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Learning Conservation Agriculture the Innovation Systems way - - PowerPoint PPT Presentation
Learning Conservation Agriculture the Innovation Systems way - - PowerPoint PPT Presentation
Grain-SA Smallholder Farmer Innovation Programme Erna Kruger, Ngcobo P, Dlamini M and Smith H Learning Conservation Agriculture the Innovation Systems way CA-Farmer Innovation Programme Key objectives and activities Stakeholder interaction,
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CA Farmer led Trial summaries Midlands Bergville EC, SKZN Season 2017 2013 2014 2015 2016 2017 2013 2014 2015 2016 2017 No of villages 6 3 9 11 17 18 4 10 8 8 13 No of trial participants 42 28 83 73 212 259 23 16 43 54 93 Area planted (trials) - ha 1,36 2,8 7,2 5,9 13,5 17,4 0,36 0,3 0,37 1,18 3,58 Average yield maize (t/ha) 2,04 3,74 3,63 4,12 5,03 5,7 0,95 0,7 1,37 2,52 2,17 Min and max yield maize (t/ha)
0,4-7,1 2-4,3 1-6,7 0,6-7,4 0,3-11,7 0,5-12,2 0,3-1,7 0,3-1,8 0,5-4,4 1,1-5,2 0,2-6,7
Average yield beans (t/ha) 0,62 1,24 0,26 0,79 1,05 1,22 1,26 0,34 0,69 1,28 0,35
Trial summaries over 5 seasons; Bergville,SKZN and EC
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- For CA plots the pH is higher
- n average and acid
saturation lower than on control plots
- The required P has reduced
- n CA plots
- And % Org C and % N
increased significantly compared to control plots
- Savings of around R400/ha
made on inorganic N in three seasons
- C:N ratios in the soil
decrease over time for the CA plots
- Soil health scores are higher
for CA plots than control plots
The CA system and effect on soil fertility and soil health
Intercropping with legumes (beans and cowpeas) and use
- f cover crops
increase soil fertility and soil health FASTER than monocropping Increased % Organic C and % N under CA
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- Visual and quantitative indicators
- Visual Soil Assessments: soil cover, soil
structure, run-off, crusting, earthworms, root size, soil porosity, soil texture
- Measurements: infiltration, run-off
plots, weather stations
- Soil health analysis
Soil health; methods
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- Colour and texture –
more an indicator of soil type – so doesn’t change too much with tillage options
- Soil depth- no
distinction between CA and Conv – how to measure?
- Soil cover- ? Which
version?
- Infiltration – how to
measure
May-18 Visual soil Indicators Stulwane Eqeleni Ezibomvini NAME OF PARTICIPANT K Dladla(T) K Dladla(C) D Hlongwane(T) D Hlongwane(C) T Dlamini (T) T Dlamini (C) M Dladla(T) M Dladla(C) C Buthelezi(T) C Buthelezi(C) P Sthebe(T) P Sthebe(C) ThZikode (T) ThZikode (C) T Zikode (T) T Zikode (C) T Mabaso (T) T Mabaso (C) N Zikode (T) N Zikode (C) S Hlatshwayo (T) S Hlatshwayo (C) C Hlongwane (T) C Hlongwane (C) P Hlongwane (T) P Hlongwane (C) SOIL TEXTURE (X3) 6 6 6 6 6 6 6 3 6 6 3 6 3 6 3 6 3 3 3 3 3 3 6 6 6 3 SOIL STRUCTURE( AGGR) (x3) 6 6 6 6 6 3 6 3 6 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 SOIL POROSITY (x3) 6 3 3 3 6 3 6 0 3 3 3 3 6 6 3 3 3 6 3 3 3 3 3 6 3 SOIL COLOUR (x2) 2 2 2 2 2 2 4 4 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 4 2
- NO. OF SOIL MOTTLES AND
COLOUR (x1) 1 1 1 1 1 1 2 2 2 1 1 1 1 1 1 1 1 0 0 1 2 1 1 1 EARTHWORM COUNTS (x2) 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 SOIL COVER (RESIDUE) (x2) 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 1 SOIL DEPTH( CM) (x2) 4 4 4 4 4 4 2 4 4 4 4 4 4 4 4 4 4 2 2 2 2 4 2 2 2 2 RUN-OFF (x2) 4 4 0 2 2 4 0 0 2 2 2 2 2 2 2 4 2 2 2 2 2 2 2 2 INFILTRATION (x2) 4 4 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 TOTALS 33 30 2 4 26 31 25 28 18 27 23 20 23 23 26 20 2520 20 17 15 18 18 19 21 27 17
VSAs
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- Should be >30%
- 15-30% still considered CA
- <15% a problem BUT little cover in
- ur system – we want to assess
increase in cover –
- Cannot assess this before spraying
– complicates things too much
- During season: IMPORTANT THT
WEEDING DOES NOT REMOVE COVER
- Option 3: A range of different
percentages with more categories to be more specific:
- 0 =0-15% cover
- 1=16-30% cover
- 2=31-45% cover
- 3=46-60% cover
- 4= 61-90% cover
- 5= > 90% cover
Soil cover
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- When in the season
should we look at soil cover?
- How to relate that to
canopy cover?
Soil cover
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Soils
O,1,2 CONTROL (CA yes or no) TRIAL Soil colour (light, ave, dark) (uniformity- specks)– (x3) Soil structure (aggregates) – (x4) Porosity (Clods, pores, organic matter)- (x5) Soil surface (run-off, texture, crusting) – (x3) Soil cover: 0-15%; 15-30%, >30% (x3)
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Bulk density
Bulk k Densit sity y - VS VSA
In the pit wall; using a pocket knife
- Knife easily pushed in, soil
disintegrates; 1.4-1.6g/cm3 (2)
- Knife pushed in for about half the
length of the blade (1,6-1,8g/cm3 (1)
- Only knife tip can be pushed in
>2g/cm3 (0)
- So, is it worth doing the VSA
version??? How difficult is the lab version
- When should the sample be taken?
Village Period undue CA (yrs) Name and Surname Control CT Control CA M M+B M+CP SCC Average Ezibomvini 4 Phumelele Hlongwane 1,30 1,36 1,38 1,33 1,38 1,28 1,34 Eqeleni 5 Ntombakhe Zikode 1,35 1,49 1,37 1,32 1,38 Thamela 1 Mkhuliseni Zwane 1,14 1,08 1,09 1,07 1,10 Average bulk density 1,27
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Rainfall data
Averages for Ezibomvini, Eqeleni, Stulwane, Thamela and Ndunwana Dec Jan Feb March April May Monthly rainfall (mm) 185 72,25 169,2 114,7 17 5 Monthly rainfall – weather station 92,8 93,2 89,6 148,8 24,8 5,2 Monthly rainfall Ezibomvini 29,5 94 11,2 114,7 17 Mean (mm) per rainfall event 7,9 5,8 8,2 7,6 2,1 0,4 Max (mm) per rainfall event 60 30 30 20 1 3,5
- Generally the rain gauge data has under- estimated the rainfall for
each month.
- There are reasonably significant differences between the villages- but
we don’t know whether it is real or due to haphazard recording
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Run-off data
- Run-off data for Phumelele only and only for two months…
- % conversion should be per rainfall event but these were not
correlated.
- Nthombakhe’s run-off plots only recorded for 1 week at end Feb…
Rainfall records Run-off plots litres Date Maize+Beans Maize only Maize+CP Summer CC Control Feb-18 169 35,61 18,53 37,05 35 57,59 Mar-18 114,7 7,5 1,52 8,9 7,7 23,32 Rainfall records Percentage rain converted to runoff Feb-18 169 21% 11% 22% 21% 34% Mar-18 114,7 7% 1% 8% 7% 20%
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Infiltration
- Infiltration in CA trials
higher for 5 of 11 participants
- Unclear whether
controls are also CA (and CA how – mono- cropped?)
- Difficult to say
anything
- Continue? And if so
how? – double ring, single ring???
Village Name and Surname Yrs under CA infiltration rate (mm/hr) control infiltration rate (mm/hr) trial Stulwane Khulekani Dladla 5 587,4 531,4 Dlezakhe Hlongwane 5 226,2 423,8 Thulani Dlamini 5 422,7 450,0 Makhethi Dladla 5 226,6 587,4 Pasazile Sithebe 5 544,4 478,3 Cuphile Buthelezi 5 429,2 637,7 Ezibomvini Phumelele Hlongwane 4 455,5 282,5 Cabangile Hlongwane 3 183,0 133,9 Eqeleni Tholwephi Mabaso 5 218,8 250,8 Tombi Zikode 5 618,1 177,1 Smephi Hlatshwayo 5 434,8 218,8
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- WEOC – sugars from root exudates,
plus organic matter degradation
- CO2 – microbial activity/respiration
- WEON –Atmospheric N2 sequestration
from free living N fixers, plus SOM degradation
- C/N – Balance between WEOC and
WEON
- MAC% - efficiency of cycling of WEOC
(WEOC/CO2-C)
Soil health(SH) scores
CO2/10+WEOC/50 +WEON/10 =SH score Joining soil science and ecology into a new science of soil health
- Developed by Rick Haney – to
accommodate for and include the
- rganic fractions of nutrients in soil
sample analysis
- Recognising that soil health is a
dynamic process of cycling of nutrients, microbial activity and degradation of
- rganic matter
- And the plant roots are active
participants in the cycling providing carbon sugars as root exudates to supply microbes with food
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- C:N ratio is determined by soil chemical
properties and micro organisms present in the soil.
- The lower this ratio is, the more organisms
are active and the more available the food is to the plants. Good C:N ratios for plant growth are <15:1.
- You can have a low or optimum C:N
(WEOC/WEON) within a range of values of available organic carbon in the soil. (WEOC)
- If this value is low, it will reflect in the C02
evolution, which will also be low. So less
- rganic carbon means less respiration from
microorganisms, but again this relationship is unlikely to be linear.
- The Microbially Active Carbon (MAC = WEOC
/ ppm CO2) content is an expression of this
- relationship. If the percentage MAC is low, it
means that nutrient cycling will also be low. One needs a %MAC of at least 20% for efficient nutrient cycling.
- The SH score ranges between 0-50. the scale
is generally 0-3; 3-7; 7-15; 15-25; 25-50
Test results ppmCO2-C N-Mineralisation Potential Biomass >100 High-N potential soil. Likely sufficient N for most crops Soil very well supplied with organic
- matter. Biomass>2500ppm
61-100 Moderately-high. This soil has limited need for supplemental N Ideal state of biological activity and adequate organic matter 31-60
- Moderate. Supplemental N
required Requires new applications of stable
- rganic matter. Biomass<1,200ppm
6-30 Moderate-low. Will not provide sufficient N for most crops Low in organic structure and microbial
- activity. Biomass<500ppm
0-5 Little biological activity; requires significant fertilization Very inactive soil. Biomass<100ppm. Consider long-term care
What the values mean
CONVENTIONAL SYSTEM: Mostly decomposer fungi – small hyphal networks, NB for soil fertility, minor role in carbon storage CA SYTEM: Mostly Mycorrhizal fungi – large hyphal networks, major role in carbon storage Mycorrhizal fungi get their energy in a liquid form, as soluble carbon directly from actively growing plants. They access and transport water - plus nutrients such as phosphorus, nitrogen and zinc - in exchange for carbon from plants. Soluble carbon is also channelled into soil aggregates via the hyphae of mycorrhizal fungi and can undergo humification, a process in which simple sugars are made up into highly complex carbon polymers. Below: Mycorrhizal fungi grow very closely associated with plant roots and create networks of filaments (hyphae) within the soil)
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Reserve Organic, 0 Release from Orga, 19.40 NO3, 1.10 NH4, 10.40 Total Inorganic, 11.5
Distribution of the Nitrogen components ppm
Reserve Organic, 7.4 Release from Orga, 1.00 NO3, 83.20 NH4, 2.80 Total Inorganic, 86
Distribution of the Nitrogen components ppm
BIOLOGICAL ANALYSES Sample # SOLVITA CO2 Burst WATER EXTRACT C/N Soil Health Calculatio n (Index) Commen t CO2 - C, ppm C Organic C ppm C Organic N ppm N ENZV 206.1 379 19.4 19.5 24.2 Excellent BIOLOGICAL ANALYSES Sample # SOLVITA CO2 Burst WATER EXTRACT C/N Soil Health Calculatio n (Index) Commen t CO2 - C, ppm C Organic C ppm C Organic N ppm N 7.1 129 8.4 15.4 2.6 Soil Organic Matter % 6.2 Microbial Active C (MAC) % 54.4 Soil Organic Matter % 1.3 Microbial Active C (MAC) % 5.5
Comparing the nitrogen profile of natural “veld” with an intensively chemically farmed plot.
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Comparing the nitrogen profile of natural “veld” with CA diverse cropped plot; Bergville, 2016/17.
BIOLOGICAL ANALYSES Sample # SOLVITA CO2 Burst WATER EXTRACT C/N Soil Health Calculatio n (Index) Commen t CO2 - C, ppm C Organic C ppm C Organic N ppm N EPHV 81,6 326 18,4 17,7 16,5 Excellent
Reserve Organic, 0 Release from Orga, 18.40 NO3, 0.30 NH4, 2.70 Total Inorganic, 3
Distribution of the Nitrogen components ppm: Veld (P Hlongwane)
Soil Organic Matter % 4 Microbial Active C (MAC) % 25
Reserve Organic, 4.2 Release from Orga, 21.20 NO3, 12.90 NH4, 4.30 Total Inorganic, 17.2
Distribution of the Nitrogen components ppm; Maize + Cowpea intercrop (P Hlongwane)
BIOLOGICAL ANALYSES Sample # SOLVITA CO2 Burst WATER EXTRACT C/N Soil Health Calculatio n (Index) Commen t CO2 - C, ppm C Organic C ppm C Organic N ppm N EPHMCP 61,8 296 25,4 11,7 14,6 Excellent Soil Organic Matter % 3,3 Microbial Active C (MAC) % 20,9
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Comparing the nitrogen profile of Mono-cropped Maize with CA diverse cropped plot; Bergville, 2016/17.
Reserve Organic, 4.2 Release from Orga, 21.20 NO3, 12.90 NH4, 4.30 Total Inorganic, 17.2
Distribution of the Nitrogen components ppm; Maize + Cowpea intercrop (P Hlongwane)
BIOLOGICAL ANALYSES Sample # SOLVITA CO2 Burst WATER EXTRACT C/N Soil Health Calculatio n (Index) Commen t CO2 - C, ppm C Organic C ppm C Organic N ppm N EPHMCP 61,8 296 25,4 11,7 14,6 Excellent Soil Organic Matter % 3,3 Microbial Active C (MAC) % 20,9
Reserve Organic, 1.5 Release from Orga, 21.70 NO3, 16.10 NH4, 2.30 Total Inorganic, 18.4
Distribution of the Nitrogen components ppm; CA Maize control (P Hlongwane)
BIOLOGICAL ANALYSES Sample # SOLVITA CO2 Burst WATER EXTRACT C/N Soil Health Calculatio n (Index) Comme nt CO2 - C, ppm C Organic C ppm C Organic N ppm N EPHC 59,6 254 23,2 10,9 13,4 Excellent Soil Organic Matter % 3 Microbial Active C (MAC) % 23,5
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- 4-5 years: Reduced need for herbicide - no spraying on trial
plots this season
- Increased organic matter, reduced fertilizer requirements -
No basal fertilizer applied- only top dressing
- Reduced runoff
- Increased yields and diversity
Bergville: Case study
Mphumelele Hlongwane- Ezibomvini
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t/ha 2016 2017 Maize (Control)-CA 7,8 9,7 Maize Trial CA - combined 6,93 8,3 Beans 0,25 1,81 Sunflower 0,3 0,8
- EXPERIMENTS: Inter- cropping, crop
rotation, legumes, SCC, WCC
- Runoff plots: CA (1,1mm/event) vs
Conventional control (3,1mm/event)
- Infiltration: CA (247mm/hr) vs Control
(50mm/hr)
- Soil health 2016, 2017:
- Build-up of organic soil carbon and nitrogen in
the trial, with more microbially available carbon and thus a much higher soil health score.
- Lower C:N ratios in CA plots (CCs and legumes
- AGGREGATE STABILITY: CA (43%-55%) CA
Control (33%) - higher aggregate stability for the plots with crop diversification- highest for inclusion of SCC mixes and Lab-Lab
- % OM: CA average (3 ,47%), Veld Baseline
(2,5%) – accumulation of organic matter in CA plots- now higher than veld baseline benchmark
(10) M + B (5) LL Control plot (8) M + B (6) M +LL (3) M + SCC +WCC Contro l plot (9) M + CP (7) M + CP (4) M + B (2)Sunn hemp, millet and sunflower (1) M + B Legend: M – Maize; B – Beans; CP – Cowpea; LL – Lab Lab; SCC – summer cover crop WCC – winter cover crop
Bergville: Case study-continued
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4 Participants over 3 seasons- crop diversity (intercropping and cover crops) and crop rotation to a lesser extent. AVERAGE FOR ALL TRIAL PLOTS SHOWN
- The Organic Carbon content
has INCREASED for all 4 participants
- The Organic Nitrogen content
has INCREASED for all 4 participants
- C:N ratios have decreased for
Phumelele Hlongwane only – as she has most coherently implemented the diverse cropping and crop rotation process (including legumes).
- Soil health scores have
increased significantly between 2016 to 2017
Soil health Test results: 3 seasons 2015-2017
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Average values of different cropping
- ptions across three
seasons for 9 participants
- If one compares
single crops (maize
- nly) to the mixed
crop options (intercrops and cover crops) then
- Organic Carbon and
Organic Nitrogen are HIGHER
- C:N ratios are LOWER
- Soil health scores are
HIGHER for all the mixed cropping options - except for maize and bean intercrop option
Soil health Test results: Different Cropping options 2015-2017
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- 3-4 years: Animal drawn traction – larger plot – very sandy
, extremely low organic matter (0,6%).
- Germination, growth and yields have increased – albeit
slowly; Maize 0,78-1,4t/ha, beans stable at 0,16t/ha
- Increased diversity – legumes and cover crops
- Reduced run-off and erosion
- Reduced weeds
- Increased soil health
Eastern Cape: Matatiele Case study
Tsoloane Mapheele– Khutsong- Matatiele
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- EXPERIMENTS: single crops, Inter- cropping,
legumes, SCC, WCC, Lucerne
- Soil health 2016-2017:
- Reduction in C:N ratio and increase in organic N in his intercropped
trial plots as compared to his Maize only control plot, indicating an increase in soil health.
- Soil health scores for the trial plots are higher than the control
plots, but still below average given the extremely sandy and infertile soils he is working on.
Case study continued
Cont (M) Trial veld Trial 2016 2017 Average of %OM 0.6 0.7 1 0.6 Average of CO2 - C, ppm C 16.8 14.6 19.2 14.6 Average of Organic C ppm C 118 116 145 73 Average of Organic N ppm N 7.5 8.5 12.4 12.1 Average of C:N ratio 15.7 13.6 11.7 6.0 Average of Soil health Calculation 3.0 3.1 4.3 4.0 20 40 60 80 100 120 140 160 Indicators
Soil Health Indicators Tsoalone Mapheele; 2016-2017
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- In Matatiele (EC) soils are generally poor and veld
benchmark values tend to be lower than the CA trial values
- The increase in available nitrogen (2016-2017)
amounts to an average Rand value of about R150 more than the veld samples. This indicates a potential saving on bought fertilizer of around 14%
- In addition Immediate release N has increased
substantially over the veld bench mark values and is higher for 2017; indicating a cropping pattern under the CA trials that builds organic nitrogen in the soil.
- In Bergville the picture is a bit different. Soils are
good and veld benchmarks are high – excellent
- Here only the trials in Ezibomvini have higher total
Nitrogen amounts than the veld. The Rand value of available organic N here is R64 more than the veld benchmark, indicating a potential saving on bought fertilizer of around 6%.
Nutrient cycling- Nitrogen; Comparison EC and Bgvl
2016 2017 2016 2016 2017 2016 2016 2017 2016 Trial Veld Trial Veld Trial Veld Khutsong Nkau Sehutlong Average of N(kg/ha) Total 215 84 151 308 422 280 325 378 280 Average of R value of Org N 103 243 175 263 353 129 162 243 84 Average of N Immediate release 6 22 10 16 31 8 10 22 5 50 100 150 200 250 300 350 400 450
Matatiele; Nitrogen 2016- 2017
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- Intercropping and use of
cover crops is very important for building soil fertility and soil health
- Crop rotation aids in
stabilising high soil health scores over time
- The more crops you use
and rotate the better
- Having legumes in the mix