The BHU Future Farming Centre

Information - Crop Management - Production

Grape Cultivar / Variety Genetic Library

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national-vine-collection

Photo credit Bernard Newman

The BHU is hosts a grape cultivar / variety genetic library.  

The genetic library was established in 2010, and holds 600 selections ranging from vinifera and hybrids to table-grapes, labrusca types, and rootstocks.  Some selections are of the same variety, but herald from different locations, and therefore may have slightly different characteristics.   

The vineyard is also the demonstration site of a range of non- tanalised / copper chromium arsenate (CCA) treated posts

For more information please email This email address is being protected from spambots. You need JavaScript enabled to view it. from the BHU / FFC.

The BHU Future Farming Centre

Information - Crop Management - Production

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Linseed Stripper Simulation Trial

Introduction

In order to gain some information and experience in harvesting decisions when using a stripper on linseed in New Zealand the Biological Husbandry Unit (BHU) was asked to simulate the use of a stripper on the New Zealand linseed cultivar ‘Hinau’. 

Materials and Methods

5 replicates of a single sowing rate (60kg/ha rows 0.10m apart) of the linseed cultivar ‘Hinau’ (tsw 4.72g) was sown on 23 December 2003 using a cone seeder.  The area sown was in spring wheat the previous season and had not had any fertiliser inputs since then.

Crop progress was monitored and a photographic record kept.  Harvesting began when one of the plots showed some browning of the stem immediately below the boll.  This occurred on 16 April 2004.  The area harvested was a 0.200m length of row from five rows giving a total harvested area of 0.10m2.  Plant stems were counted for each of the rows harvested within the harvest area.  Ten stems had individual bolls scored for maturity and bird/insect damage.  Bolls were then manually stripper from stems using a kitchen fork.

The weight of the stripped material was recorded and the material the oven dried until ‘crisp’ at 40°C.  Dry weights were recorded and the seed manually threshed and dressed for each plot.  Yield from each plot/harvest event was weighed and kept for future oil yield and quality assessment.

Results

Change in drymatter content over time

The first harvest was undertaken on 16 April 2004, 115 days after sowing.  As the harvests progressed with increasing crop maturity over the following month the dry matter content (DM) of the manually stripped material increased steadily.  The final harvest event had a higher moisture content (i.e. a lower %DM) than the previous harvest, probably due to recent rain (this event occurred sooner after rain than was desirable due to a forecast for further rain the following day).

The changes in %DM over time are shown for the 5 plots and the mean of these in Figure 1, below.

Figure 1:          Changes in %DM stripper simulated material with sequential harvesting of the linseed cultivar ‘Hinau’.

 image002

From the perspective the least amount of moisture (i.e. highest %DM) in the stripped material the dates of 7 and 10 May were optimum (136 and 139 days after sowing). 

Yield of seed

While the seed yield varied quite widely between plots within sample harvest events and within plots between sample harvesting events, seed yield was remarkably consistent at around 20g per 0.1m2 or 2T per hectare.  This is illustrated in Figure 2, below

Figure 2           Yield of dry linseed from each sampling event

 image004

Seed yield as a % of fresh weight of material stripped

As can be seen from Figure 3 the maximum % of the fresh weight (FW) achieved by any plot was approximately 55%, while the average for the maximum %DW time line (7 and 10 May) was between 40 and 50%.  This has implications for the harvesting, drying, dressing and storing logistics for this stripped linseed which will be different to those for the windrowed and headed linseed.

Figure 3           Linseed seed dry weight as a % of the material harvested during the linseed stripper simulation

image006

Changes in visual cues to crop maturity over time

Figure 4 shows the changes in the % of each of four categories that bolls were placed in to rank the maturity of the crop.

Figure 4           The % of bolls ranked as green, yellow, brown or damaged for some of the sampling events during the linseed stripper simulation.

 image008

This graph has a corresponding set of digital prints for visual comparisons

Discussion

The visual cues, the water content of the ‘harvested’ material and the seed % of ‘harvested’ material all concur with the optimal harvest date being on or about 07/05/04.  harvesting sooner than this has implications for transport, drying and dressing seed.

With the inclusion of information on oil yield and oil quality another layer of information will be available for harvest timing decision support.

Conclusions

While it is not possible come to definitive conclusions regarding when to harvest with a stripper, valuable lessons have been learned to support the decision making process.

The BHU Future Farming Centre

Information - Crop Management - Production

Corn, Bean, Squash Intercrop Experiment, 2002-03

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Background

Beans, Maize and Squash are frequently planted together as part of an intercropping system in the highland subtropics of Central America.  This apparently has several advantages, particularly for the maize, which performs as well as or better than it does alone. 

Choice of varieties is very important for this type of experiment.  In Mexico where this practice was established the combination is between specific varieties of corn beans and squash. 

Results from a famous experiment near Tabasco in Mexico are presented in Table 1 below

TABLE 1: Yields and Total Biomass of Maize, Beans, and Squash (kg/ha) in Polyculture as Compared with Several Densities (plants/ha) of each crop in monoculture (from Gliessman l998)

Crop

Monoculture

Polyculture

Maize

 

 

 

 

 

Density

33,000

40,000

66,600

100,000

50,000

Yield

990

1,150

1,230

1,170

1,720

Biomass

2,823

3,119

4,487

4,871

5,927

Beans

 

 

 

 

 

Density

56,800

64,000

100,000

133,200

40,000

Yield

425

740

610

695

110

Biomass

853

895

843

1,390

253

Squash

 

 

 

 

 

Density

1,200

1,875

7500

30,000

3,330

Yield

15

215

430

225

80

Biomass

241

841

1,254

802

478

Total polyculture yield

 

 

1,910

Total polyculture biomass

 

 

6,659

There are several approaches to analysing the relationships and relative yield within these intercropping systems.  Here we will look at the treatments outlined in the table below;

Maize

100%

(flour)

Blue Hopi

1

Beans

100%

(dry)

Pinto

2

Squash

100%

(non running)

Sweet Mama

3

 

 

 

 

 

Maize bean squash

100%

 

 

4

Maize bean squash

75%

 

 

5

Maize bean squash

50%

 

 

6

Three replicates were made of each of the six treatments

 

100%

75%

50%

 

Inrow

Interow

Density(plants/m2)

Inrow

Interow

Density(plants/m2)

Inrow

Interow

Density(plants/m2)

corn

0.3

0.45

7.41

0.4

0.45

5.56

0.6

0.45

3.70

beans

0.15

0.45

14.8

0.2

0.45

11.1

0.3

0.45

7.41

squash

0.45

0.45

4.94

0.6

0.45

3.70

0.9

0.45

2.47

Crops were planted on a grid where the rows of corn, beans and squash were 0.15m offset from each other to minimise early competition between species.

Due to season length and low germination considerations the maize corn was grown as cell transplants, while the squash and beans being short season plants were direct seeded.  None of the plots were weeded so the yield effects of weed suppression could be expressed.

Results

Unfortunately each of the treatments was highly variable between reps.  This meant little opportunity to separate the means but also gave the polycultures a greater opportunity to compensate where one crop did poorly.

 Direct relative yield results are illustrated in the table below.

Cropping System

Squash

Bean

Corn

% relative yield

 

Monocrop Maize

 

 

100%

100%

b

Monocrop Beans

 

100%

 

100%

b

Monocrop Squash

100%

 

 

100%

b

Polyculture 100%

61%

19%

90%

170%

a

Polyculture 75%

59%

19%

94%

172%

a

Polyculture 50%

57%

21%

70%

148%

a

The Mexican experience had a cumulative relative yield or land efficiency ratio (LER) of 1.73 for this cropping combination when compared to optimal planting densities.  Other subsistence farming intercrop combinations have shown results of up to 2.82 with recently designed combinations (Altieri 2002)

BHU

monoculture

polyculture

Maize

100%

100%

75%

50%

Density

74074

74074

55556

37037

Yield

4389

3963

4111

3062

%CV

31%

Beans

Density

148148

148148

111111

74074

Yield

3498

1244

1279

1399

%CV

32%

Squash

Density

49383

49383

37037

24691

Yield

36214

22016

21193

20576

%CV

23%

Total polyculture yield

27223

26583

25037

%CV

15%

5%

20%

Yield stability was higher with the polycultures as opposed to the monocultures as can be seen by the coefficient of variation (%CV).  A lower %CV means less variation relative to the yield, so polyculture crops had a LER that varied by 5 – 20% while monoculture crops varied by 23 – 32%.

Similar intercrops have been used on European organic farms to produce cereal legume stock feed mixes e.g. oats and peas (Lampkin 1990).  There is potential for the use of this type of system to produce food directly for humans as well.

One of the additional advantages of the corn-bean-squash intercrop system is the additional biomass produced (Gliessman, 1998).  The additional biomass produced has the potential for stock food or for ‘feeding’ the soil.  Unfortunately, biomass production was not examined in this experiment.

Conclusion

Polycultures have the potential to increase yields and sustainability in many parts of the world.  This type of system could be designed to fit the New Zealand context. 

References

Alteri, M. A. 2002.

Gliessman, S.R. 1998. Agroecology: ecological process in sustainable agriculture. Ann Arbor Press, Michigan.

Lampkin N, 1990.  Organic Farming. Farming Press Books, Ipswich.

The BHU Future Farming Centre

Information - Crop Mangement - Production

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Golden Linseed Trial 2003-2004

Introduction

In order to avoid the risk associated with growing a single cultivar of linseed (‘Hinau’) for processing in Canterbury and Nth Otago, three ‘golden’ linseed varieties were assessed for agronomic characteristics and yield late in the 2003/04 growing season at the Biological Husbandry Unit (BHU) Lincoln University, New Zealand.

Materials and Methods

Five replicates of three sowing rates (30, 60 and 90 kg/ha, 14 rows at 0.10m row spacings) of four linseed cultivars were sown in 5m long plots on 23 December 2003 using a cone seeder in this fully factorial experiment.  The area sown was in spring wheat the previous season and had not had any fertiliser inputs since then.

Cultivars sown were as follows in the table below;

Cultivar

TSW

Seed colour

Notes

‘Hinau’

4.72g

Brown

NZ standard cv

Nugget

5.57g

Yellow

New to NZ

Unknown (Chantelle)

4.58g

Yellow

New to NZ

Unknown (Dakota)

5.59g

Yellow

New to NZ

Crop progress was monitored at approximately weekly intervals with flower period recorded and a photographic record kept.  Harvesting occurred as each plot matured.  This began on 19 April 2004.  The area harvested was a 1.25m length of row from eight rows giving a total harvested area of 1.0m2.  Whole aerial plants were harvested and dried over a 2 week period before mechanical threshing.

Results

Flowering

The date of flowering varied between different cultivars as did the flowering period.

start

30

60

90

All

Chantelle

62.0

62.0

62.0

62.0

c

Dakota

49.0

49.0

49.0

49.0

a

Hinau

59.6

62.0

60.8

60.8

b

Nugget

60.8

60.8

60.8

60.8

b

All

57.9

58.5

58.2


finish

30

60

90

All

Chantelle

86.0

87.4

88.8

87.4

c

Dakota

73.4

72.0

72.0

72.5

a

Hinau

86.0

86.0

93.0

88.3

c

Nugget

84.6

83.2

81.8

83.2

b

All

82.5

82.2

83.9

length

30

60

90

All

Chantelle

24.0

25.4

26.8

25.4

bc

Dakota

24.4

23.0

23.0

23.5

ab

Hinau

26.4

24.0

32.2

27.5

c

Nugget

23.8

22.4

21.0

22.4

a

All

24.7

23.7

25.8

In checking for correlations between yield and other agronomic factors it was found that yield was very closely correlated with the date that the treatment finished flowering.  The figure below illustrates this.  It should be noted that 5 replicates went into each of the data points on the graph.

The equation for the pink fitted regression line is;

“yield (g/m2)” = 586 – 4.79 x “mean flower finish day after planting”

where;

“mean flower finish day after planting” is the mean per treatment of the days after planting that greater that < 5% of plants were still flowering.

The adjusted R2 of this regression line is 79.8%, so this is a potential source of yield variation during this shoulder season period.

Harvest Date

The ranking of the cultivars in terms of harvest date is shown below.

Cultivar

Days after sowing

Harvest date

Dakota

118

19/04/2004

Nugget

127

28/04/2004

Hinau

139

10/05/2004

Chantelle

147

18/05/2004

Yield

Yield varied markedly between cultivars as illustrated in the table below.

yield g/m^2

30

60

90

All

Chantelle

181.88

160.64

185.26

175.93

bc

Dakota

238.62

247.1

234.91

240.21

a

Hinau

177.42

142.7

138.8

152.97

c

Nugget

196.67

167.83

209.34

191.28

b

All

198.65

179.57

192.08

In terms of seed yield per seed planted the following relationship was observed.

seed/seed

30

60

90

All

LDS

Chantelle

60.8

26.6

20.6

36

bc

Dakota

79.4

41.2

26.2

48.9

a

Hinau

59.2

23.6

15.2

32.7

c

Nugget

65.6

27.8

23.2

38.9

b

All

66.25

29.8

21.3

LSD

a

b

c

It may be more meaningful to look at this relationship graphically in terms of the actual density of sowing as illustrated below.

 image004

Discussion

Dakota was the best performing linseed cultivar of the four trialled in the experiment.  This was probably due to the short growing season available due to late planting.  This hypothesis is supported by a tight relationship between last date of observed flowering and the yield (g/m2).

The ‘lack’ of effect from density is likely to be because the environment was the key factor limiting production.  It should be noted that density appeared to have a greater effect with the shorter season cultivars, although this could be confounded by the larger size of the seed of the shorter season cultivars.

The lower yield observed with later flowering may be due to a temperature effect on pollination, ovary survival or seed development.  None of these were investigated.

Conclusion

Dakota is an effective linseed cultivar agronomically for late season golden linseed production.  Dakota may also be effective for early season planting and drought avoidance.  These factors both have implications for continuity of supply to the manufacturer/processor.