they saw no need for further modifications to their business as it could upset the already established biodiversity balance which changes itself according to nature, weather and the availability of food and shelter.

Table 65: Reasons why respondents have not undertaken additional steps for biodiversity.

Reasons for not undertaking additional steps for biodiversity	Total Respondents	Percentage (Denominator 195)
I need more advice to know what to do	102	52.3%
Concerned these measures are detrimental to my business	44	22.6%
Concern of the impact on production	54	27.7%
Too costly	55	28.2%
I do not see the need to do this	48	24.6%
Not relevant to my business	27	13.8%
Other	21	10.8%

2.12.9 Why businesses potential would undertake additional steps for biodiversity

Of the 195 respondents who have not carried out additional steps to support the creation, enhancement or preservation of suitable habitats on their land, 83.6% (163) stated that financial assistance would encourage them while 65.1% (127) noted the need for free or low cost advice (Figure 94 and Table 66). Respondents also noted that if there were no competitive schemes, that the schemes were equally accessible they would be encouraged to practice more methods to support the creation, enhancement or preservation of suitable habitats on their land. Another respondent noted that if there was evidence that measures could help their business, they would also be encouraged to further enhance the biodiversity within their business.

Table 66: Reasons why respondents would potentially undertake further actions for biodiversity in the future.

Reasons for undertaking additional biodiversity activities in future	Total Respondents	Percentage (Denominator 195)
Financial assistance	163	83.6%
Free or low cost advice	127	65.1%
Help with the application process for schemes	104	53.3%
Other	15	7.7%

2.13 Communication Channels

60.3% (589) of the respondents when looking for information on new agricultural practices would review Farming press articles. 60.1% (587) would have ad-hoc discussions with other farmers/crofters/land managers (Figure 95 and Table 67).

50.4% (492) of respondents went to official government websites for advice (Figure 95). Respondents did note that they sometimes found these sites difficult to work through and perceived the language used as ‘legal talk’ rather than ‘plain talk’. Websites that respondents found useful included the Farming Forum, Game and Wildlife Conservation Trust (GWCT), SAC, Farming Advice Service (FAS), Bee Base, NatureScot, RSPB, Wildlife Trust Scotland, Woodland Trust, Bird Track, Working for Waders, Scottish Bee Keepers Association.

Table 67: Agricultural information sources for respondents.

Communication channels	Total Respondents	Percentage (Denominator 977)
Official Government Websites	492	50.4%
Farm Advisor	462	47.3%
Social Media Platforms (Facebook, Twitter, Instagram etc.)	343	35.1%
Ad-hoc discussions with other farmers/crofters/land managers	587	60.1%
Meet-ups, e.g. monitor farm meetings, discussion groups etc.	396	40.5%
Farming Advisory Service	435	44.5%
Farming Press	589	60.3%
Product Representative	175	17.9%
Vet	479	49.0%
Online	151	15.5%
Other	101	10.3%