INVESTIGATION OF THE POTENTIAL FOR FORAGE SPECIES TO ENHANCE THE SUSTAINABILITY OF DEGRADED RANGELAND AND CROPLAND SOILS
THESIS
Presented in Partial Fulfillment of the Requirements for the Degree Master of Science in the Graduate School of The Ohio State University
By
Boniphace Mokiri Nkombe, B.S.
Graduate Program in Horticulture and Crop Science
The Ohio State University
2016
Master's Examination Committee:
Professor David J. Barker, Advisor
Professor Ephraim J. Mtengeti
Professor R. Mark. Sulc
Professor Brian K. Slater
Copyrighted by
Boniphace Mokiri Nkombe
2016
ABSTRACT
Soil degradation is among the most important issues that threaten the sustainability of the world’s agriculture, and its effects can be seen in all continents including America and
Africa. The first objective of research in Chapters 3 (Ohio) and 4 (Tanzania) was to evaluate the effect of various forage cover crop species under varying levels of fertilizer treatment on forage production (yield) and stand density. The second objective was to determine the effect of the same vegetation and fertilizer treatments on water infiltration and soil penetration resistance (SPR). The third objective was to evaluate various seed characteristics on germination and yield in the laboratory and greenhouse in an attempt to understand factors affecting establishment success in the field studies. Both Exp. 1 (Ohio),
2 and 3 (Tanzania) used a split plot design with two factors, namely, species and fertilizer where Exp. 1 had species at four levels plus an unsown control as the main plot factor, and fertilizer at two levels (+N and +P) plus the unfertilized control as the sub-plot factor. Exp.
2 and 3 (Tanzania) had species at four levels and the subplot factor was fertilizer at three levels. The main-plot vegetation treatments for Exp. 1 were Cenchrus ciliaris (buffel grass) that was dominated by weeds, Brachiaria deflexa (brachiaria), Glycine max (soybean ),
Eragrostis teff (teff), and the control (bare soil). The main plot vegetation treatments for
Exp. 2 included, C. ciliaris, Chloris gayana, Stylosanthes scabra, and the unplanted control
ii while Exp. 3 mainplot vegetation treatments included E. teff, Vigna inguiculata, Sorghum vulgare and the unplanted control. Fertilizer treatments applied to Exp. 2 and 3 were DAP
(diammonium phosphate, 46% P2 O and 18% N) at the rate of 30, 20, and 0 kg/ha. In all experiments there were four replications as a randomized complete block design making
60 experimental units in Exp. 1, and 48 experimental units for Exp. 2 and 3. The measurements were similar in all experiments and included, baseline chemical status, soil penetration resistance (SPR) by penetrometer, seedling emergence, water infiltration using the Mariotte bottle technique, yield, plant density, plant cover and soil moisture. In Exp. 1 there were significant effects (P<0.05) between species for yield, species population density, penetration resistance, and water infiltration. In Exp. 2 and 3, species treatments were significantly different for yield, SPR at some depths, water infiltration, population density, emergence, and cover (P<0.05). Fertilizer treatments were significantly different in yield, water infiltration and SPR for both experiments (P<0.05). However, fertilizer had no significant effects on emergence, cover, population density, and soil moisture. There was a species by fertilizer interaction effect (P<0.05) in yield and soil penetration resistance in both experiments. Our results showed that plant vegetation has the potential to alter soil physical properties such as water infiltration and soil compaction through improved cover and biomass production. Therefore improved soil physical characteristics through biomass production and soil organic matter can reduce vegetation and soil degradation and enhance the overall sustainability of the soil quality. iii
ACKNOWLEDGMENTS
I would like to thank my Advisor Dr. David Barker for his support, confidence and guidance throughout these two years. Also, I wish to thank my advising committee members Dr. Mark Sulc, Dr. Brian Slater and Dr. Ephraim Mtengeti for all their efforts during this project. It was an honor to work with my advisor and all the committee members. I thank the Waterman Farm Manager for providing with important help during site preparation. I thank USAID through IAGRI for funding my studies.
Furthermore, I thank the Tanzania Livestock Research Institute (TALIRI), Kongwa for hosting part of my project. I thank Dr. Msangi and George Fupi and all workers at TALIRI
Kongwa for their immense support. Additionally, I thank Mr. Mdoe for all his great help with soil analysis in the laboratory. I wish to thank my family, for their great encouragement during the whole period of my studies. Last but not least, I express my appreciation to my wonderful fiancée, Privata Simon for her support in every step during my project. Her efforts during these two years will never be forgotten.
iv
VITA
2009...... Kibiti High School
2012……………………………………… B.S. Range Management, Sokoine
University of Agriculture, Tanzania
2012 to 2014 ...... Research Assistant, Sokoine University of
Agriculture
2014 to present ...... Graduate Student, The Ohio State University
FIELDS OF STUDY
Major Field: Horticulture and Crop Science
Minor Field: Forage Agronomy
v
TABLE OF CONTENTS
ABSTRACT ...... ii
ACKNOWLEDGMENTS ...... iv
VITA ...... v
FIELDS OF STUDY...... v
Major Field: Horticulture and Crop Science ...... v
Minor Field: Forage Agronomy ...... v
LIST OF TABLES ...... xiii
LIST OF FIGURES ...... xviii
INTRODUCTION ...... 1
CHAPTER 2: LITERATURE REVIEW ...... 6
Degradation of cropland and rangelands in Tanzania ...... 6
Overgrazing ...... 6
Weed infestation ...... 8
vi
Erosion, runoff, and loss of soil organic matter ...... 10
A review of forages used in Tanzania ...... 12
Main forage species used in Tanzania ...... 12
Agro-ecological zones with potential forage resources in Tanzania ...... 15
Forage establishment ...... 18
Seedbed preparation ...... 18
Seeding depth effect on germination and subsequent establishment ...... 19
Seeding methods ...... 20
Sprig seeding ...... 20
Natural reseeding ...... 21
Broadcast seeding ...... 21
Drilling...... 22
Fertilizer effect on vegetation growth and establishment ...... 23
Environmental restoration from re-established vegetation ...... 24
Water infiltration ...... 24
Soil compaction ...... 27
Biomass production ...... 30 vii
CHAPTER 3: ...... 33
THE POTENTIAL OF FORAGE SPECIES TO ENHANCE THE SUSTAINABILITY
OF AN OHIO CROPLAND SOIL ...... 33
ABSTRACT ...... 33
INTRODUCTION ...... 34
MATERIALS AND METHODS ...... 36
Site description ...... 36
Design, procedures and management ...... 37
Field experiment ...... 37
Measurements...... 38
Germination test ...... 39
Green house experiment ...... 40
Statistical Analyses ...... 41
RESULTS ...... 41
Weather data ...... 41
Yield and density of forage cover crop species...... 42
Soil penetration resistance and water infiltration of different cover forage species ..... 43
viii
Soil Penetration resistance (SPR) ...... 43
Water infiltration ...... 44
Germination, population density (emergence) and yield of various grass and legume
seed characteristics ...... 45
DISCUSSION ...... 46
Weather and climate ...... 46
Cenchrus ciliaris ...... 47
Eragrostis teff ...... 49
Brachiaria deflexa ...... 51
Glycine max ...... 52
Control ...... 54
Fertilizer Nitrogen (N) and Phosphorus (P) ...... 55
Unfertilized (control)...... 55
Conclusion ...... 56
CHAPTER 4: ...... 80
COVER CROP EFFECTS ON RANGELAND AND CROPLAND SOILS IN
TANZANIA ...... 80
ix
ABSTRACT ...... 80
INTRODUCTION ...... 81
MATERIALS AND METHODS ...... 83
Site description ...... 83
Design procedures and Management ...... 84
Experiment II: Rangeland ...... 84
Experiment III: Cropland ...... 85
Measurements...... 86
Statistical Analyses ...... 89
RESULTS ...... 90
EXPERIMENT II-RANGELAND ...... 90
Weather data ...... 90
Grazed land soil characteristics ...... 90
Rangeland seedling emergence and population density ...... 91
Rangeland biomass production ...... 91
Rangeland forage herbaceous cover and proportion of sown species...... 92
x
Soil penetration resistance and water infiltration of different forage cover crop species
...... 93
Soil penetration resistance (SPR) ...... 93
Rangeland water infiltration ...... 94
EXPERIMENT III CROPLAND ...... 95
Cropland soil characteristics ...... 95
Seedling emergence of cover cop species and population density...... 95
Cropland biomass production...... 96
Cropland vegetation cover and proportional of sown species...... 97
Soil Penetration Resistance and water infiltration of cover crop species ...... 98
Soil penetration resistance ...... 98
Water infiltration ...... 100
DISCUSSION ...... 101
EXPERIMENT II-RANGELAND ...... 101
Weather and climate ...... 101
Cenchrus ciliaris...... 101
Chloris gayana ...... 103
xi
Stylosanthes scabra ...... 105
Control (unplanted) ...... 106
Diammonium phosphate fertilizer ...... 107
Conclusion ...... 108
EXPERIMENT III-CROPLAND ...... 109
Sorghum vulgare...... 109
Eragrostis teff ...... 111
Vigna inguiculata ...... 112
Control (unplanted) ...... 113
Diammonium phosphate fertilizer ...... 114
Conclusion ...... 115
REFERENCES ...... 153
xii
LIST OF TABLES
Table 1: Agro-ecological zones with potential forage resources...... 17
Table 2: Seed rates and characteristics used for the Ohio field study (Exp.1)...... 57
Table 3: Mean air temperature, total precipitation, relative humidity, solar radiation and soil temperature recorded in Columbus, OH for the year 2015 ...... 58
Table 4: Yield of cover forage species at the end of Exp.1 in October 2015...... 59
Table 5: Yield of cover forage species at the end of Exp. 1 in October 2015 under various fertilizer treatments...... 60
Table 6: Population density of four cover forage species measured in October 2015. .... 61
Table 7: Population density of cover forage species at various fertilizer treatments measured in October 2015 (Exp. 1) ...... 62
Table 8: ANOVA for soil penetration resistance measured in September, 2015 ...... 63
Table 9: Soil penetration resistance and soil moisture measured in September 2015...... 64
Table 10: Soil penetration resistance at various fertilizer treatment measured in September
2015 (Exp. 1)...... 65
Table 11: ANOVA for soil penetration resistance measured in November 2015 (Exp. 1)
...... 66
Table 12: Soil penetration resistance and soil moisture measured in November 2015 in
(Exp. 1)...... 67
xiii
Table 13: Soil penetration resistance under various fertilizer treatments measured in
November 2015 (Exp. 1)...... 68
Table 14: Water infiltration measured by Mariotte bottle in September 2015 (Exp. 1).. . 69
Table 15: Water infiltration measured by Mariotte bottle under various fertilizer treatments in September 2015 (Exp. 1)...... 70
Table 16: Water infiltration measured by Mariotte bottle in November 2015 (Exp. 1).. . 71
Table 17: Water infiltration as affected by fertilizer measured by Mariotte bottle technique in November, 2015...... 72
Table 18: Cumulative germination percent of four cover forage seed species tested in the germination chamber from July, 15 to August , 5 2015...... 73
Table 19: Cumulative germination percent means of four cover forage seed species tested in the germination chamber 2015...... 74
Table 20: Mean emergence of four cover forage species planted in a greenhouse from
September to December 2015 Columbus Ohio...... 75
Table 21: Mean yield of four cover forage species planted in a greenhouse from September to December 2015 Columbus Ohio...... 76
Table 22: Monthly mean precipitation recorded at Kongwa Pasture Research Center for consecutive years of 2015 to May 2016 where the experiment ended...... 117
Table 23: Mean seedling emergence of cover forage species in (Exp. 2) on February 2016..
...... 118 xiv
Table 24: Mean yield of cover forage species measured on (Exp. 2) in April 2016...... 119
Table 25: Mean yield of cover forage species measured in April 2016 on (Exp. 2) as affected by DAP fertilizer treatment...... 120
Table 26: Yield of cover forage species measured in April 2016 on (Exp.2) as affected by species and fertilizer interaction.s ...... 121
Table 27: Mean population density of cover forage species measured in April 2016 on
(Exp.2)...... 122
Table 28: Vegetation cover percent measured on (Exp.2) in March 2016. In the parentheses are sown species cover…………...... 123
Table 29: ANOVA for soil penetration resistance measured in April, 2016 on (Exp. 2).
...... 124
Table 30: Soil penetration resistance and soil moisture measured in April 2016 on (Exp.
2)...... 125
Table 31: Soil penetration resistance as affected by species and fertilizer interaction measured in April 2016 on (Exp 2)...... 126
Table 32: Water infiltration measured in April 2016 on (Exp. 2)...... 127
Table 33: Water infiltration as affected by fertilizer measured in April 2016 on (Exp. 2)..
...... 128
Table 34: Soil characteristics in (Exp. 2) measured in January 2016 ...... 129
xv
Table 35: Seedling emergence of cover crop species counted in February 2016 in (Exp. 3)
...... 130
Table 36: Population density of cover crop species measured in April 2016 on (Exp. 3).
...... 131
Table 37: Yield of cover crop species measured in April 2016 on (Exp. 3)...... 132
Table 38: Yield of cover crop species measured in April 2016 as affected by DAP fertilizer on (Exp. 3)...... 133
Table 39: Species by fertilizer interaction on yield of cover crop species measured on April
2014...... 134
Table 40: Vegetation cover of crop species measured in March 2016 on (Exp. 3). In the parentheses is the proportional of sown species...... 135
Table 41: Vegetation cover percent of cover crop species as affected by DAP fertilizer measured in March 2016 on (Exp. 3)...... 136
Table 42: ANOVA for soil penetration resistance measured in April, 2016 on (Exp. 3).
...... 137
Table 43: Soil penetration resistance of cover crop species measured in April 2016 on (Exp.
3)...... 138
Table 44: Fertilizer effect on soil penetration resistance measured in April 2016 on (Exp.
3)...... 139
xvi
Table 45: Fertilizer by species interaction on soil penetration resistance measured in April
2016 on (Exp. 3)...... 140
Table 46: Water infiltration measured in April, 2016 on (Exp. 3)...... 141
Table 47: Water infiltration as affected by fertilizer measured in April 2016 on (Exp. 3)..
...... 142
Table 48: Soil characteristics measured on (Exp. 3) in January 2016...... 143
Table 49: Mean seedling emergence planted in a green house, February 2016 ...... 144
Table 50: Mean yield of cover forage species measured in a green house, April 2016. 145
xvii
LIST OF FIGURES
Figure 1: Linear regression line showing the relationship between soil penetration resistance and water infiltration...... 77
Figure 2: Linear regression line showing the relationship between forage mass and water infiltration...... 78
Figure 3: Linear regression line showing the relationship between forage mass and soil penetration resistance ...... 79
Figure 4: Water infiltration model for determination of unsaturated hydraulic conductivity.
...... 146
Figure 5: Species by fertilizer interaction effect on yield measured in April 2016 on (Exp.
2)...... 147
Figure 6: Species by fertilizer interaction effect on soil penetration resistance (7.5cm) depth measured in April 2016 on (Exp. 2)...... 148
Figure 7: Fertilizer by species interaction on yield measured on (Exp. 3) in April, 2016.
...... 149
Figure 8: Linear regression line for the relationship between soil penetration resistance and water infiltration measured in April 2016 on (Exp. 30)...... 150
Figure 9: Linear regression line for the relatioship between forage mass and water infiltration measured on April 2016 on (Exp. 3)...... 151 xviii
Figure 10: Linear regression line for the relationship between yield and soil penetration resistance measured on (Exp. 3) in April 2016 ...... 152
xix
CHAPTER 1:
INTRODUCTION
Soil degradation is among the most important issues that threaten the sustainability of the world’s agriculture, and its effects can be seen in all continents including America and
Africa. The effects of soil degradation include carbon loss to the atmosphere, reduced agricultural productivity, and accelerated soil loss by erosion into lakes and rivers.
Degradation can result from both over-grazing by livestock in rangeland, and repeated cultivation in cropland. The goal of this research project was to determine the extent to which re-establishment of vegetation can prevent and reverse soil degradation.
Sustainability is a broad term with many definitions, however, these are consistent in that sustainable land use comprises both biophysical and socio-economic components. In this study, the biophysical dimension will be emphasized and its indicators include elements that can be used to define resources such as soil, water, and vegetation (Lambert et al.,
1996). For the purpose of this study, sustainability is defined as the wise use of both cropland and rangeland resources by producing the best output without deteriorating their production potential. Sustainable utilization of these components will ensure farmers provide goods and services while protecting their financial returns.
Herbaceous forage species can be used to manage agro-ecosystems as a mechanism to naturally enhance and sustain fertility, soil stability, and water availability. To achieve these goals, understanding the potential of different forage species in protecting and 1 sustaining the soil in terms of protection from disasters such as degradation is of importance in maximizing crop and forage growth with less use of external inputs. Cover crops for instance, have benefits in rangelands and croplands, including to sustain their soil quality (Eviner & Chapin, 2001).
Research in this study was conducted within the Innovative Agricultural Research Initiative
(iAGRI) funded by United States Agency for International Development (USAID) as part of its Feed the Future (FtF) program. The goal of FtF is to sustainably reduce global poverty and hunger. Among the Objectives of iAGRI are to provide advanced degree training in agricultural, biological and social sciences for 120 Tanzanian post-graduate students, and this project addressed items 1) irrigation and water management, and 7) climate change and natural resources management. While at The Ohio State University, I learned methods in agronomic study that were subsequently applied in field research in Tanzania.
Oversowing with improved plants has benefits such as improved herbage production, improved quality of forage, and provides better tolerance for grazing, drought, animal trampling effects, low fertility, or pest attack (Lambert et al., 1985). Depending on the purpose, the oversowing techniques might differ. For example, oversowing on bare ground is most relevant for a grass-legume mixture while for pasture improvement, species selection is determined by the fertility level. Introduction of improved plant species in unimproved pastures is of no advantage while oversowing legumes in a moderately improved pasture is advantageous (Lambert et al., 1985). 2
Fertilizer application such as N and P, at the establishment stage is of great value since it can enhance plant emergency and seedling vigor where soil fertility is inadequate (Barker et al., 2012). Even though, in most rangelands especially in semi-arid areas, studies indicated lack of moisture rather than soil fertility as the predominant constraint to pasture growth and productivity (Mtengeti, 2015). That is increased forage production is observed with precipitation increase to about 500mm per year, subsequently soil characteristics can undertake much higher role in determining forage production than precipitation (Mtengeti,
2015).
Rangelands in Tanzania are estimated to be 60 million ha of these, the suitable rangelands for livestock grazing are estimated to carry about 20 million animal units (Mwilawa et al.,
2008). One Tropical livestock unit of a Tanzanian short horn zebu is a 250 kg cow. The predominant rangelands suitable for livestock grazing in Tanzania are in Dodoma, Singida,
Shinyanga, Mwanza, Arusha, and Kagera regions. However most of these areas are dry and drought-prone, which can complicate the livestock industry. The livestock population in Tanzania is largely cattle (25.8 million), goats (17.1 million), and sheep (9.2 million)
(MALF, 2016) traditional pastoralists and agro-pastoralists own 99% of livestock, and the remaining 1% are owned by ranchers and dairy farmers (Mwilawa et al., 2008).
High stocking has decreased the production from rangeland which has caused traditional pastoralists and agro-pastoralists to develop different ways of maximizing the utilization of forages. High forage production during the wet season allows pastoralists to rest some 3 grazing areas for future use. However, lack of land ownership (title deed) and land use pressure such as conversion of grazing land into crop lands give no assurance of the recovery time and the overall reserve practices are even difficult and complicated
(Mwilawa et al., 2008). The resultant decreasing mobility of nomadic herders in rangelands has caused overgrazed and degraded vegetation, leaving large areas of land bare and vulnerable to accelerated erosion. Thus this study will investigate the use of annual and perennial forage cover crop species to enhance the sustainability of degraded rangeland and crop land soils, by increasing ground cover to aid water infiltration, build organic matter, and enhance soil structure.
This thesis comprises four chapters. Chapter 2 is a review of the literature, summarizing recent research into the mechanisms by which plant vegetation might affect soil physical attributes. Chapter 3 describes a field study in Columbus OH, in which the effects of plant and fertilizer treatments on soil penetration resistance and water infiltration were measured.
Chapter 4 describes two field studies in which plant and fertilizer treatment effects were measured on the same soil characteristics in Tanzania.
The first objective of research in Chapters 3 (Ohio) and 4 (Tanzania) was to evaluate the effect of various forage cover crop species under varying levels of fertilizer treatment on forage production (yield) and stand density. The second objective was to determine the effect of the same vegetation and fertilizer treatments on water infiltration and soil penetration resistance (SPR). The third objective was to evaluate various seed 4 characteristics on germination and yield in the laboratory and greenhouse in an attempt to understand factors affecting establishment success in the field studies.
The hypothesis of the research was that establishment of forage species (annuals into cropland and perennials into grazing land) would result in plant vegetation of benefit to both forage production (yield), and improved soil physical characteristics (Carter, 2002;
Kaspar et al., 2001; Roberson et al., 1995). Vegetation is expected to increase water infiltration, and reduce SPR. The effects of fertilizer are expected to be greater forage yield, and increased effects on water infiltration and SPR.
5
CHAPTER 2: LITERATURE REVIEW
Degradation of cropland and rangelands in Tanzania
Overgrazing
As is in other parts of the world, overgrazing in Tanzania is one of the main factors causing environmental degradation due to its dramatic environmental consequences such as erosion, biodiversity reduction, runoff, change in soil properties, and the overall reduction of soil quality (Sangeda et al., 2013). The major indicators of rangeland degradation are a shift in plant species composition, loss of range biodiversity, reduction in biomass production, less plant cover, low herbaceous cover, low herbaceous productivity, low frequency of desirable forage species, low small ruminant productivity, and accelerated soil erosion (Ahmad & Ehsan, 2012; Mtengeti, 2015). These indicators of rangeland degradation have been observed in the arid and semi-arid rangelands of central Tanzania
(Sangeda et al., 2013; Mtengeti, 2015).
In north Africa, rangelands and natural pastures are reported to have high degradation and as a result have reduced their contribution to livestock feed for example, in Tunisia, the contribution of rangelands to livestock diet has decreased from 65 to 10% (Karrou and El
Mourid, 2008). Similarly, as observed in Ethiopia, pastoral systems are losing resilience as traditional coping mechanisms fail to provide forage supply due to increasing
6 environmental and rangeland degradation and lack of national polices to address the problem (Kassahun, 2008).
Deterioration of rangelands has been intensified by increased human population pressure and encroachment of rangelands by other land uses (Vetter, 2005). Generally, rangeland vegetation is managed by grazing. However, overgrazing has always resulted in reduced ground cover, soil compaction, and erosion (Oztas, 2003). Retzer (2006) pointed out that uncontrolled grazing has increased pressure in most African rangelands and led to vegetation cover loss and change in vegetation species composition. Oztas (2003) reported erosion has removed 500 million tons of productive soil due to over-grazing in Turkey.
This is a serious problem in many countries, including Tanzania, where over-grazing is common.
Different studies agree that, under rangeland conditions, depletion of vegetation cover due to overgrazing, dominance of undesirable species and unpalatable plants, depletion of soil nutrients and its quality, absence of litter, and soil trampling is the most critical factor causing degradation of physical and biological rangeland resources (Oztas, 2003;
Haileslassie, 2005; Wolde et al., 2007).
Kassahun (2008) reported an increasing degradation of rangeland resources both in intensity and magnitude as revealed by environmental degradation has resulted in increasing abject poverty and poses great threat to the sustainability of pastoral production systems in Somali region of Ethiopia. Degradation of rangeland resources is therefore a 7 serious challenge and has caused serious problems to pastoral livelihood by affecting the livestock production system.
Weed infestation
The introduction of non-native species to a new environment is of concern due to their potential negative ecological and economic impacts. In Tanzania, many agricultural fields have been infested by weeds which reduce productivity of both crop and livestock agriculture. Weeds in forage crops are essentially competitors for light, soil nutrients and moisture (Fick et al., 2003). Weeds can be classified based on their designation as native, invasive and/or noxious (Masters & Mitchell, 2007). However, invasive and noxious weeds represent species of special concern due to special threat they pose to the environment.
Invasive species are described as exotic which lack enemies to limit their population expansion and are characterized by high rapid growth and reproductive rates (Masters &
Mitchell, 2007). Exotic plants may or may not be invasive, however all invasive plants are exotic. Many exotic plants are agronomically important crops (Masters & Mitchell, 2007).
Hanley (2003) describes the reasons contributing to spread of the alien weed species, primarily, plants evolving in a new habitat are capable of developing and reproducing without the restrictive effects of tissue loss or seed predation, resulting in a competitive advantage over indigenous species in the new environment.
Similarly, Peltzer (2014) identified agroecosystems to be both sources and sinks of non- native weedy plant species and of native plant species. The author mentioned 8 anthropogenic factors such as the increased propagule pressure, to be a larger driver towards infestation of non-native plant species. However, different land use and management practices are described to control the association between native and non- native diversity upon disturbance and primary productivity regimes (Sandel & Corbin
2010; Tomasetto et al., 2013)
It has been reported that weed infestation is among the serious problems in Africa, and may take up to 50% or more of the labor or labor cost that is required for producing crops
(Okezie, 1980). This has reduced the effectiveness of agriculture production in many
African countries including Tanzania. The problem is intensified due to the reason that, only few farmers have the capacity to control weeds using methods other than mechanical control.
Okezie (1980) describes how characteristics of the humid and sub humid tropics, such as high temperature and humidity, can favor rapid and excessive weed growth. Where moisture is limiting, such as in rangelands, weeds pose greater competition and can adversely affect crop growth and development while in humid areas where moisture is not limiting, weeds pose more competition for light and nutrients. However, the severity of weed infestation and their impacts on yield reduction vary with type of crops, soil type, rainfall patterns, land management practices, and planting density (Okezie, 1980).
In a different context, seed dispersal is crucial ecologically, and patterns of dispersal and establishment mechanisms are key in determining the extent of spread and new infestations 9 in the environment (Radford, 2001). Options for seed dispersal include contamination with farm implements even before preparing a seedbed for forage grasses, planting the seed which are contaminated with weed seed, wind dispersal, and animals via their digestive tract. Many weeds are adapted to survive in a low fertility environment and can readily grow in overgrazed areas or under shifting cultivation practices and frequent fires which make them persist in our agriculture systems. Annuals are described to be the first plants to colonize the area following disturbance such as tillage and through seed production make their spread rapid therefore reducing the amount of seeds produced is key to effective long- term management of weeds (Masters & Mitchell, 2007).
Erosion, runoff, and loss of soil organic matter
Land management practices have been described to influence erosion and transport of sediments and nutrients from the surface runoff. Haan et al. (2006) describe how cattle grazing and their resulting treading can adversely affect grazing resources due to a decreased soil organic matter, as a result of of leaf litter reduction. The overall result can be a reduced water holding capacity of the soil, lowered infiltration, which result in increased surface water runoff.
Sangeda et al. (2013) identified the semi-arid rangelands of central Tanzania to be degraded and identified signs of erosion such as gullies due to runoff, loss of plant cover, and loss of soil organic matter associated with various land uses including grazing. Similar degradation is likely in other areas of Tanzania rangelands. 10
High stocking may reduce water infiltration due to associated soil compaction as a result of cattle treading. However forage production systems assocated with correct stocking has benefits that include soil structure improvement, microporosity increase, improved water infiltration, soil protection from rain drop impact, and sediment filtration from surface runoff (Haan et al., 2006). Treading effects has been documented to reduce soil organic matter (Betteridge et al., 1999), which results in associated effects such decreasing infiltration rate and hence increasing the volume of surface runoff. The study by Haan et al. (2006) indicated significant lower soil penetration resistance (in the upper 14 cm) and higher infiltration rate in ungrazed treatment as compared to paddock with other forage management treatments. Similarly, another study by Naeth et al. (1991) pointed out that reduced water infiltration was a result of soil compaction due to animal trampling effects.
However, the intensity of grazing which dictates the extent of vegetation degradation influences loss of soil organic matter and severe runoff observed in many degraded lands.
A study by Betteridge et al. (1999) reported sediment loss due to larger bare spaces on the pasture vegetation. The study observed an increased sediment loss with a reduced canopy height from 4.7 cm to 0.5 cm under simulated rainfall. Under the same reduced rate of canopy cover, moderate treading was observed to have higher soil degradation as compared to severe treading with a lower rate. Therefore the study explains the fact that areas that have no or less vegetation cover are more prone to degradation due to livestock treading as compared to areas with good vegetation cover. Therefore managerial practices that ensure 11 permanent vegetation cover reduce the risk of soil degradation, prevent runoff, and sustain soil quality.
Aksakal et al. (2011) described how animal trampling can affect soil properties by compacting the soil and therefore reduce its porosity reduce water infiltration, increase runoff and erosion, and impede root growth. In this study, grazing was identified to be significantly affecting bulk density and penetration resistance of rangeland soils. While a significant increase in soil penetration resistance was observed to be higher between July and August (3.88-4.21 MPa) and more constant in September, the mean bulk density for
August was found to be higher (5.7%) than that for July. The results generally indicated varaiability in penetration resistance measurements to be almost constant with grazing after
July. In addition, Owens et al. (2012) described input losses by surface runoff in pastures managed by continuous or rotational stocking. The study pointed out that, grazing intensity affected the quality of surface runoff.
A review of forages used in Tanzania
Main forage species used in Tanzania
East African natural grasslands are among the world’s largest genetic resources of cultivated tropical grasses (Boonman, 1993). Grassland can be defined as “Land dominated
12 by grasses and occasionally other herbs; sometimes with widely scattered or grouped trees and shrubs, the canopy cover of which does not exceed 2%” (Boonman, 1993).
Forage grasses of economic importance are found in genera such as Cenchrus, Chloris,
Cynodon, Brachiaria, Pennisetum, Panicum, Andropogon, Digitaria, Eragrostis,
Sorghum, Setaria, Melinis, Urochloa, Hyperrhenia, Heteropogon, and Themeda.
Important legume genera include; Centrosema, Desmodium, Stylosanthes, Medicago,
Lablab, Vigna, Pueraria, Rhyconsia, Clitoria, Calopogonium, Macroptilium, Mucuna, and
Trifolium. While important woody legume fodder include genera Leucaena, Gliricidia,
Acacia, Sesbania, Grewia, Albizia, Cajanus, and Desmanthus. On the other hand, there are some non-leguminous fodder trees and shrubs such as genera Calliandra, Morus, and
Moringa (Kayombo et al., 2016).
Forage availability is generally determined by factors such as climate, soil type, topography, and the type of management. However, livestock production in Tanzania relies predominantly on natural pastures. The main types of natural pastures include Chloris roxburghiana, Enteropogon macrostachyus, Cenchrus ciliaris, Cymbopogon aucheri, and
Aristida ascensionis (Sarwatt & Mollel, 2006). These are found between 450 and 1140 m and <380-640 rainfall (Sarwatt & Mollel, 2006). The main trees associated with these grasses include Commiphora, Acacia, and Adansonia. Grasses such as Eragrostis species,
Setaria, and Hyparrhenia spp occurs in open grassland (savanna) and are influenced by
13 extreme cultivation. They occur in high rainfall areas between 1500 and 1800 mm rainfall
(Sarwatt & Mollel, 2006).
Hyparrhenia rufa and Bothriochloa insculpta are grasses of edaphic grassland and are influenced by frequent burning and flooding. Others include Andropogon schirensis,
Pennisetum polystachyon, Setaria spp, Chloris gayana, and Hyparrhenia filipendula,
Echinochloa pyramidalis, and Imperata cylindrical. They occur within the zone of 760 to
1140 mm rainfall and 1200 m altitude (Sarwatt & Mollel, 2006).
Panicum species are among the most abundant in Africa. This genus is associated with woodland at varying densities of Acacia species. It occurs along the coast with rainfall of
1000 mm. Common species include Panicum maximum, Hyparrhenia rufa, Pennisetum purpureum, Brachiaria mutica, Bothriochloa glabra, Echinochloa pyramidalis, and
Chloris gayana. Panicum is also associated with species such as Cenchrus ciliaris,
Brachiaria brizantha, and Cynodon nlemfuensis which occurs between 750 and 1350 m above sea level and rainfall between 380 and 760 mm (Sarwatt & Mollel, 2006).
Themeda triandra and Pennisetum clandestenum occur in open grassland with tall grasses or sometimes short grasses maintained by fire, grazing management, and fertility of the soil. They are largely found in medium to high altitudes areas (1500-2400 m) with a bimodal pattern of rainfall of 750-1500 mm (Sarwatt & Mollel, 2006).
Graziers in Tanzania make heavy use of natural pastures, and practice relatively little supplementation. Some popular improved grasses include; Pennisetum purpureum and 14
Tripsacum laxum while leguminous trees such as Leucaena lecocephala, Gliricidia and
Acacia species have been widely cultivated as multipurpose trees in terms of fodder, fuel wood, electric poles, wind breaks, and shade (Kayombo et al., 2016). Livestock production especially in agro-pastoral areas also relies on crop residues such as maize, rice, beans, and pea straw, which can be harvested and fed to the animals during the dry season or grazed directly in the field. However, grazing crop residues in-situ should be discouraged because the resultant trampling can damage soil structure and exacerbate wind soil erosion.
Agro-ecological zones with potential forage resources in Tanzania
In Tanzania, there are four ecological zones with significance for forage production: humid to dry sub-humid (eco-zone II), dry sub-humid to semi-arid (eco-zone III), semi-arid (eco- zone IV) and arid (eco-zone V) (Table 1) (Boonman, 1993; Sarwatt & Mollel, 2006). Zone
I (The Afro-Alpine) which is in highland (mountainous) areas is of limited use and potential.
The humid to sub-humid zone (ecological Zone II) is described as forest derived grasslands and bush which have potential for forestry, intensive agriculture, and cash crops such as coffee and tea. This zone has potential for intensive management of natural grasslands to support livestock production (Boonman, 1993; (Sarwatt & Mollel, 2006).
The dry sub-humid to semi-arid zone (ecological Zone III) is described to have a varying cover of moist woodland, savannah, or bush where the dominant trees are largely broad- leaved species such as Combretum or Brachystergia (Boonman, 1993; Sarwatt & Mollel, 15
2006). It is highly cultivated for crops, with large areas under extensive grazing. The grass species commonly in this zone are stimulated or maintained by burning. Ley farming is also encouraged (Boonman, 1993).
The semi-arid zone (ecological Zone IV) is described as land of marginal crop potential dominated with natural vegetation of Acacia-Themeda association with dry Brachystegia woodland (Boonman, 1993; (Sarwatt & Mollel, 2006). This zone has potentialy productive rangeland (Boonman, 1993). It is constrained by bush encroachment, invasive plants, degraded soils, drought, and tsetse fly infestation and hence a lower carrying capacity.
The arid or ecological zone (Zone v), is an area described as unsuitable for agriculture however, crops can be grown in small areas of fertile soil and run-on rainfall (Sarwatt &
Mollel, 2006). The forage species dominating the area include perennial grasses such as
Cenchrus ciliaris and Chloris roxburghiana where the woody vegetation dominating the area include Commiphora and Acacia (Boonman, 1993). Prescribed burning is crucial in maintaining bush control however care is required.
16
Table 1: Agro-ecological zones with potential forage resources. Modified from Boonman (1993; Sarwatt & Mollel, 2006).
Climatic zone Eco - Common species
zone
Humid to dry sub-humid II Penisetum purpureum, Pennisetum
clandestinum, Cynodon nlemfuensis, Cynodon
plectostachyus Digitaria mombasana,
Heterepogon contortus, Dactyloctenium
geminatum, Hyperrhenia rufa, Themeda
triandra.
Dry sub-humid to semi- III Themeda triandra, Hyparrhenia filipendula, arid Hyperthelia dissolute, Panicum maximum,
Brachiaria decumbens, Pennisetum unisetum
and Bothriochloa insculpta, Chloris gayana,
Semi-arid IV Themeda triandra, Cymbopogon pospischilii,
Eragrostis superba, Bothriochla insculpta,
Pennisetum mezianum and Panicum
coloratum
Arid V Cenchrus ciliaris, Chloris roxyburghiana
17
Forage establishment
Establishment of forage species may be required for various reasons such as the loss of desirable forage species due to overgrazing and climate change. Improved forage species might be desired to increase yield. Factors such as seedbed preparation, time and depth of planting, seed quality, seeding rate, pH of the soil, soil fertility, and weed control are very important during forage establishment (Barker & Collins, 2003) (Cosgrove & Collins,
2003).
Seedbed preparation
Seedbed preparation is important before forage planting. The preparation varies depending on the objective. For example, oversowing may require less preparation in terms of removal of native vegetation as compared to the goal of establishing a new and pure pasture stand.
Seedbed preparation becomes even more critical for forage planting as compared to grain crops due to their smaller seed size compared to crop seeds (Cosgrove & Collins, 2003).
Tillage practices also differ, ranging from finely cultivated seedbed to less cultivated seedbeds, factors such as erosion (sloping ground) and seedling emergence may determine whether the seedbed should be heavily cultivated or less cultivated (Cosgrove & Collins,
2003). However the goal of fully and well prepared seedbed with tillage and fertilizer application for instance is to create a good environment that enhances seed establishment or plant propagules (Barker et al., 2012). One purpose of cultivation is to create a firm, fine, and level seedbed, using mechanical equipment which includes ploughing, cultivating 18 or discing, harrowing, and/or rolling (Sheldrick, 2000). A loose seedbed, which might result from excessive tillage are prone to both surface crusting following rainfall and rapid moisture loss. However, a poorly cultivated seedbed can impede seed-soil contact and make germination difficult. An ideal seedbed is fine and firm (not loose or cloddy) to foster emergence by ensuring a seed-soil contact, free from competition from native vegetation and weed seeds, and the seedbed just below the planting depth is very firm
(Barker et al., 2012). A firm and fine seedbed is crucial to ensure moisture can reach seeds through capillary action via the fine pore spaces, while a level surface enables the drilling machinery to go smoothly and consistently, to place the seed at the correct depth
(Sheldrick, 2000).
Seeding depth effect on germination and subsequent establishment
Depth of planting is crucial for forage planting due to the forage seed size and varying shape. Proper depth utilization during planting maximize chances for emergence, and seedling growth to allow rapid establishment (Barker et al., 2012). The ideal planting depth has been described by Barker et al., (2012) as depending on; seed size, soil texture, available soil moisture, seeding time, and the firmness of the seedbed. Planting forage seeds too deep in the soil might hinder germination and hence subsequent establishment however, large seeds can emerge from greater depths. It has been noted that, most forage seedlings fail to emerge from the ground if planted more than 25 mm deep (Cosgrove &
Collins, 2003). Optimum soil seed contact is very important to foster germination and 19 subsequent establishment. On the other hand, seedling emergence from greater depths of coarser-textured sandy soils has been well documented. On clay and loam soils, optimum seeding depths are recorded to be 6 to 12 mm while 12 to 25 mm has been recorded as optimum depths for sandy soils (Cosgrove & Collins, 2003). Greater depth of planting is also crucial in a dry environment to conserve soil moisture which is important for seed germination. However shallow depth planting is recommended where moisture is available.
Seeding methods
Seeding methods vary depending on the goal of the establishment. Seeding method for grassland species for instance, may range from high cost, high input methods which optimizes conventional establishment where the field is fully cultivated and the seedbed well tilled to low cost, low input methods such as livestock seeding or frost seeding (Barker et al., 2012).
Sprig seeding
Sprig method is used to establish plants vegetatively using plant stolons or tillers. Bermuda grass (Cynodon dactylon) has commonly been established with stolons (Greene et al.,
1992). On the other hand, plant tillers such as those of Cenchrus ciliaris can also be used due to the presence of underground stems (rhizomes) which contain nodes from which roots emerge. However a substantial amount of moisture is important to facilitate
20 germination and subsequent establishment (Barker et al., 2012). The depth recommendation for sprig planting ranges from 3-5 cm deep into moist soil (Taliaferro et al., 2004).
Natural reseeding
Successful stand establishment using natural reseeding involves the application of knowledge from natural grassland reproductive processes. For instance, delayed grazing or harvesting can be used after the seed ripens, such as for legume seeds with long lived seeds and which don’t have auto toxicity. This method is not applicable nor recommended with grass species that have short longevity in the soil (Barker et al., 2012). In addition, canopy management is required to reduce competition during seed germination and seedling establishment. Overall, however, seedlings from natural reseeding establish poorly in a competitive environment due to low quality seeds. Natural reseeding was documented to be successful in the northern Great Plains with wheat-fallow rotation where forage legumes were introduced with no till planting (Carr et al., 2005). The rotation improved the overall economic and environmental sustainability of crop production due to improved nutrient cycling, soil structure, and erosion reduction.
Broadcast seeding
Broadcasting seeding includes a range of techniques all of which are characterized by spreading the seed evenly on the soil surface (Hall & Vough, 2007), but with various
21 options for seed incorporation. Most tropical grass seeds are small with the 1000-seed
(spikelet) weighing < 500 mg (Boonman, 1993). With small acreages, sowing is commonly done by hand, however, scattering such small seeds evenly on ground surface requires adequate skills. One common practice to help sowing is to mix inert matter such as saw dust, rough sand (Boonman, 1993) or even with fertilizer (Sheldrick, 2000) such as phosphorous (Boonman, 1993). However, whenever phosphorous fertilizer is mixed with seeds it needs to be broadcast immediately to avoid scorching the seed. (Boonman,
1993). Lots of broadcast tools exists.
Drilling
While broadcast seeding has been in use many years, and is best suited to low inter-seedling competition, with the sward forming a uniform cover (Sheldrick, 2000), However the shallow sowing depth has a high chance of drying out. With modern grass drills, deeper planting is possible to avoid the dry surface region. Typically, coulters are set about 8-10 mm depth while cereal drills go up to 15-20 mm deep. In order to reduce intra-row competition, half of the seed can be drilled in one direction while the other half at an angle to the first (Sheldrick, 2000). One disadvantage with drilling can be the spacing between the drill rows, which can give rise to weeds and the potential for increased competition as compared to broadcast seeding (Sheldrick, 2000). Drill seeding has an advantage of placing the seed at a uniform depth, where optimum depth ranges up to 1.0 cm for small seeded grasses (such as timothy) and up to 2.5-3.0 cm for large seeded grasses such as rye 22
(Sheldrick, 2000). Cultipacker seeding is one example of broadcasting methods which give optimum seed placement depth and enhance good seed-soil contact. Cultipacker seeders are largely used in tilled seedbeds. Across medium and heavier textured soils with cultipacker seeder, the seeds become distributed over a wide range of depths from the surface to about 2.5 cm deep. With sandy soils, cultipacker seeder increase depth of seed coverage while in heavier soils with finely tilled seedbeds the chances for crusting formation becomes higher (Hall & Vough, 2007).
Fertilizer effect on vegetation growth and establishment
Vegetation growth is related to the fertility status of the soil. Soil testing information is crucial and will inform the researcher whether additional fertilizer is required. Fertilization is more common in cultivated crop lands as compared to rangelands, where less cultivation is made. However, good vigor and sufficient forage yield similar to grain crops can be achieved with adequate fertilization established on soil test information (Cosgrove &
Collins, 2003).
The use of inorganic fertilizer in Tanzania traces back to 1956 when it was introduced by the British American Tobacco Company (BAT) and was mainly for cash crops such as tobacco, coffee and cotton in Northern and Lake zones of Tanzania (Massawe, 2012). More widespread use didn’t start until the 1980s when fertilizer was initiated through the
Kilimo/FAO fertilizer program (Massawe, 2012). However, the current fertilizer recommendations were released in 1993. The report by Massawe (2012) done in Kongwa 23 on agronomic practices and soil fertility analysis for improved maize production in the nearby village where the experiment was conducted, recommends parameters such as cation exchange capacity, soil organic matter, nitrogen, phosphorus, and sulfur to be addressed. The author recommended incorporation of crop residues during land preparation to improve soil organic matter and cation exchange capacity. Phosphorus was recommended with band application of 20-30 kg/ha at sowing. Nitrogen at the rate of 40 kg/ha or more was recommended (Massawe, 2012).
Environmental restoration from re-established vegetation
A cover crop is defined as vegetation that is planted or managed to protect or improve rangelands or crop land, which may have been degraded in terms of soil physical parameters such as water infiltration, soil compaction, crop yield, or soil organic matter
(Dabney, 1998).
Water infiltration
One important soil-ecosystem function is to enhance infiltration of precipitation into the soil, resulting in less surface runoff and erosion (Lal & Shukla, 2004). Existence of an active cover crop or inert residue can increase hydrological resistance of the soil surface and, as a result, slow down runoff (Dabney, 1998). Rain drop impact can cause crusting of the soil surface, and can be reduced with mulch or vegetative cover on the soil surface (Lal
& Shukla, 2004). The overall mechanism is based upon biological and physical interactions
24 which create good and stable soil structure with abundant macropores for quick water transmission (Lal & Shukla, 2004). Disturbed soil due to tillage and related anthropogenic activities (such as high grazing density) often seal surface pores and creates soil crust which results in less infiltration and increased runoff (Lal & Shukla, 2004).
In degraded rangelands where the forages have been overgrazed and soil erosion is evident, techniques that reduce rain water run-off and increase infiltration could benefit germination when reseeding to improve the herbage species composition, ground cover, and soil organic matter. This ultimately improves soil conditions, and especially the soil structure.
In comparison to other land use options, herbaceous forages lower the soil erosion rate
(Owens et al., 1989). In perennial grasslands this occurs by the mechanism of reduced rainfall impact to the soil and protection of the surface structure (Exner & Cruse, 1993).
With their extensive root system, perennial forages enhance soil porosity that facilitates water infiltration, while their dense stand slows surface water movement. In addition, dense and fine roots hold soil particles and the presence of larger number of earthworm aids the formation of macropores which further enhances infiltration (Owens et al., 1989).
Through their impact on soil, cover crops affect hydrology by modifying the partitioning of precipitation into the fractions of runoff amount, infiltration, surface storage, and surface detention (Dabney, 1998). For instance, percolating water may leach beyond the root zone or flow through the root zone to re-emerge as surface flow or remain stored in the soil
(Dabney, 1998). One beneficial aspect of a cover crop is altered runoff by increasing the 25 water infiltration rate, hydraulic roughness, canopy and surface detention, increasing evapotranspiration by increasing profile storage capacity, and altering soil matrix in terms of its structure and porosity (Dabney, 1998).
Through the mechanism of root growth, cover crops can change the macro-pore geometry and indirect affect populations and activities of macro fauna such as earthworms and ants.
By transpiring water, they reduce leaching losses and scavenging nutrients.
Generally cover crops increase the rate and amount of water infiltration in to the soil
(Dabney, 1998). Cover crop species may vary in terms of the extent to which they increase the amount of water infiltration depending on tillage practices, soil type, and climate
(Dabney, 1998). Increase in infiltration could be due to prevention of surface sealing by covering the soil and absorbing the kinetic energy from rain drops, prevention of soil detachment by cover crop canopies which could results in altering soil particles arrangement and hence create surface sealing (Dabney, 1998).
Bruce et al. (1992) describe surface sealing protection to be a function or enhanced by no- till management practice that retains residues on the surface for a longer period of the year.
However, through improved aggregate stability, cover crops can increase the rate and amount of water infiltration even with conventional-tillage by incorporating residues and hence runoff reduction (Folorunso et al., 1992). Dunn and Phillips (1991) found a rye
(Secale cereale L.) cover crop increased water infiltration and reduced runoff in every month except in February. This was due to rapid thawing of bare ground which enhanced 26 water absorption, at the same time, the areas with surface sealing, legume cover crops can increase macroporosity that play a big role in increasing rates of infiltration both in conventional and no-tillage management systems. Some perennial cover crops such as
Tripsicum dactaloides L. can increase the macroporosity of subsurface horizons (Kemper et al., 1987).
Studies have described the variable impacts of different cover crops such as legumes, grasses, annuals, and perennials (Dabney, 1998). One study by Williams and Phillips
(1960) in California indicated that the benefits for water infiltration by various cover crops under furrow irrigation were largest in the cover crop with lowest nitrogen content. Dunn and Phillips (1991) also demonstrated higher infiltration from rye than from a hairy vetch
(Vicia villosa Roth) cover crop in one of the two years observed. The study further suggest over longer periods, some legume cover crops could have larger benefits.
Soil compaction
Soil compaction can be viewed from either dynamic or static perspectives. For example, in dynamic terms, compaction is the physical deformation soil. In static terms, compaction is characteristically related to the resistance of soil to increase its bulk density. In practice however, compaction is a process which results in i) soil mass compression into a smaller volume and, ii) deformation, which leads to reduced macroporosity, water transmission, and gaseous exchange reduction (Lal & Shukla, 2004). The relevance of soil compaction in agriculture lies on the fact that it can impose a devastating effect on root development 27 and crop yield (Lal & Shukla, 2004). Tropical soils are easily compacted and can cause a severe reduction in crop yield. Therefore the goal of soil management is to maintain soil bulk density within the optimal range that favors root growth and development, water retention and transmission, and enhance exchange of gases (Lal & Shukla, 2004). The optimal range for bulk density in most soils is < 1.4 mg/m3, however, this may differ among soils and crops and therefore effects of soil compaction on yield of crops become soil dependent (Lal & Shukla, 2004).
Factors that affect soil compaction include soil wetness and heavy traffic of agricultural machinery particularly in arable land. The pressure exerted on the surface by a single a tyre of a single-axle load is proportional to the total weight of the machinery (Lal & Shukla,
2004).
Soil penetration resistance is a measure of soil strength or resistance to deformation which defines compaction and depends on shape, size and orientation of the axis of the penetrating object. Some soil compaction becomes inevitable with the use of agricultural machinery and other causes such as cattle trampling (Soane and Van Ouwerkerk, 1994). In clay soils of low permeability and poor drainage, soil compaction results in severe crop yield reductions (Kayombo & Lal, 1994) which is a result of impeded root growth. Soil texture also can have a critical limit for root growth which differ in various crops. With sandy loam soil for instance, at field capacity the critical limit for root growth in cotton was measured as 3000 kPa (Lal & Shukla, 2004). 28
Techniques to prevent soil compaction include minimizing the number and frequency of operations with vehicular traffic to absolutely essential, and restricting field operations until when the soil moisture is below range for potential compaction (Lal & Shukla, 2004).
Reduced tillage techniques, such as mulch farming, can help reducing risk of compaction in certain types of soils and environments (Carter, 1994). Other useful methods include, low ground pressure tyres (Vermenlen & Perdok, 1994), dual and wide tyres, and guided traffic could help in reducing pressure on soils.
Hoof action from cattle treading can modify soil physical properties and in concert with reduced cover, normally results in increased bulk density and soil penetration resistance
(Wood & Blackburn 1981). Therefore grazing animals may compact soil and disrupt soil aggregate stability (Willatt & Pullar 1984). The degree of soil compaction is affected by the soil moisture content at the time of compaction. Reduced water infiltration can also occur as a result of soil compaction due to surface sealing and litter cover reduction (Naeth et al., 1991).
The devastating impacts of soil compaction rely on the limitation of available water and nutrients, pore volume reduction, impeded root development and elongation, plant growth reduction, and creation of an anaerobic environment that is intolerable to many plants
(Unger & Kasper, 1994). Deep tillage which requires heavy implements distracts formation of a soil structure and important microorganisms (Lal, 1993).
29
Biomass production
Forage biomass offers a number of benefits including grazing, protecting soil from erosion once it is established, alteration of the soil physical properties by increasing water infiltration and hence reduce runoff, increased organic matter in the soil, retention of nutrients in the soil that could be washed away, and increased soil nitrogen as a result of root and nodule turnover (Barker et al., 2012). Pasture production differs depending on species, cultivars, and the environment in which they are planted.
It is possible to plant species with different growth patterns together or separately in adjacent pastures within a grazing system which help to diversify seasonal availability of the forage quantity and quality (Moore et al., 2004). The goal is to achieve a constant supply of grazeable forage for livestock, conversely the goal can be restricted by periods of drought especially in tropics, cold winters and dry summers in temperate regions (Barker et al., 2012). This means species should be selected on various characteristics ranging from their ability to tolerate extreme weather conditions such as drought, or other factors such as production, ease of harvest, storage, and growth compatibility in mixtures.
Oversowing with improved plants has benefits such as improved herbage production, improved quality of forage, and provides better tolerance for grazing, drought, animal trampling effects, low fertility, or pest attack (Lambert et al., 1985). Depending on the purpose, the oversowing techniques might differ. For example, oversowing on bare ground is most relevant for a grass-legume mixture while for pasture improvement, species 30 selection is determined by the fertility level. Introduction of improved plant species in unimproved pastures is of no advantage while oversowing legumes in a moderately improved pasture is advantageous (Lambert et al., 1985).
Despite complex management, planting mixtures of pasture species offers benefits in terms of larger biomass production and greater livestock production stability (Sanderson et al., 2004). For instance, grass-legume mixtures offer complementary growth patterns in addition to nitrogen fixation from legumes (Barker et al., 2012). Forage biodiversity studies indicate the significance of pasture species mixtures ranging from simple to complex grasses and legumes, to have the potential for herbage yield that can be obtained as a result of increased plant diversity in forage and grazing lands (Sanderson, et al., 2004). Sanderson et al. (2004) argues that an increasing trend in herbage yield is correlated with an increasing number of productive species within the pasture mixture. Considering various factors affecting herbage production and with the difficulty in predicting which species to use and the variation in the best species between seasons suggests forage production maximization is most consistent with planting complex mixtures (Sanderson et al., 2004).
The major environmental factors affecting growth and biomass production include temperature, light, and soil moisture (Hopkins, 2000). Enzyme controlled processes such as photosynthesis and respiration are highly affected by temperature. It also affects growth rates and senescence depending on temperature patterns and its diurnal range (Hopkins,
2000). The effect of solar radiation lies on its wavelength, intensity, and duration or day 31 length since the transformation of absorbed carbon dioxide into biomass depends on captured photosynthetically active solar radiation (Hopkins, 2000). Soil moisture is also an important factor that affects the amount of forage production particularly in dry areas of the tropics. In dry summer areas that experience seasonal drought, soil moisture is affected by amount of precipitation, temperature, and soil conditions (Hopkins, 2000).
Soil nutrient status also affects biomass production and the major nutrients limiting herbage production include N, P, and K (Hopkins, 2000). Grasslands soils largely contain non- available forms of N in terms of organic matter and only a small portion can be mineralized into soil available N. Forage production can be increased drastically with N supply particularly when other environmental factors are not limiting. In addition, forage production could also be limited with limited P and K (Hopkins, 2000).
32
CHAPTER 3:
THE POTENTIAL OF FORAGE SPECIES TO ENHANCE THE
SUSTAINABILITY OF AN OHIO CROPLAND SOIL
ABSTRACT
Frequent cultivation and low soil organic matter can limit crop production. A preliminary study was conducted in central Ohio. The experiment used a split plot design with two factors, namely, species at four levels plus an unsown control as the main plot factor, and fertilizer at two levels (+N and +P) plus the unfertilized control as the sub-plot factor. The main-plot vegetation treatments were Cenchrus ciliaris (buffel grass) that was dominated by weeds, Brachiaria deflexa (brachiaria), Glycine max (soybean), Eragrostis teff (teff), and the control (bare soil). There were four replications as a randomized complete block design making 60 experimental units in total. The measurements included, baseline chemical status, soil penetration resistance (SPR) by penetrometer, population counts, water infiltration using the Mariotte bottle technique, yield, and soil moisture. There were significant effects (P<0.05) between species for yield, species population density, penetration resistance, and water infiltration. However, there were no significant effects of fertilizer, or the fertilizer by species interaction (P>0.05). Our results showed water infiltration to correlate with SPR where higher water infiltration is direct proportional to low SPR. Therefore improved soil physical characteristics through biomass production and
33 soil organic matter improvements can reduce vegetation and soil degradation and enhance the overall sustainability of the soil quality.
INTRODUCTION
Soil and water are two critical components of crop production due to their role for plant support, provision of water, and nutrient supply (Eckert, 2005). Frequent cultivation and low soil organic matter with arable cropping are among the factors that might limit crop production in Ohio. It has been documented that most soils in mid-west United States have lost about 30% to 50% of their carbon because of cropping (Fae et al., 2009). However, adoption of various crop and soil management practices such as frequent use of cover crops and tillage practices (no-till) have been identified to be valuable in sequestering carbon and replenishing the overall soil quality of the soil (Lal, 2002; Navas et al., 2011).
Cover crops can increase soil aggregate stability due to increased soil organic matter, and in combination, these can reduce erosion (Carter, 2002; Kaspar et al., 2001), improve soil physical properties such as higher water infiltration rate (Roberson et al., 1995), reduce loss of nutrients through runoff and leaching (Ruffo et al., 2004), and increase carbon sequestration (Reicosky & Forcella, 1998). The study by Fae et al. (2009) on forage cover crop integration into a no-till corn silage crop system in Ohio found that a single season of
34 livestock exclusion and use of forage cover crops resulted in reduced SPR equivalent to a non-grazed treatment without cover crop.
Certain forage species could be valuable in providing soil conservation and improvement roles. Inclusion of legumes in a mixture, reduces nitrogen fertilizer requirements, improves forage quality, and improves animal performance. Inclusion of grasses in a mixture can help prolong the life of a stand because they tend to persist longer and are more tolerant to mismanagement than legumes (Sulc & Barker, 2005). Therefore good cropping practices that ensure land cover protection are of great importance due to benefits such as reduced runoff, reduced erosion, improved water infiltration, reduced compaction, and improved soil organic matter. However, improving the cropping land for sustainable production is challenging. One of the challenges being successful establishment of certain forage cover crops. Establishment depends on many factors such as climate and soil nutrient availability.
Fertilizer application such as P and N can help to improve emergence and seedling vigor in low fertility soils (Barker et al., 2012). Nitrogen for instance is considered the most limiting nutrient element in forage agriculture (Barker & Collins, 2003). Application of fertilizer N has been observed to have variable effects particularly in seedling emergence, where some studies have reported reduced emergence from N fertilizer, especially if weed populations are high (Barker et al., 2012). In addition, P fertilizer is also crucial during forage establishment and seedling emergence responses. The fundamental mechanism of
P response to grass and legumes lies in its ability to stimulate root growth (Teutsch et al., 35
2000). Fertilizer P should be applied to soil and incorporated before seeding because it has a very low solubility.
The first objective of this research was to evaluate the effect of various forage cover crop species under varying levels of fertilizer treatment on forage production (yield) and stand density. The second objective was to determine the effect of the same vegetation and fertilizer treatments on water infiltration and soil penetration resistance. The third objective was to evaluate various seed characteristics on germination and yield in the laboratory and greenhouse.
MATERIALS AND METHODS
Site description
The project started on 1 July 2015 at the Waterman Research Farm, Ohio State University,
Columbus, Ohio (40◦ 00’ N, 83◦ 02’ W, 236 m altitude). The field had been in cultivation for more than 20 years, with a history of corn-soybean cropping. The soil was a Crosby silt loam (fine, mixed, active, mesic aeric Epiaqualfs) (NRCS, 2016). This soil typically has an A-horizon (topsoil) of 20 cm depth, and a B-horizon (sub-soil) at 20-75 cm depth. These soils are typically somewhat poorly drained, have 0 to 6% slope, and are formed from loess or other silty material in the underlying loamy till (NRCS, 2016). Before planting, the area was covered by self-seeded weeds.
36
Design, procedures and management
Field experiment
The plot area was prepared by spraying with glyphosate and tillage with a rotary hoe to remove prior vegetation. Prior to application of fertilizer treatments, soil samples (30 cores per sample) were collected to 15 cm depth for soil chemical analysis. Samples comprised an aggregate for each replicate; four samples in total. Phosphorous fertilizer was applied as diammonium phosphate (DAP) (18-46-0), prior to planting at 150 kg/ha. For the nitrogen treatment, fertilizer was applied to sub-plots at 120 kg/ha, one month after seed planting as urea (46-0-0). Seed was evenly applied to the experimental units by broadcasting. Seed rates and characteristics are shown in Table 2. The seed treatments included; Cenchrus cilliaris (buffel grass), Brachiaria deflexa (brachiaria), Eragrostis teff
(teff) and Glycine max (soybean).
The study employed a split plot design with two factors. The main plot factor was forage species, which included five vegetation treatments, namely buffel grass (predominantly weeds), Brachiaria, Eragrostis teff (teff), soybean (Glycine max) and the unplanted (bare) control treatment. The subplot factor was fertilizer, which included three treatments, namely P as triple superphosphate, N as urea, and an unfertilized control. Therefore each replication comprised of five main plots (vegetation treatments) and three subplots
(fertilizer treatments) making a total of 15 experimental units. There were four replications as complete blocks, making a total of 60 experimental units for the overall experiment. 37
Each replication was 30 x 16.5 m, each main plot was 6 x 16.5 m, and each subplot
(experimental unit) was 6 x 5.5 m. The treatments were randomly assigned to experimental units using random numbers generated in Excel.
Weeds were removed from the unplanted control by mowing (on 15 August 2015) and glyphosate spray (on 20 August 2015). Weeds were removed from the brachiaria plots by hand weeding on (25 August 2015). Weeds were not removed from teff, buffelgrass, or soybean treatments.
Measurements
Baseline chemical status was measured by sampling soil in each block for determination of soil organic matter and chemical status in the laboratory.
SPR was measured using a digital penetrometer (Field Scout SC-900, Spectrum
Technologies, Inc, Aurora, IL), with a 1cm diameter head. In each subplot a total of five readings were taken making a total of 300 readings in the whole experiment. This was done two times during the experiment, namely, after seedling emergence and establishment (on
3 September2015) and at the end of the experiment (on 1 November 2015). The measurements were taken following rainfall, when the soil was at or near field capacity.
The soil penetrometer measures pressure and depth continuously, and the maximum depth measured was 40 cm. Soil samples were collected for determination of soil moisture content in each block. This was done gravimetrically by recording the initial wet weight at the time of sampling and the final dry weight after drying the samples for 48 hours at 50 38
◦C. Soil moisture measurement aimed at determining if differences existed between treatments that would affect soil penetration resistance measurements.
Water infiltration measurement was done using the Mariotte bottle techniques which use a
Mini Disk Infiltrometer (Decagon, Pullman, WA) to measure the unsaturated hydraulic conductivity. Measurement was done in each treatment five times. A suction rate of 2 cm was used. The mini disc infiltrometer was placed on a smooth spot in each treatment made to ensure a good contact between the soil and the infiltrometer. The infiltration was measured at 30 s intervals for 2 min and subsequently at 60 s intervals up to 10 min; thus one measurement took 10 minutes before commencing a second reading. Five readings were taken in each subplot treatment making a total of 300 readings in the whole experiment. The measurements were done after vegetation establishment (6 September
2015), and at the end of the experiment on 4 November 2015.
Forage species density was measured on 5 October 2015 using quadrats of 0.1 x 0.1 m for teff and buffel grass and 1 x 1m for soybean and Brachiaria.
Dry matter yield was measured in all plots using two 0.1 x 0.1 m quadrats on 25 October.
Herbage samples were dried at 60oC for at least 48 hr.
Germination test
Seed germination was measured in a temperature-controlled (30◦C in the day and 15◦C during the night) incubator for the three-week period 13 July to 5 August 2015. Each species had three replications. Each replication of buffelgrass had 50 seed, brachiaria had 39
50 seed in each replication, teff had 49-60 seed, while soybean had 30 in each replication.
Water was replenished for the germination blotter in each petri dish approximately daily.
The number of seeds germinated was recorded for each replication and cumulative germination percentage was calculated.
Green house experiment
The experiment was conducted at the Ohio State University greenhouse from September to December 2015, Columbus OH. The forage species were planted in 15 cm diameter pots with artificial media. The treatments (forage species) included, buffel grass with spikelets and without spikelets, teff (Eragrostis teff), which was coated with lime, brachiaria
(Brachiaria deflexa) which was coated with lime, and alfalfa (Medicago sativa). The source of fertilizer include N as urea (0.5 g/pot), P (0.25 g/pot), and K (0.25 g/pot) was applied one month after germination, to facilitate growth. Each of four species were planted to pots, and arranged in a completely randomized design with three replicates. The treatments were planted to a depth of about 3-5mm and watered daily. The effective sowing rates were; bare buffel grass seeds (1.5 g/m2), brachiaria seeds (100 g/m2), alfalfa (50 g/m2) and coated buffel grass (50 g/m2) respectively. The parameters measured include; number of seedlings emerged in each treatment after 30 days, establishment density (after 60 days), percent emergence rate, and yield at the end of the experiment (after 90 days).
40
Statistical Analyses
Treatment effects were analyzed using general linear model procedures of SAS. The experimental design was a two-factor factorial with a split plot restriction. There were four replications, arranged as complete blocks. Thus the following effects were included in the model: Yk(ij) = µ + αi + ek(i) + βj +αβij + ek(j) . Where; µ = grand mean, αi = is the effect of th th i level of forage species, ek(i) = is the main plot error term, βj = is the effect of j level of fertilizer, αβij = is the effect of the interaction between forage species and fertilizer, ek(ij) =
th th is the error term associated with the subplot factor, Yk(ij) = is the response of the i and j factors in the ij(k) combination. Mean comparison was done by Fishers Protected Least
Significant Difference (LSD) at P = 0.05. The LSD was calculated by multiplying the appropriate t-value by the standard error of the difference, as provided by the output for analysis of variance with means comparisons option.
RESULTS
Weather data
Rainfall for Columbus Ohio was higher in June followed by July, with the lowest precipitation in November (Table 3). The highest mean air temperature was measured in
July followed by June and August which had approximately equal mean air temperature.
The weather data also indicate relative humidity was higher in December, followed by
41
June. However, relative humidity did not vary much during the year. Solar radiation was higher in August. The data shows great variation in solar radiation between August and
December. July and August had the highest mean soil temperature.
Yield and density of forage cover crop species
The yield of forage cover crop species measured at the end of the experiment found significant differences (P < 0.0001) between species where teff had the highest yield, averaging 6712 kg/ha and the unplanted (control) treatment had the lowest mean yield 3410 kg/ha (Table
4). The other treatments had yield between these extremes. There was no effect of fertilizer or the fertilizer by species interaction on forage yield (Table 5).
The density of four cover crop forage species measured in October 2015 was significantly different between species (P<0.0001), where teff had the highest stand density with mean of (1293 m2) and soybean had the lowest (16 m2) and the difference was significant (Table
6). Buffel grass plot had the highest number of weed population since no buffel seedling emerged making its density to be higher than that of brachiaria (22 m2) and soybean (16 m2) but less than that of teff and the difference was significant. There was no significant difference in density between Brachiaria and soybean. The density of weeds (47 m2) in soybean treatment outnumbered the density of soybean itself (16 m2). There was no significant effect of fertilizer or fertilizer by species interaction (P>0.05) of forage cover crop species (Table 7). 42
Soil penetration resistance and water infiltration of different cover forage species
Soil Penetration resistance (SPR)
SPR in September 2015 showed significant effects (P<0.05) at some depths notably at 10 cm and 12.5 cm depth. (SPR) below 10 cm depth and above 15 cm depth showed no significant effects (P>0.05) (Table 8). Fertilizer or fertilizer by species interaction showed no significant effect (P>0.05) on penetration resistance at various depth at 10cm and
12.5cm depth (Table 10). Brachiaria showed the lowest penetration resistance as compared to other cover crop forage species (Table 9) at 12.5cm depth. At both depths, buffel grass was measured with high SPR, 963 kPa at 10cm depth and 1378 kPa at 12.5cm depth than all cover crop species and the difference was significant at 10cm depth (Table 9).
SPR measured in November found significant effects (P<0.05) at some depths notably at
22.5, 25, 27.5 and 30 cm depth (Table 11). There was no significant effect with penetration resistance measured below 20 cm depth and above 30 cm depth (P>0.05). Fertilizer or species by fertilizer interaction showed no significant effect (P>0.05) on soil penetration resistance (Table 13). At all depths that found significant effects, brachiaria had the lowest penetration resistance while the control treatment and teff was measured with the highest penetration resistance at the same depths (Table 12).
43
Water infiltration
Water infiltration as measured by Mariotte bottle in September, 2015 found significant effects between species (P<0.05). However, there was no significant effect between fertilizer (Table 15) or fertilizer by species interaction (P>0.05). Among all cover forage planted, brachiaria had the highest water infiltration and teff had the lowest (Table 14).
Buffel grass had higher water infiltration (5.033 x10-5 cm/s) as compared to soybean (2.969 x10-5 cm/s) and the difference was significant. On the other hand, soybean had higher water infiltration (2.969 x10-5 cm/s) as compared to teff (2.332 x10-5 cm/s) and the difference was significant.
Water infiltration measured in November found significant effects between species
(P<0.05) (Table 16), but no fertilizer or fertilizer by species interaction effect was observed
(P>0.05) (Table 17). Among the cover crops planted, brachiaria had the highest water infiltration as compared to other species and the lowest water infiltration was measured in soybean (Table 16). Buffel had higher water infiltration than teff and soybean and the difference was significant (Table 16). Teff had significant higher water infiltration 2.89 x10-5 cm/s than soybean 2.25 x10-5 cm/s.
The relationship plotted between SPR and water infiltration indicated higher water infiltration was correlated with lower SPR and higher SPR correlated with lower SPR as indicated with the linear regression line (figure 1) just as we expected. However, the relationship between forage mass (yield) and water infiltration gave a negative relationship 44
(figure 2) different from what was expected and the relationship between forage mass and
SPR (figure 3) also gave higher SPR with larger mass which was unexpected. This could be due to the reason that brachiaria soil measurements were made adjacent to the plants, whereas all other measurements were made at random. Thus the low for brachiaria might not fit the regression line as well because bare ground included in the yield measurement, was not included in the soil physical measurements.
Germination, population density (emergence) and yield of various grass and legume
seed characteristics
Germination test of four forage seed species conducted in the laboratory from July to
August 2015 (Table 18) indicated highest cumulative germination percent was measured in soybean seeds (97%) and teff (94%) while the lowest cumulative germination percent was measured in brachiaria (10%) and buffel grass (9%) (P<0.0001) (Table 19).
Four seed treatments from three species of buffel grass (with and without spikelet), brachiaria, and alfalfa were tested under greenhouse conditions and significant effect between species was observed (P<0.05) for emergence and yield. In average, buffel grass seeds without spikelet were measured with higher emergence (73%) than all other seed type (Table 20) and buffel grass with spikelet had the lowest emergence (12%). On the other hand, all three seed types planted had higher emergence than buffel grass seed with spikelet and the difference was significant.
45
The highest yield was measured with buffel grass planted with seeds without spikelet and the lowest yield was measured with buffel grass planted with spikelet seeds and the difference was significant (Table 21). Brachiaria had relatively higher yield than alfalfa and the difference was significant. On the other hand, alfalfa was measured with relatively higher yield (362 kgDM/ha) than buffel seed planted with spikelet (307 kgDM/ha) and the difference was significant.
DISCUSSION
Weather and climate
Weather and climate data for Columbus Ohio in 2015 was generally good where the spring of last year (March) started with 2.8 mm of rainfall and kept on increasing to 6.9 mm of rainfall in June. The experiment began with a relatively lower precipitation in July (4.3mm) as compared to that in June. However the amount of precipitation was enough to give good germination and subsequent establishment of planted species. On the other hand, the weather also favored high weed infestation on plots that had lower or no germination at all such as in buffel grass plot. There were some dry periods but these didn’t restrict growth.
There was a good solar radiation prior to experimental establishment and after establishment which is important for photosynthesizing plants.
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Cenchrus ciliaris
Cenchrus ciliaris commonly called buffel grass or African foxtail grass is a perennial grass that was planted using seeds. There was no seedling emergence with this cover crop species or if any was outcompeted with weeds that infested the plots and hence unrecognized.
Therefore this treatment changed to a weed plot treatment. Emergence failure could be associated with the seed characteristics. The germination test showed the lowest percentage cumulative germination (9%) as compared to other species. However, a greenhouse test on emergence between buffel grass with spikelet and without spikelet showed lower emergence on buffel grass seeds with spikelet (12%) as compared to those without spikelet
(73%). The yield under greenhouse test followed the same trend where buffel grass with spikelet was measured with the lowest yield whereas buffel grass with bare seeds was measured with the highest.
Literature shows seeds with impervious seed coat does not respond to germination quickly, however it can germinate once its seed coat is degraded (Barker et al., 2012). Despite the fact that the seeds were bought from a certified agent, however most seed sellers do not provide on the label the information on seed size and seed storage conditions applied during harvesting and processing (Barker et al., 2012).
Buffel grass treatment generally gave a higher yield of about 4.3 T/ha much higher than brachiaria and the control plot and the population density of 690 m2 higher than for brachiaria and soybean. Good yield could be due to good weed yield as a result of higher 47 weed population density. But also it could be due to less competition between plant species for moisture, light and space (Hopkins, 2000) since the entire plot was weed infested (less diversity)as compared to brachiaria and soybean that competed with weeds after emergence.
The relevance of soil compaction in agriculture lies on the fact that it can impose devastating effects on root development and crop yield (Lal & Shukla, 2004). Soil penetrometer resistance measured in September and November found significant effects between different forage cover crop species at some depths (P<0.05). Despite the fact that soil moisture affect soil penetration resistance, soil moisture measurement which was done simultaneously with SPR showed no significant difference between treatments (P>0.05).
Generally, it was observed that, SPR measured below 20 cm depth had lower compaction as compared to that measured above 20 cm depth. The SPR measured in buffel treatment in September was higher (963 kPa) as compared to other treatment plots. However SPR measured in November in buffel treatment was relatively lower than that for control treatment at various depths (Table 12). Higher SPR observed in September could be due to impeded root development and elongation (Unger & Kasper, 1994) hence lower ability of the weeds to reduce SPR as compared to other treatments in the early stage of the experiment.
48
A relatively lower SPR measured in November indicated that longer term experimental data might be required to measure real effects of certain cover crops in reducing compaction.
Water infiltration data measured in September and November showed significant effects of cover crops on water infiltration (P<0.05). In September, the buffel treatment had higher water infiltration (5.033 x10-5 cm/s) than soybean (2.969 x10-5 cm/s) or teff (2.332 x10-5 cm/s) and the difference was significant (Table 14). However water infiltration measured in November showed the buffel treatment to have lower water infiltration (5.29 x10-5 cm/s) than teff and soybean and the difference was significant (Table 16). Reduced water infiltration could be due to higher compaction as a result of surface sealing (Naeth et al.,
1991).
Eragrostis teff
Eragrostis teff commonly teff is an annual grass forage widely cultivated in Ethiopia where its leaf is a good livestock feed and the grain is used to make human food. In this experiment teff was planted by seed which were coated and seedling performed well in terms of emergence, growth and yield. Between all treatments, teff produced the highest yield of 6.7 T/ha and the difference was significant. Higher yield of teff could be due to its good emergence and stand establishment.
The population density counted in teff was the highest between all treatments with 1293m2 plant population. This could be due to its good germination rate under favorable conditions. 49
The germination test for various seed characteristics before field planting showed higher cumulative germination percent in teff (94%) as compared to brachiaria and buffel grass and the difference was significant. Teff had good emergence and establishment that out- competed the weed population where the weed population density was less than the teff population density.
SPR measurements in September indicated a lower soil penetration resistance (695 kPa) as compared to the buffel grass (Table 9) at 10 cm depths and the difference was significant.
Soil moisture measured simultaneously with soil SPR showed no significant effect between treatments and therefore lower penetration resistance measured in teff could be due to its good root characteristics in reducing compaction. SPR measured in November at various depths (Table 12) indicated a relatively low SPR in teff as compared to the control treatment, however the difference was not significant. Relatively low SPR measured in teff could be due to good soil structure as a result of good plant growth and establishment, root development and elongation.
One important soil-ecosystem function is to enhance infiltration of precipitation into the soil resulting in less surface runoff and erosion (Lal & Shukla, 2004). Water infiltration measurement in September gave a lower water infiltration in teff as compared to all treatment (Table 14). However, there was an increase in water infiltration measured in
November for teff compared to soybean (Table 16). Higher water infiltration in teff could be explained by an interaction between biological and physical mechanisms which create 50 good and stable soil structure with abundant macropores for quick water transmission (Lal
& Shukla, 2004). In addition, an increase in water infiltration from September to November suggested that longer term experimental data be done to measure the effective of a cover forage species in improving water infiltration and how that can vary between species.
Brachiaria deflexa
Brachiaria deflexa commonly brachiaria used in this experiment was a perennial grass planted as a main plot treatment by seeds which were coated. It is a productive species that is used for grazing and can also make a good hay. The performance of brachiaria in this study was not very good. Seedlings emerged but not in a substantial number therefore the yield measured at the end of the experiment was lower (3.5 T/ha) compared to all other species (Table 4). Lower yield could be due to poor seedling emergence and establishment.
However there were some good treatments that produced a good stand.
The population density counted was lower than that of teff and buffel but higher than that for soybean (Table 6). This was associated with poor emergence. The weed population in brachiaria was removed by hand weeding. The germination test done in the laboratory also gave a lower cumulative germination percent as compared to soybean and teff (Table 18).
However, under greenhouse test (Table 20) brachiaria emergence percent was relatively higher as compared to that of alfalfa and buffel with spikelet. The yield of brachiaria in a greenhouse was also higher (4 T/ha) than that of alfalfa (3.6 T/ha) and buffel grass planted with spikelet (3 T/ha) and the difference was significant (Table 21). 51
Despite poor emergence, population density and yield, SPR measured in September and
November indicated a lower SPR than all treatments at different depths (Table 9, 12). On average between all depths that showed significant effects the penetration resistance measured in brachiaria treatment in September and November was less than 1000kpa while all other treatment at a depth greater than 10cm the penetration resistance was above
1000kpa Table (9, 12). Soil moisture measured simultaneously with SPR showed no significant effect between treatment and therefore lower penetration resistance from brachiaria treatment could be due to its ability to create a good soil structure as a result of good rooting and increased organic matter content and enhancement of soil biological activity.
Water infiltration results from brachiaria treatment indicated higher water infiltration measured in September and November. In September for instance, brachiaria had the highest water infiltration than all cover crop forage species (Table 14). Water infiltration measured in November was higher than that for September and than all cover forage species measured in November and the difference was significant. Higher water infiltration in brachiaria could be due to lower SPR which indicates improved aggregate stability and good soil structure (Folorunso et al., 1992).
Glycine max
Glycine max commonly soybean is an annual crop which is used as a livestock feed and its grain as human food. Soybean treatment was planted with seeds and its performance in 52 terms of emergence and establishment and population density was poor. Despite the highest cumulative germination percentage (97%) when tested in germination chamber, its emergence in the field plot was very low and its population density was the lowest between all treatments and the population of weed in soybean was relatively higher than for soybean itself. Lower emergence could be due to failure to compete with the weed population.
However, the yield of soybean was relatively higher (5.8 T/ha) than that of buffel (4.9
T/ha), brachiaria (3.5 T/ha) and control treatment (3.4 T/ha) and the difference was significant. However soybean yield was a combination of soybean and its weed population.
SPR measured in September showed lower SPR in soybean as compared to buffel grass at
10 cm and the difference was significant (Table 9). In November, soybean was measured with less soil penetration resistance when compared to all treatment except with bracharia at all depths (Table 12). Soil moisture measured simultaneously with soil penetration resistance found no significant effects between treatment and therefore lower SPR could be due to other factors such as improved soil structure and alleviation of surface sealing by the cover crop species.
Water infiltration results in September for soybean was lower (2.969 x10-6 cm/s) than for brachiaria, buffel and control but higher than teff (2.332 x10-6 cm/s) and the difference was significant (Table 14). In November, water infiltration in soybean was also lower than all cover forage species planted and the difference was significant.
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Control
The control treatment received no cover crop forage species and it was mowed later during the experimental phase when the plots were infested with weeds and therefore it had a lot of litter accumulation. Therefore there was no population count in this treatment, however yield was harvested which mostly litter was accumulated on the ground as basal cover and it was the lowest compared to all treatments (Table 4). The yield in a control treatment didn’t vary significantly with that of brachiaria. .
SPR measured in September on the control treatment was relatively lower than that for buffel grass at 10cm and 12.5cm depth respectively (Table 9). However, the control treatment and soybean didn’t vary significantly in SPR measured in September at 12.5 cm depth (Table 9). The SPR measured in November indicated highest SPR in the control treatment as compared to all treatments (Table 12). Soil moisture measured simultaneously with SPR showed no significant effect between treatments. Therefore the relatively lower
SPR measured in September could be due to litter accumulation after mowing. High SPR later during the experiment could be due to lack of plant growth on the control treatments which had a bare soil as compared to other treatments.
Water infiltration measured in September indicated higher water infiltration in the control treatment (6.405 x10-5 cm/s) than all treatment except for brachiaria (6.931 x10-5 cm/s) which didn’t vary significantly. Water infiltration measured In November showed higher water infiltration in the control treatment (6.55 x10-5 cm/s) than all treatments (Table 16 54
) except for brachiaria and the difference was significant. Higher water infiltration in the control treatment could be due to litter accumulation in the treatment plot after mowing.
Fertilizer Nitrogen (N) and Phosphorus (P)
Fertilization is one of the most important practical management tools that farmers or managers can use to correct nutrient deficiencies in the soil and improve production
(Barker & Collins 2003). Nitrogen in particular is described in general terms as the most limiting nutrient in forage agriculture largely due to its use in plant growth for about 60% dry matter and highly leached (Barker and Collins 2003). On the other hand, P fertilizer is crucial during seedling emergence and forage establishment. The fundamental mechanism of P response to grass and legumes lies in its ability to stimulate root growth (Teutsch et al., 2000).
In this experiment N and P were applied as subplot treatments. P was applied prior to seeding due to solubility reasons while N was applied after seedling emergence about one month post planting. However, there was no significant effect of fertilizer and fertilizer by species interaction on yield, density, SPR and water infiltration. Therefore treatment averages across parameters are presented (Table 5, 7, 10, 13, 15, 17).
Unfertilized (control)
Unfertilized plot or the control treatment was applied as a subplot treatment effect.
However, there was no significant effect of subplot treatment (fertilized and unfertilized
55 treatment) and species by fertilizer or unfertilized effect. Therefore treatment averages across parameters are presented (Table 5, 7, 10, 13, 15, 17). The unfertilized treatment was applied to measure treatment effect against the fertilized effect.
Conclusion
Our results indicated good performance of cover forage species in terms of emergence, density and yield. The results also indicated the potential of cover forage species in altering soil physical properties such as water infiltration and SPR where significant effects was measured for water infiltration and SPR at some depths. Our results also showed water infiltration to correlate with SPR where higher water infiltration was direct related to low
SPR. Therefore improved soil physical characteristics through biomass production and soil organic matter improvements can reduce vegetation and soil degradation and enhance the overall sustainability of the soil quality. This is of paramount to livestock farmers to ensure resilience and sustainability of their grazing lands while maintaining productivity of goods and services from land resources.
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Table 2: Seed rates and characteristics used for the Ohio field study (Exp.1).
Species Sowing Sowing rate 100 seed germination Coat
rate weight
kg/ha seed/ha g (%)
buffel grass 5 2,500,000 0.2 x Not
coated
teff 9 8,333,333 0.06 V Coated
(50%)
brachiaria 10 476,190 2.1 V Coated
(18%)
soybean 100 666 15 V Not
coated v- Seedling emergence observed x- No seedling emergence observed
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Table 3: Mean air temperature, total precipitation, relative humidity, solar radiation and soil temperature recorded in Columbus, OH for the year 2015
Mean/month
Month Air temp. Precipitation Rel.humidity Solar rad. Soil temp.
◦C (mm) % W/m2 ◦C
January -3.5 2.3 78.58 6.89 1.54
February -7.2 1.0 73.86 9.89 0.24
March 3.3 2.8 71.77 13.26 3.58
April 12.1 3.0 65.57 16.02 11.72
May 19.8 2.8 68.13 19.72 18.81
June 21.7 6.9 80.43 16.22 23.09
July 22.6 4.3 79.23 18.17 25.29
August 21.9 2.0 74.16 19.85 25.04
September 20.6 2.3 72.97 16.48 22.5
October 12.9 2.0 70.74 11.56 15.49
November 8.9 1.5 70.83 8.15 10.16
December 6.5 4.1 84.13 4.02 7.55
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Table 4: Yield of cover forage species at the end of Exp.1 in October 2015. Means followed with the same letter are not significantly different (P>0.05).
Treatments Yield (kg DM/ha) t-groupings Teff 6712 A
Soybean 5840 AB
Buffel 4930 B
Brachiaria 3522 C
Control 3410 C LSD (0.05) 950.31
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Table 5: Yield of cover forage species at the end of Exp. 1 in October 2015 under various fertilizer treatments.
Fertilizer Yield (kgDM/ha)
Nitrogen 5106
Phosphorus 4640
Control 4901
LSD NS
NS-Not significant
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Table 6: Population density of four cover forage species measured in October 2015. Means followed with the same letter are not significantly different (P>0.05). In the parentheses are the weed population number for the respective treatments. Species Density (m2) t-groupings
Teff 1293 (23) A
Buffel* (-) (690) B
Brachiaria** 22 (0) C
Soybean 16 (47) C
Control *** (-)
LSD 209.78
(*) weed population, no buffel seed emerged. (**) plots hand weeded to remove weeds (***) weed density was not measured
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Table 7: Population density of cover forage species at various fertilizer treatments measured in October 2015 (Exp. 1)
Fertilizer Density (m2)
Nitrogen 428
Phosphorus 476
Control 500
LSD NS
NS-Not significant
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Table 8: ANOVA for soil penetration resistance measured in September, 2015
Depth (cm) Species Fertilizer Species*Fertilizer
0-7.5 NS NS NS
10 0.0169 NS (0.0881) 0.0712 (NS)
12.5 0.0398 NS NS
15 0.0846 (NS) NS NS
17.5 0.0706 (NS) NS NS
20 NS NS NS
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Table 9: Soil penetration resistance and soil moisture measured in September 2015. Means with the same letter within column are not significantly different (P>0.05). Species LSMEANS (kPa) LSMEANS (kPa) Soil
(10cm depth) (12.5cm depth) moisture
(g/100g)
0-15 cm
buffel 963 a 1379 a 20
control 728 ab 1262 a 18
Soybean 715 b 1264 a 16
teff 695 b 1240 a 16
Brachiaria 683 b 891 b 18
LSD (0.05) 236.37 282.49
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Table 10: Soil penetration resistance at various fertilizer treatment measured in September 2015 (Exp. 1).
Fertilizer LSMEANS (kPa) LSMEANS (kPa)
(10 cm depth) (12.5 cm depth)
Nitrogen 1318 1741
Phosphorus 1228 1635
Control 1075 1576
LSD NS
NS-Not significant
65
Table 11: ANOVA for soil penetration resistance measured in November 2015 (Exp. 1)
Soil Depth (cm) Species Fertilizer Species*Fertilizer
0-20 NS NS NS
22.5 0.0443 NS (NS)
25 0.0104 (*) NS NS (0.0622)
27.5 0.0028 (**) NS NS (0.0684)
30 0.0009 (***) NS NS (0.0592)
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Table 12: Soil penetration resistance and soil moisture measured in November 2015 in (Exp. 1). Means with the same letter within column are not significantly different (P>0.05).
Species LSMEANS LSMEANS LSMEANS LSMEANS Soil
(kPa) (kPa) (kPa) (kPa) moisture
(22.5 cm (25 cm (27.5 cm (30 cm (g/100 g)
depth) depth) depth) depth) 15-30 cm
control 1629 a 1642a 1713a 1522a 20
Teff 1581 a 1522 a 1363 ab 1321 a 20
buffel 1473 a 1437 a 1307ab 1201 ab 19
soybean 1222 ab 1222a 939bc 822 bc 22
brachiaria 789 b 659 b 604 c 450 c 21
LSD (0.05) 597.39 560.88 540.95 493.69
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Table 13: Soil penetration resistance under various fertilizer treatments measured in November 2015 (Exp. 1).
Fertilizer LSMEANS LSMEANS LSMEANS LSMEANS
(kPa) (kPa) (kPa) (kPa)
(22.5 cm depth) (25 cm depth) (27.5 cm (30 cm
depth) depth)
Nitrogen 1353 1386 1263 1003
Phosphorus 1354 1277 1146 1103
Control 1310 1226 1147 1084
LSD NS NS NS NS
NS=Not significant
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Table 14: Water infiltration measured by Mariotte bottle in September 2015 (Exp. 1). Means with the same letter within column are not significantly different (P>0.05).
Treatments KLSMEANS (cm/s) t-groupings
Brachiaria 6.931 x 10-5 A
Control 6.405 x 10-5 A
Buffel 5.033 x 10-5 AB
Soybean 2.969 x 10-5 BC
Teff 2.332 x 10-5 C
LSD (0.05) 2.14 x 10-5
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Table 15: Water infiltration measured by Mariotte bottle under various fertilizer treatments in September 2015 (Exp. 1).
Fertilizer KLSMEANS (cm/s)
Nitrogen 5.012 x10-5
Phosphorus 4.463 x10-5
Control 4.665 x10-5
LSD NS
NS=Not significant
70
Table 16: Water infiltration measured by Mariotte bottle in November 2015 (Exp. 1). Means with the same letter within column are not significantly different (P>0.05). Treatments KLSMEANS (cm/s) t-groupings brachiaria 9.07 x10-5 A
control 5.73 x10-5 B
buffel 5.29 x10-5 BC
Teff 2.89 x10-5 CD
Soybean 2.25 x10-5 D
LSD (0.05) 2.71 x10-5
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Table 17: Water infiltration as affected by fertilizer measured by Mariotte bottle technique in November, 2015.
Fertilizer KLSMEANS (cm/s)
Nitrogen 3.206 x10-5
Phosphorus 4.218 x10-5
Control 3.439x10-5
LSD NS
NS=Not significant
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Table 18: Cumulative germination percent of four cover forage seed species tested in the germination chamber from July, 15 to August , 5 2015.
Date (2015) Species Reps 15 16 20 21 26 29 31 5 Un Tota germinate l d (%) JU JU JU JU JU JU JU A U 1 46 95 95 95 95 95 95 95 5 100 Teff 2 41 93 93 93 93 94 94 94 5 100 3 40 93 93 93 93 93 93 93 6 100 Mea 42 93 93 93 93 94 94 94 5 100 n 1 33 76 93 93 93 93 93 93 6 100 Soybean 2 40 96 10 10 10 10 10 10 0 100 0 0 0 0 0 0 3 66 10 10 10 10 10 10 10 0 100 7 0 0 0 0 0 0 0 Mea 46 91 97 97 97 97 97 97 2 100 n 1 0 0 0 2 4 4 4 6 94 100 Brachiari 2 0 0 0 0 0 2 2 8 92 100 a 3 0 0 0 6 16 16 18 18 82 100 Mea 0 0 0 2 6 7 8 10 89 100 n Buffel 1 0 0 0 2 6 8 8 12 88 100 2 0 0 0 0 4 4 4 6 94 100 3 0 0 6 6 6 6 6 10 90 100 Mea 0 0 0 2 5 6 9 9 90 100 n
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Table 19: Cumulative germination percent means of four cover forage seed species tested in the germination chamber 2015. Means with the same letter within the column are not significantly different. Species Mean germination (%) t-Grouping
Soybean 97.77 A
Teff 94.57 A
Brachiaria 10.67 B
Buffel 9.33 B
LSD (0.05) 8.0272
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Table 20: Mean emergence of four cover forage species planted in a greenhouse from September to December 2015 Columbus Ohio. Means followed by the same letter within the column are not significantly different (P>0.05).
Species Mean emergence (%) t-groupings
Buffel bare 73.33 A
Brachiara 63.33 A
Alfalfa 58.67 A
Buffel coated 12.33 B
LSD (0.05) 16.516
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Table 21: Mean yield of four cover forage species planted in a greenhouse from September to December 2015 Columbus Ohio. Means followed by the same letter within the column are not significantly different (P>0.05). Species Mean yield (kgDM/ha) t-groupings
Buffel bare 775.67 A
Brachiaria 459.67 B
Alfalfa 362.33 BC
Buffel coated 307.83 C
LSD (0.05) 146.99
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Figure 1: Linear regression line showing the relationship between soil penetration resistance and water infiltration. The values are the means for SPR at 22.5cm depth (November) and water infiltration means (September) 2015.
Relationship between SPR and water infiltration 1800 1600 1400 1200 1000 800 y = -6E+06x + 1640.8 R² = 0.1416 600 400 200
Soil penetration Soil resistance (kPa) 0 0.00E+00 1.00E-05 2.00E-05 3.00E-05 4.00E-05 5.00E-05 6.00E-05 7.00E-05 8.00E-05 Water infiltration (cm/s)
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Figure 2: Linear regression line showing the relationship between forage mass and water infiltration. The values are the means yield (November) and water infiltration means (September) 2015.
Relationship between yield and water infiltration 8000 7000 6000 5000 4000 3000 y = -7E+07x + 8169.4 R² = 0.9653 Yield Yield (kgDM/ha) 2000 1000 0 0.00E+00 1.00E-05 2.00E-05 3.00E-05 4.00E-05 5.00E-05 6.00E-05 7.00E-05 8.00E-05 Water infiltation (cm/sec)
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Figure 3: Linear regression line showing the relationship between forage mass and soil penetration resistance. The values are the means for SPR at 22.5cm depth (November) and water infiltration means (September) 2015.
Relationship between yield and SPR 8000
7000 y = 1.3807x + 3034.3 6000 R² = 0.1097 5000 4000 3000
Yield Yield (kgDM/ha) 2000 1000 0 0 200 400 600 800 1000 1200 1400 1600 1800 Soil Penetrometer Resistance (kPa)
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CHAPTER 4:
COVER CROP EFFECTS ON RANGELAND AND CROPLAND SOILS IN
TANZANIA
ABSTRACT
Drought, continuous arable cropping, and overstocking are among the factors limiting crop and livestock agriculture in Tanzania. Two experiments were conducted at Kongwa Pasture
Research Center-Dodoma, on sites with a history of grazing land and cropland use, respectively. Both experiments used a two factor factorial with split plot restriction. For each experiment, the main factor was species at four level and the subplot factor was fertilizer at three levels. The species sown on the rangeland site included, Cenchrus ciliaris,
Chloris gayana, Stylosanthes scabra, and the unplanted control while the cropland species treatments were, Eragrostis teff, Vigna inguiculata, Sorghum vulgare and the unplanted control. Fertilizer treatments applied to rangeland and cropland sites was DAP
(diammonium phosphate, 46% P2 O and 18% N) at the rate of fert-20, fert-30, fert-0 kg.
There were four replications as randomized complete blocks making 48 experimental units in total at each site. The measurements included, soil chemical status, seedling emergence, plant density, plant cover, yield, soil penetration resistance, soil moisture, and water infiltration. Species treatments were significantly different for yield, soil penetration resistance (SPR) at some depths, water infiltration, population density, emergence, and
80 cover for both experiments (P<0.05). Fertilizer treatments were significantly different in yield, water infiltration and soil penetration resistance for both experiments (P<0.05).
However, fertilizer had no significant effects on emergence, cover, population density, and soil moisture. There was a species by fertilizer interaction effect (P<0.05) in yield and soil penetration resistance at both rangeland and cropland sites. Our results shows plant vegetation has the potential to alter soil physical properties such as water infiltration and soil compaction through improved cover and biomass production.
INTRODUCTION
Drought, continuous arable cropping, and overstocking are among the factors limiting crop and livestock agriculture in Tanzania, as they contribute to soil nutrients depletion and erosion (Mtengeti, 2015; Boonman, 1992), especially in degraded lands that are shallow, infertile and have low organic matter. Rangelands in particular are described to be in a state of ecological adjustment driven by factors such as climate, the impact of fire, grazing animals, anthropogenic forces, and the interaction between trees and under-story vegetation (Mtengeti, 2015). Indigenous species are the most adapted forages however due to degradation, some range improvements techniques such as reducing bush encroachment and water infiltration enhancement is important in order to increase their productivity and quality (Shemaghinde et al., 2015).
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Most of the grazing lands (rangelands) are overstocked and hence suffer degradation such as soil erosion, biodiversity loss, reduction in biomass production and less plant cover
(Mtengeti, 2015). Such changes in rangeland condition due to degradation lead to reduced soil aggregate ability, soil fertility and soil organic matter. However, a sustained crop and livestock production requires improved water relations. Therefore, in most cases the most limiting factor for primary biological production is water (Mtengeti, 2015). While 40% of the Tanzania land area receives ≤ 600 mm/year of rain fall where, vast areas of central
Tanzania, such as Kongwa-Dodoma receive ≤ 450 mm/year (Mtengeti, 2015). While these semi-arid areas of central Tanzania receive low annual rainfall, likewise these areas make a large part of the country that practice livestock production. Due to overstocking and long dry periods, most of these areas have lost their vegetation cover and biomass production is low. Therefore techniques that enhance water infiltration, such as increasing vegetation cover via oversowing of suitable forage cover, are of significant value.
On the other hand, failure of agriculture systems to comprehend the impacts of erosion as well as intensive weathering under hot-humid conditions, has led to wide spread of poor and highly eroded, infertile soils all over the tropics and subtropics (Ochse et al., 1961).
Under these production systems, optimum production of crops is affected by application of fertilizer and amendments of soils. However, to utilize fertilizer application to its advantage, measures to restrict or decrease losses from leaching and erosion, water
82 relations improvement, maintenance of soil organic matter, rehabilitation of degraded soils and to reclaim waterlogged or saline soils are crucial (Ochse et al., 1961).
A close association between soil fertility and productivity occurs in the grass-soil-crop- complex, especially under livestock grazing (Boonman, 1992). The water infiltration rate can be significantly higher in ungrazed than grazed areas (Allington & Valone, 2010).
However, cover crops can have a significant role in improving soil quality (Navas et al.,
2011), by increasing soil aggregate stability, due to increased soil organic matter, and reduce erosion (Kaspar, 2001); (Carter, 2002) and facilitate water infiltration to the soil and soil compaction reduction.
The objective of this study was therefore, to evaluate the effects of cover forage and crop species under varying level of fertilizer on seedling emergence, plant density, vegetation cover, dry matter yield, soil compaction and water infiltration.
MATERIALS AND METHODS
Site description
The experiment was conducted at Kongwa Pasture Research Center, located in Kongwa
District, Dodoma Region in central Tanzania (6oº - 6º6'S; 26º22' - 36º30'E ; 1067 m a.s.l.).
The area is located at about 65 km east of Dodoma town, along Dar-es-Salaam Road and
22 km north of Kongwa town. The area is characterized by small hills and undulating
83 plains. The soils are mainly sandy loams, but vary from hill tops to valley bottoms. Pallid soils occur on the hills, red soils on slopes, and limited calcareous soil in depressions. The area is in the semi-arid zone, with a mean annual rainfall of about 500 mm, which falls between December and April. Rainfall is unimodal, erratic, and poorly distributed with high variability within and between seasons. The rainy season is characterized by short dry spell in January or February which is often detrimental to crop production. The average minimum temperature is 150 C and average maximum temperature is 300 C. The hottest month is November, while the coolest month is August. The vegetation is typified by
Acacia woodland dominated by Acacia and Commiphora species. Albizzia and Euphorbia species are widespread. Scattered baobab trees (Adonsonia digitata) > 10 m height are a characteristic feature of the landscape.
Design procedures and Management
Experiment II: Rangeland
Experiment II started on 29 December 2015. The area was previously uncultivated and was dominated by native forage species. The main species dominating the area included;
Aristida species, kongwa weed, Solanum species, Urochloa species, Macrotyloma, Sida alba, Cynodon dactylon, and Brachiaria species. In this study, the native vegetation was
84 removed by hand hoe, and then species treatments (except for buffel grass) were established from seed by broadcast sowing, or oversowing.
The study used a split plot design with four replicates as complete blocks. The blocks were laid down across slope. The main plot treatments were forage species, which include
Cenchrus ciliaris (buffelgrass), Chloris gayana (Rhodes grass), Stylosanthes scabra
(Stylo) and the control treatment (unsown). The subplot treatments included two rates of fertilizer as DAP (diammonium phosphate, 46% P2O and 18% N) (at the recommended rate of 20 kg fertilizer/ha, 1.5 times the recommended rate 30 kg fertilizer/ha, and an unfertilized control (Fert-20, Fert-30, and Fert-0, respectively). The whole experiment comprised 48 experimental units. Each main plot treatment was 12 x 8 m (96 m2) while each subplot treatment was 8 x 4 m (32 m2).
The forage species sowing rates were: Rhodes grass 3 kg/ha, Stylo 5 kg/ha, while Buffel grass was, planted using tillers (6 m-2). The seeds and fertilizer were applied by broadcasting. The fertilizer was applied on 7 January, 2016. Forage seed was planted on
11 January 2016. Water spreading structures were applied in all treatment plots to reduce runoff and erosion.
Experiment III: Cropland
Experiment III started on 30 December 2015. The area has been previously cultivated for grain mainly maize for more than three years. The main species dominating the area 85 included; Dactylosternium species, “kongwa weed”, Solanum species, Urochloa species, macrotyloma, Sida alba, Cynodon dactylon, and Brachiaria species. . In this study, broadcast sowing, or oversowing and drilling was used where the native vegetation was removed by a tractor cultivation.
The study used a split plot design with four replicates as complete blocks. The blocks were laid down across slope. The main plot treatment were cover crops which include; cow pea,
Teff, sorghum and the control (unplanted). The subplot treatments included two rates of fertilizer as DAP (46% P2O and 18% N) at the recommended rate of 20 kg fertilizer/ha, 1.5 times the recommended rate 30 kg fertilizer/ha, and an unfertilized control. The whole experiment comprised 48 experimental units. Each main plot treatment was 12 x 8 m (96 m2) while each subplot treatment was 8 x 4 m (32 m2).
The cover crop species sowing rates were: Cow pea legume 30 kg/ha, Teff grass 15 kg/ha and sorghum 19 kg/ha. The seeds and fertilizer were applied by broadcasting (teff,) and drilling (cow pea and sorghum). The fertilizer was applied on 7 January 2016. Cover crop seed was planted on 11 January 2016. Water spreading structures were applied in all treatment plots to reduce runoff and erosion.
Measurements
Baseline chemical status was measured in January 2016 by sampling soil in each block for determination of soil pH, soil physical properties such as particle size determination and soil organic matter and chemical properties (soil nutrients) such as N, P and K in the 86 laboratory. Soil pH was determined potentiometrically in water as described by Mclean
(1982), where the pH of soil sample was determined using a pH meter. Particle size analysis was determined by Bouyoucos hydrometer method as described by Bouyoucos (1962), where the textural class was determined by USDA textural class triangle (Estefan et al.,
2013). Total N was determined by Kjeldahl method (Jones, 1991). Extractable P was determined according to Bray-1-method (Olsen & Sommers, 1982). Exchangeable K was determined by flame photometer method (Rhoades, 1982). Soil organic C was determined as described by Walkley (1947).
Soil penetration resistance was measured using a digital penetrometer (Field Scout SC-
900, Spectrum Technologies, Inc, Aurora, IL), with a 1 cm diameter head. In each subplot, measurement comprised an average of five sub-sample readings, 240 readings in total.
Measurements were made near to the end of the experiment on April 2016. The measurements were made when the soil was at or near field capacity. The soil penetrometer measured pressure per depth, and the maximum depth measured was 40 cm. Soil samples were collected for determination of soil moisture content in each block. This was done gravimetrically by recording the initial wet weight at the time of sampling and the final dry weight after drying the samples for 48 hr at 50 ◦C. Soil moisture measurement aimed at determining if differences existed between treatments that would affect soil penetration resistance measurements.
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Water infiltration was measured using the Mariotte bottle techniques which use a Mini
Disk Infiltrometer to measure the unsaturated hydraulic conductivity. Measurements were repeated five times in each plot. A suction rate of 6 cm was used, however a suction rate of 2 cm was necessary for some measurements due to a sandy soil. The mini disc infiltrometer was placed near a plant on a smooth spot in each treatment made to ensure a good contact between the soil and the infiltrometer. The infiltration was measured at 30 s intervals for 2 minutes and then at 60 s for 10 minutes, which made one measurement of
10 minutes duration before commencing a second reading. Five readings were taken in each subplot treatment making a total of 240 readings in the whole experiment. The measurements were done after vegetation establishment. The volume of water infiltrated was transformed into the model to determine the unsaturated hydraulic conductivity
(Figure 7).
Seedling emergence was measured in all treatments using quadrats of 1 x 1 m. This was done at approximately one month after planting, on February 2016 just after vegetation establishment. The final stand count was measured near the end of the experiment in April
2016.
A visual assessment of vegetation cover was done on 30 March 2016 as a consensus between three observers and recorded in percent for each treatment. The assessment scored the overall vegetation cover in each treatment and the proportional of sown species to herbage mass in percent. 88
Dry matter yield was estimated in all treatment where a quadrat of 0.5 x 0.5m was used to sample the biomass that was used for measurement. However, yield measurement for sorghum was determined by harvesting an area of 1m*3m and a chopped sample was taken and weighed fresh.
Statistical Analyses
Treatment effects were analyzed using general linear model procedures of SAS. Both experiments comprised a randomized complete block design, with split-plot restriction on the randomization. The model included the following effects: Yk(ij) = µ + αi + ek(i) + βj +αβij
th + ek(j) . Where; µ = Grand mean, αi =is the effect of i level of forage species ek(i) = is the
th main plot error term, βj = is the effect of j level of fertilizer αβij = is the effect of the interaction between forage species and fertilizer ek(ij) = is the error term associated with the
th th subplot factor Yk(ij) = is the response of the i and j factors in the ij(k) combination. Mean comparisons were done using a Fishers Protected Least Significant Differences (LSD) at P
= 0.05. The LSD was calculated by multiplying the appropriate t-value by the standard error of the difference, as provided by the output for analysis of variance with means comparisons option.
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RESULTS
EXPERIMENT II-RANGELAND
Weather data
Generally the location where the experiment was located had low annual rainfall. The weather data for the year 2015 recorded at the research site shows lower rainfall which started in November and ended in March (Table 22). April and May 2015 received no or just trace amount of rainfall. The dry season for the previous year started in April and ended in October. However, the rainfall in this year was relatively higher than last year in almost all months since the start of the experiment. This enhanced good seedling emergence and establishment of forage species planted and produced a larger biomass. A trace amount of precipitation was recorded in April 2015 while this year there was a higher amount of rainfall (14.16 mm) in April. However, the distribution and frequency of rainfall is poor which affect crop production.
Grazed land soil characteristics
The soil was characterized by a sandy clay texture class with relatively slight acidic soil with an average pH of 6.5 which is satisfactory for most crops (Table 34). Nitrogen determination found an average of 0.24%, with A low soil organic matter of 0.61 % and low soil phosphorous content of 5.92mg/kg . The basic cation tested (K+) was measured with an average of 0.74 Cmol/kg.
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Rangeland seedling emergence and population density
Seedling emergence measured in February 2016 showed significant effects between forage cover species (P<0.05). Stylo had higher emergence, 30 plants m-2 as compared to buffel grass (19 m-2) and Rhodes grass (11 m-2) (Table 23). Buffel grass had higher emergence
(19 m-2) than Rhodes grass (11 plants m-2), however the difference was not significant.
Fertilizer and species by fertilizer interaction showed no effects on emergence of forage cover crops species (P>0.05).
The population density estimated in April 2016 showed significant effects between species
(P<0.05). Buffel grass had significantly higher population density (137 plants m-2 ) as compared to Rhodes grass (58 m-2) and stylo (54 m-2) (Table 27). Rhodes grass density
(58 plants m-2) was not significantly different than stylo (54 plants m-2). The species by fertilizer interaction was not significant (P>0.05).
Rangeland biomass production
Yield of range forage cover crop species showed significant effects between species, fertilizer, and species by fertilizer interaction (P<0.05). Buffel grass had higher yield (1.2 tons ha-1) as compared to other forage cover crop species (Table 24) and control had the lowest yield (0.3 tons ha-1). However buffel grass and Rhodes grass didn’t vary significantly in yield where Rhodes grass produced 1.1 tons ha-1. Stylo had higher yield
(0.7 tons ha-1) as compared to control (0.3 tons ha-1).
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Rangeland biomass production was also affected by fertilizer and the species by fertilizer interaction. The Fert-30 treatment had higher yield than Fert-20 or Fert-0 (Table 25). The
Fert-30 treatment had an average of 1.2 tons ha-1 while Fert-20 and Fert-0 gave 0.76 and
-1 0.6 tons DM ha , respectively. However, the Fert-20 and Fert-0 yields were not significantly different
The species by fertilizer interaction effect gave higher yield between all species at Fert-30 the higher rate (30 kg ha-1) followed by 20 kg ha-1 and the control (0 kg ha-1 ) had the lowest yield except for the unplanted treatment (Table 26; Figure 5). Buffel grass gave the highest yield (1.8 tons ha-1) at Fert-30 as compared to all species fertilized at the same rate and stylosanthes had relatively lower (1.2 tons ha-) than all species at the same rate of fertilizer applied (Table 26). On the other hand, stylo gave the lowest yield (0.4 tons ha-) between all species at Fert-0 and buffel grass had the highest (0.9 tons ha-) followed by Rhodes grass (0.6 tons ha-) at Fert-0.
Rangeland forage herbaceous cover and proportion of sown species.
Forage vegetation cover measured in March 2016 showed significant effects between species (P<0.05). However, the fertilizer main effect and the species by fertilizer interaction showed no effects on vegetation cover (P>0.05). Buffel grass had higher percentage cover (74%) as compared to all treatments and the control had the lowest (4%)
(Table 28). However the difference in vegetation cover between Rhodes grass (55 %) and stylo (54 %) did not vary significantly. 92
The proportional of sown species showed no significant effects between species (P>0.05) therefore average mean were provided (Table 28). On average buffel grass had higher proportional of sown species (40%) as compared to stylo (14%) and Rhodes grass (1%).
Soil penetration resistance and water infiltration of different forage cover crop
species
Soil penetration resistance (SPR)
Soil penetration resistance as measured by soil penetration resistance showed significant effects at 2.5, 5, 7.5, and 10 cm depth (P<0.05). However, fertilizer showed no significant effects while species by fertilizer interaction showed significant effect at 7.5 cm depth
(Table 29). Buffel grass had the lowest soil penetration resistance 278, 467, 770, and 907 kPa at 2.5, 5, 7.5, and 10 cm depth, respectively, while the control treatment had the highest soil penetration resistance 655, 958, 1201, and 1399 kPa at the same depths and the difference was significant (Table 30). The penetration resistance increased with depth.
Stylo had lower penetration resistance, 428, 709, 969, and 1158 kPa as compared to Rhodes grass which measured 630, 928, 1162, and 1344 kPa respectively at the same depths that had significant effects between species. Rhodes grass had lower penetration resistance as compared to the control and the resistance increased with depth, however the difference was not significant.
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The species by fertilizer interaction showed significant effect at 7.5 cm depth where buffel grass (761 kPa) and stylo (809 kPa) at Fert-30 had lower soil penetration resistance as compared to the same species at Fert-20 or Fert0 (Table 31; Figure 6). Unfertilized buffel grass plot had 821 kPa while for Fert-20 buffel grass had 728 kPa. Stylo had lower penetration resistance at Fert-30 (809 kPa) than at Fert-0 (997 kPa) or Fert-20 (1100 kPa)
(Table 31). Unfertilized Rhodes grass had higher soil penetration resistance (1166 kPa) than Rhodes grass at 20 kg/ha which measured 1146 kPa (Table 31).
Soil moisture measured simultaneously with soil penetration resistance showed no significant difference at 0-15 cm depth between treatment where buffel grass had a soil moisture of 13 g/100 g soil , 12 g/100g soil in stylo, 11and 12 g/100g soil in Rhodes grass and control treatment respectively (Table 30).
Rangeland water infiltration
Water infiltration as measured with Mariotte bottle in rangeland, April 2016 showed significant effects between species and fertilizer (P<0.05), however there was no significant effect between species by fertilizer interaction in water infiltration. Buffel grass had the highest water infiltration (5.3948 x 10-4 cm/s) than all species and the control treatment had the lowest infiltration (2.56 x 10-4 cm/s) and the difference was significant
(Table 32). Stylo had higher water infiltration (4.5482 x 10-4 cm/s) than Rhodes (3.6095 x
10-4 cm/s) and control, and the difference was significant. Rhodes grass had the lower water infiltration than all species except for the control treatment. 94
Water infiltration showed significant effects between Fertilizer level where as the higher rate of fertilizer rate (30 kg/ha) had higher water infiltration than the other two rates of 20 kg/ha and 0 kg/ha and the difference was significant (Table 33). Higher water infiltration of 4.4014 x10-4 cm/s was measured at 30 kg/ha fertilizer rate followed by 3.8861 x 10-4 cm/s measured at 20 kg/ha fertilizer rate and the lowest rate of water infiltration (3.7892 x10-4 cm/s) was measured at 0 rate of fertilizer. However, there was no significant difference in water infiltration measured between 0 rate of fertilizer and with 20 kg/ha fertilizer.
EXPERIMENT III CROPLAND
Cropland soil characteristics
The soil was characterized by a sandy clay texture class with an average pH of 5.9 which is satisfactory for most crops, and is described as lime free where close monitoring is important (Table 48). Nitrogen determination found an average of 0.34%, with a low soil organic carbon of 0.64% and low soil phosphorous content of 2.92mg/kg. The basic cation tested (K+) was measured with an average of 1.01 Cmol/kg.
Seedling emergence of cover cop species and population density
Seedling emergence of cover crop species measured in February 2016 showed significant effects between species (P<0.05), however there was no significant effect between fertilizer and species by fertilizer interaction in emergence (Table 35). Sorghum had higher
95 emergence than cowpea and teff and the difference was significant. Sorghum population density was 36 m-2 plants while cowpea and sorghum was 16 and 7 seedlings m-2 respectively (Table 35). Cowpea and teff didn’t vary significantly in seedling emergence.
Mean seedling emergence planted in a green house February 2016 found significant effects between species (Table 49), where teff had higher emergence than all species followed by sorghum and the difference was significant. Cowpea, Rhodes and stylo didn’t vary significantly in emergence.
Population density of cover crop species measured in April 2016 showed significant effects between species (P<0.05), however fertilizer and species by fertilizer interaction showed no significant effects (P>0.05). Sorghum had higher population density than all species and cow pea had the lowest population density (Table 36). Sorghum had a population density of h 128 plants m-2 while teff had 46 plant m-2 and cowpea 42 plants m-2. The difference in population density between teff and cow pea was not significant.
Cropland biomass production
The yield of cover crop species showed significant effects between species and fertilizer
(P<0.05), however there was no significant effect between species by fertilizer interaction
(P>0.05). Sorghum had the highest yield than all cover crop species while the control treatment had the lowest yield and the difference was significant (Table 37). Sorghum had
1.7 ton DM/ha while the control treatment had 0.3 ton DM/ha. Cow pea had higher yield
(1.4 ton DM/ha) than teff (0.7 ton DM/ha) and control and the difference was significant. 96
Teff had higher yield (0.7 ton DM/ha) as compared to the control treatment (0.3 ton DM/ha) and the difference was significant.
Fertilizer level of application showed significant effects in yield. Fertilizer application rate of 30 kg ha-1 had the highest yield (1.2 ton DM/ha) as compared to 20 kg ha-1 which produced 1 ton DM/ha and the control (unfertilized) which gave the lowest yield of 0.8 ton
DM/ha and the difference was significant (Table 38).
The species by fertilizer interaction in yield showed no significant effect, however the yield measured at 30 kg ha-1 fertilizer level was higher than that measured at 20 kg ha-1 and 0 kg ha-1 (Table 39; Figure 7) in all treatments. The yield measured at 0 kgha-1 fertilizer level was the lowest in all treatments. Sorghum had the highest yield (1.8 tons DM/ha) at fertilizer level of 30 kgha-1 while teff had the lowest yield (0.8 tons DM/ha) at the same rate of fertilizer between all species planted.
Mean yield of cover crop species measured in a greenhouse April 2016 found significant effects between species (Table 50). Sorghum and cowpea was measured with higher yield while teff, Rhodes and stylo didn’t vary significantly.
Cropland vegetation cover and proportional of sown species
Vegetation cover measured in March 2016 showed significant effects between species
(P<0.05). There was, however, no significant effect of fertilizer and species by fertilizer interaction in vegetation cover (P>0.05). On the other hand, fertilizer showed significant effect in proportional of cover crop species sown (P<0.05) (Table 41). On average, cowpea 97 had higher percentage cover (95%) followed by sorghum (91%), and teff (66%) where control had the lowest (12%) (Table 40). However, the difference in cover between all species measured showed no significant difference except for the control treatment which varied significantly with all species (Table 40).
Proportional of sown species showed no significant effects between species, fertilizer and species by fertilizer interaction and therefore the average means are presented in parentheses (Table 40). Sorghum experimental plots had higher proportion of sown species
(90%) and cow pea was relatively lower (84%) than that of sorghum.
Soil Penetration Resistance and water infiltration of cover crop species
Soil penetration resistance
The SPR in April showed significant effect in species, fertilizer and species by fertilizer interaction at some depths (P<0.05) (Table 42). However soil moisture measured simultaneously with soil penetration resistance showed no significant effects between treatment (P>0.05), therefore average soil moisture percent are presented across treatments
(Table 43). Species significant effects was observed at 2.5, 7.5, 10, 12.5, and 15 cm depth, fertilizer effect was observed at 12.5 cm depth and species by fertilizer interaction was observed at 20 cm and 22.5 cm depths (Table 42).
Sorghum had the lowest soil penetration resistance than all treatment, while the control treatment had the highest penetration resistance than all other treatments at all depths and
98 the difference was significant (Table 43). Penetration resistance increased with depth where sorghum was measured with 214, 440, 554, 686, and 863 kPa while the control treatment was measured with 336, 742, 916, 1199, and 1396 kPa at 2.5, 7.5, 10, 12.5, and
15 cm depth, respectively.
Sorghum had a lower soil penetration resistance than cowpea at all depths and the difference was significant except at 7.5 cm where sorghum had a penetration resistance of
440 kPa and cowpea had 502 kPa and the difference was not significant. Cowpea had lower soil penetration resistance than teff at some depths and the difference was significant.
Lower soil penetration resistance in cowpea observed at 2.5, 10, and 15 cm was significant different than that for teff, however, the lower soil penetration resistance observed at 7.5 cm and 12.5 cm didn’t vary significantly from that of teff.
Soil moisture measured simultaneously with soil penetration resistance showed no significant effect between treatments where sorghum had 16% soil moisture, 14% in cowpea, 11% and 10% for teff and control, respectively (Table 42).
Fertilizer and species by fertilizer interaction showed significant effect in soil penetration resistance (Table 44, 45), however the two fertilizer level applied didn’t affect soil compaction when compared to the control (unfertilized treatment).
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Water infiltration
Water infiltration as measured by Mariotte bottle showed significant effects for species and fertilizer (P<0.05). However, there was no significant effect for the species by fertilizer interaction (P>0.05). Sorghum had higher infiltration than all treatments and control had the lowest and the difference was significant (Table 46). Sorghum had higher water infiltration (6.59 x10-4 cm/s) than cowpea (5.31 x10-4 cm/s) and the difference was significant. Cowpea had higher water infiltration than teff (3.71 x10-4 cm/s) and control
(2.95 x10-4 cm/s) and the difference was significant. However, teff and control didn’t vary significantly.
Fertilizer showed significant effect (Table 47) in water infiltration where higher water infiltration (5.4197 x10-4 cm/s) was observed at Fert-30 followed by Fert-20 and Fert-0 where water infiltration had 4.45 x10-4 cm/s and 3.98 x10-4 cm/s hydraulic conductivity respectively. However, Fert-20 and Fert-0 didn’t vary significantly in water infiltration.
The relationship between water infiltration and SPR showed negative relationship where high SPR was measured with low water infiltration and high water infiltration was measures with low SPR (Figure 8). Likewise, the relationship between forage mass and water infiltration showed positive relationship where higher forage mass was measured with higher water infiltration (Figure 9). Additionally, forage mass also showed a negative relationship where low forage mass was measured with higher soil penetration resistance
(Figure 10). 100
DISCUSSION
EXPERIMENT II-RANGELAND
Weather and climate
Generally the weather data recorded at the experimental site in this year since the start of the experiment was better than that for last year (Table 22), and gave higher seedling emergence, density and the overall large biomass production in both rangeland and cropland site. Despite the fact that the area is located in dryland, the rainfall data recorded this year for the whole period of experiment indicates higher precipitation than the previous year which favored vegetation growth. However, rainfall distribution and frequency wasn’t very good which resulted in poor yield of grain crops in some areas.
Cenchrus ciliaris
Cenchrus ciliaris is commonly buffel grass or African foxtail grass is a perennial grass and one of the important forage crops for livestock feeding in Tanzania due to its quality and ability to tolerate dry conditions. It was planted using stem tillers due to lack of good quality and certified seeds in the country. Due to good precipitation, buffel grass performed very well with higher emergence (tiller number) than Rhodes grass. Buffel grass had the highest population density counted near to the end of the experiment (April, 2016) as compared to all species planted and the difference was significant. Higher population density could be due to good weather, particularly amount of precipitation during its
101 establishment. In addition, buffel grass had on average high vegetation cover reaching
40% of the proportion of sown from weeds infested its experimental plots.
The yield in buffel grass was highest when compared with other treatments. This could be due to good emergence (tiller number), higher stand density count and high percent cover.
Studies indicate environmental factors such as temperature, light and soil moisture are major factors affecting growth and biomass production (Hopkins, 2000). These factors were not limiting during the start of the experiment until the establishment stage of the vegetation which could be the reason for good performance in terms of yield, cover and population density.
Buffel grass had lower SPR than all treatment and the difference was significant in all depths that showed significant effects (Table 30). The percentage soil moisture that was measured simultaneously with penetration resistance showed no significant effects between species and therefore, lower SPR in buffel grass as compared to other treatment could be due to the cover crop effects in improving soil structure and aggregate stability
(Carter, 2002; Kasper et al., 2001) due to increased root biomass and soil organic matter as a result of good biomass and the overall quality of the soil (Navas et al., 2011). However, more research cold be crucial to measure the cover crop effectiveness for a longer period of time.
Existence of a growing cover crop or residues increase hydrological resistance of the soil surface and, as a result, slow down runoff (Dabney, 1998). Through their impact on soil, 102 cover crops affect hydrology by modifying the partitioning of precipitation into the fractions of runoff amount, infiltration, surface storage, and surface detention (Dabney,
1998). In our experiment water infiltration as measured by Mariotte bottle found higher water infiltration in buffel grass than all cover crop species and the control treatment and the difference was significant. This could be due to its lower SPR measured at various depths and its root architecture in creating good micro environment especially macropores
(Lal & Shukla, 2004) and through improved aggregate stability (Folorunso et al., 1992) in the soil and enhance infiltration.
Chloris gayana
Chloris gayana commonly called Rhodes grass is a perennial grass and one of the important forage crop in Tanzania which is used for livestock feeding. It has been well established in various places for feeding cattle and it produces very good hay when cut at the right stage of growth. Rhodes grass was planted using seeds, however it has a very poor or no emergence in almost all plots.
This could be due to poor seed quality where no certification of pasture seeds is done in the country. The seeds are bought from producers mainly research centers with no description of the harvesting process, germination percent, and percent of inert matters.
Barker et al., (2012), suggest in their forage and biomass synthesis that certified seeds of named cultivars to be very important for forage planting. In addition, greenhouse test of the Rhodes grass seedling showed lower emergence as compared to teff, sorghum and 103 cowpea, but higher than that for stylo. It could also be due to immature embryo, failure to compete with weeds since few plants were observed.
Seedling emergence counted in this treatment represents weeds. Population density measured near to the end of the experiment (April 2016) showed lower population density in Rhodes grass which had no significant difference with stylo. The vegetation cover percent was higher (55%) than that for stylo and the control treatment, however, the proportional of sown (Rhodes grass) was only 1% due to its poor emergence.
Rhodes grass had higher yield than that for stylo and control treatment and the difference was significant. Higher yield could be due to adaptability of the weed species to the site
(Barker et al., 2012) and their higher population density. The SPR was higher than for all species except for the control treatment (Table 30) in all depths which showed significant effects. Higher SPR could be due to poor ability of the invaded weed to improve soil structure and lower compaction.
Rain drop impact can cause crusting of the soil surface (Lal & and Shukla, 2004) which often seals surface pores which results in less infiltration and increased runoff. Water infiltration measured in Rhodes grass treatment was lower than that of buffel grass and stylo, but higher than the control treatment and the difference was significant (Table 32).
Lower water infiltration could be due to higher compaction measured and poor ability of the weeds infested to improve the soil structure and the overall soil physical properties.
104
However, significant higher water infiltration than that in the control treatment indicates the role of vegetation cover in protecting the soil and to improve soil physical properties.
Stylosanthes scabra
Stylosanthes scabra commonly called shrubby stylo is a perennial forage legume which was selected due to its ability to survive in dryland environments. It has a good nutritional quality for livestock feeding. Stylosanthes was planted by broadcasting using seeds and it had the highest emergence (30 plants per m2) than all species planted and the difference was significant.
The population density measured near to the end of the experiment was lowest than all species planted. However the population density between stylo and Rhodes didn’t vary significantly. The lower population density in stylo is because no weeds were counted while Rhodes grass were essentially weeds counted and tiller number in buffel grass. Stylo didn’t vary significantly with other species in cover. The proportional of sown species in stylo was higher (14%) than that for Rhodes grass (1%) but lower than that for buffel grass.
Stylo had lower yield when compared to buffel grass and Rhodes grass and the difference was significant, however it gave higher yield than that for the control treatment. Lower yield could be due to the fact that during harvesting, stylo wasn’t at its maximum sward growth and probably higher competition from weeds reduced density and cover of the vegetation and hence relatively lower yield.
105
Stylo had lower SPR than Rhodes grass and control treatment and the difference was significant at all depths that showed significant effects. Lower SPR could be due to species good root structure especially root growth (Dabney, 1998) which can increase aggregate stability and the overall structure and hence reduced compaction. On the other hand, Stylo had higher water infiltration than Rhodes grass and the control treatment and the difference was significant. Dabney, (1998) indicate cover crops through mechanisms of root growth can change soil macro-pores and indirect affect populations and activities of macro fauna such as earthworms and ants and hence increased infiltration than Rhodes and the control treatment.
Control (unplanted)
The control treatment received no seeding, however it was fertilized. Weeding was also applied to this treatment and therefore neither emergence nor population density was measured. The goal of weeding was to maintain less cover so that we can measure the difference between cover crop effect and bare land that could be a result of heavy grazing or any other natural or anthropogenic activities.
Vegetation cover in the control treatment was measured with the lowest cover and this is because weeding was applied and no seeding was done in this treatment. Herbage yield was also the lowest between all treatments and the difference was significant and the reason is due to weeding and absence of planted species. Soil compaction was measured with the highest soil penetration resistance than all cover crop species planted. This could be due to 106 less cover on the control treatment and justify the role of cover crop in improving or reducing SPR and the overall sustainability of the soil quality. Rhodes grass and control treatment didn’t vary significantly in SPR. This indicates cover crops might vary in terms of extent to which they can facilitate an increasing water infiltration and reduced runoff
(Dabney, 1998).
Control treatment was also measured with the lowest water infiltration than all treatments and the difference was significant. Lower water infiltration could be due to absence or less vegetation cover which protect the soil against rain drop effect which can create hard surface and reduce pore size in soil and hence impede infiltration. Lower infiltration in the control treatment justifies the fact that existence of a growing cover crop or residues increase hydrological resistance of the soil surface and, as a result, slow down runoff and increae infiltration (Dabney, 1998).
Diammonium Phosphate Fertilizer (DAP)
DAP comprises 18% N and 46% P, and was applied as a sub plot factor treatment.
Fertilizer application is important to enhance early establishment and plant vigor where chlorophyll is enhanced via N application and root growth with P application. The recommendation rate was per semiarid central zone recommendation, where a micro doze of 20 kg ha-1 is recommended.
There was no significant effect in fertilizer application observed in emergence, population density and cover. However the yield of cover crop forage was affected by fertilizer and 107 fertilizer by species effect where, the higher rate applied (30 kg ha-1) had the highest yield followed by the recommended rate of 20 kg ha-1 and the unfertilized had the lowest yield
(Table 25). All species had the highest yield at the highest rate of fertilizer applied as compared to the recommended rate and the unfertilized control (Table 26). Higher yield with fertilizer application justify the role of fertilizer for vegetation growth and establishment in improving vigor and sufficient forage yield (Cosgrove & Collins, 2003).
There were no significant effects of fertilizer on SPR, however, there was a fertilizer by species interaction at 7.5cm depth. Despite the interaction effect, fertilizer level showed no consistent trend in SPR reduction in all sown species (Table 31). On the other hand, fertilizer level showed significant effect in water infiltration where the higher rate of fertilizer applied had higher water infiltration than the recommended rate and the control
(Table 32). The recommended rate and the control didn’t vary significantly in water infiltration. Higher water infiltration with the higher rate of fertilizer could be due to enhanced root growth which create macropores in the soil and enhance good soil structure.
Conclusion
Our results indicated good performance of forage cover crop species in terms of emergence, cover and density, despite the failure of Rhodes grass. Fertilizer didn’t influence emergence, cover and density of cover crop species which could be due to heavy rain that could have diluted nutrient responses. Yield of cover crop species was good and 108 varied between species and fertilizer rates applied where the higher rate of fertilizer applied had higher yield as compared to the low rate and the control. The results also indicated the potential of cover crop species in altering soil properties such as water infiltration and SPR.
Cover crop species varied with soil penetration resistance and water infiltration measurements where as highly fertilized species had higher water infiltration while SPR was unaffected by fertilizer. Therefore our results indicated the potential of cover forage crop species in improving soil physical properties and thus reducing soil degradation and enhance sustainability rangeland productivity.
EXPERIMENT III-CROPLAND
Sorghum vulgare
Sorghum is a grain crop that is used as one of the staple food in the country. It was selected as a cover crop plant for this research due to its drought tolerant ability. It was planted using seeds by drilling. Sorghum gave a higher emergence than all species sown where it had 36 seedlings per square metre and the difference was significant. Higher emergence could be due its adaptability to the site (Barker, et al., 2012) especially its drought tolerance and its good viability. The population density measured in April showed higher stand count than all other species sown where sorghum had 128 plants per m2 and the difference was
109 significant. Higher population density was expected due to a good emergence observed few weeks after sowing.
Sorghum and teff didn’t vary significantly, however it had a higher vegetation cover than that for teff and the difference was not significant. A significant difference in cover was observed between sorghum and the unplanted control, however this is because the control treatment received weeding. Despite the fact that the proportion of sown species didn’t show significant, however the results indicated that sorghum plots had higher proportion of sown species than all other planted species (Table 40). This is because of good emergence and seedling cover.
Biomass production of sorghum was the highest between all treatments and the difference was significant (Table 37). This could be due to higher emergence, percentage cover and proportional contribution of sown species and population density. On the other hand, sorghum had lower soil penetration resistance at all depths that showed significant effects
(Table 43) than all treatments and the difference was significant. Soil moisture measured simultaneously with soil penetration resistance showed no significant effects between treatments and therefore lower SPR could be due to the ability of the cover crop to improve its soil structure (Cater, 2002) and improve soil quality (Navas et al., 2011). In addition, sorghum had higher water infiltration than all cover crop species and the control and the difference was significant. Higher water infiltration could be due to lower SPR (Lal &
110
Shukla, 2004) and the ability of the crop to improve soil physical properties such as macropores distribution and improve rate of water infiltration.
Eragrostis teff
Eragrostis teff commonly known as teff is an annual herbaceous grass that is used as a forage crop and its grains is used as food in some countries such as Ethiopia. Teff was planted with seeds by broadcasting however, no emergence was observed and therefore its treatment plots were weed infested. Emergence failure could be due to seed being washed or covered by mud after planting due to higher amount of rainfall which was raining during planting time. This is justified by higher seedling emergence observed in teff planted in greenhouse (Table 49) than all species sown in greenhouse. Therefore seedling emergence counted in teff was the number of weed plants emerged in the treatment plot.
Seedling emergence counted in this treatment was the lowest than all species sown and this could be due to failure of teff to emerge and late weed emergence due to the fact that seedbed preparation was well prepared. On the other hand, the population density measured in teff was higher than that for cowpea however, the difference was not significant. Higher population density was a result of weed infestation in this plot following failure of teff. On average, percentage cover measured in teff was less than all species sown
Biomass production in teff was lower than all species sown but higher than that of control
(Table 37). On the other hand, soil compaction in teff was measured with higher soil penetration resistance than all species sown, but lower than that measured in the control 111 treatment. Soil moisture measured simultaneously with soil penetration resistance showed no significant effects and therefore higher SPR than other species sown could be due lower ability of the weed species to improve soil physical properties such as penetration resistance, likewise, lower compaction than the control treatment shows the significance of cover crop in improving soil structure such as lowering soil compaction.
Teff was measured with lower water infiltration than all species sown except for the control treatment. Lower water infiltration in teff could also be associated with higher compaction measured in teff (Lal & Shukla, 2004).
Vigna inguiculata
Vigna unguiculata commonly known as cowpea is a herbaceous forage legume which is used as a food crop through its peas, leaves also make a good vegetable widely eaten in the country. However, fresh leaves also make a good forage for animals due to its quality.
Cowpea performance was good and this was demonstrated through its emergence, which was higher than that for teff. Cowpea population density was lower than all species counted, however its density didn’t vary significantly with teff. On the other hand, cowpea was measured with the highest vegetation cover percent than all species sown and this could be due to its ability to creep and cover the ground and hence form a good herbaceous cover crop. The proportional of sown species was not significant between species.
Cowpea was measured with higher biomass production than teff and control and the difference was significant. Higher biomass could be due to higher vegetation cover and 112 good leafy production produced. On the other hand, cowpea was measured with lower SPR than teff and control. Lower SPR in cowpea could be due to its ability to form a good cover and hence protect and improve soil physical properties such as soil structure (Dabney,
1998). In addition, cowpea had higher water infiltration than teff and control and the difference was significant. Lower infiltration could also be associated with lower SPR (Lal
& Shukla, 2004).
Control (unplanted)
The control treatment received no seeding, however it was fertilized. Weeding was also applied to this treatment and therefore neither emergence nor population density was measured. The goal of weeding was to maintain less cover so that we can measure the difference between cover crop effect and bare land that could be a result of poor cropping practices or any other natural or anthropogenic activities.
Vegetation cover in the control treatment was measured with the lowest cover and this is because weeding was applied and no seeding was done in this treatment. Herbage yield was also the lowest between all treatments and the difference was significant and the reason is due to weeding and absence of species sowing. The SPR for the control treatment was higher than all other treatments and this could be due to less cover on the control treatment and justifies the role of cover crop in improving or reducing SPR and the overall of soil quality. The difference in soil penetration resistance between control and all other treatment
113 was significant. This indicated the role that cover crop species play in improving soil physical properties such as alleviating soil compaction.
Control treatment was also measured with the lowest water infiltration than all treatments and the difference was significant with exception of teff which didn’t differ significantly with control. Lower water infiltration could be due to absence or less vegetation cover which protect the soil against rain drop effect which can create hard surface and reduce pore size in soil and hence impede infiltration (Lal & Shukla, 2004).
Diammonium Phosphate Fertilizer (DAP)
Diammonium fertilizer (18-46-0) was applied as a sub plot factor treatment. Fertilizer application is important to enhance early establishment and plant vigor where chlorophyll is enhanced via N application and root growth with P application. The recommendation rate was per semiarid central zone recommendation, where a micro doze of 20 kg ha-1 is recommended.
There was no significant effect in fertilizer application observed in emergence, population density and cover. However the yield of cover crop species was affected by fertilizer, where the higher rate of fertilizer applied (30 kgha-1) was measured with the highest yield followed by the recommended rate of 20 kgha-1 and the unfertilized had the lowest yield
(Table 38).
114
Species and fertilizer by species interaction showed no significant effects however, on average all species gave the highest yield at the highest rate of fertilizer applied as compared to the recommended rate and the unfertilized control (Table 39).
SPR showed significant effects in fertilizer at 12.5cm, and species fertilizer interaction at
20cm and 12.5cm depth. Despite significant effect in fertilizer, and fertilizer by species interaction, fertilizer level showed no consistent in SPR reduction in all species sown
(Table 44, 45). On the other hand, fertilizer level showed significant effect in water infiltration where the higher rate of fertilizer applied was related to higher water infiltration than the recommended fertilizer rate and the control (Table 47). The recommended fertilizer rate and the control didn’t vary significantly in water infiltration. Higher water infiltration with higher rate of fertilizer could be due to enhanced root growth which create macropores in the soil and enhance good soil structure (Dabney, 1998).
Conclusion
Our results indicated good performance of forage cover crop species in terms of emergence, cover and density, despite the failure of teff grass. Fertilizer didn’t influence emergence, cover and density of cover crop species. However the yield of cover crop species was good and varied between species and fertilizer rates where the higher rate of fertilizer resulted in higher yield as compared to the low rate and the control. The results also indicated the potential of cover crop species in altering soil properties such as water infiltration and soil compaction. Cover crop species varied with soil penetration resistance 115 where fertilizer and fertilizer by species interaction showed significant effects. Despite significant effect in fertilizer, SPR was not reduced with fertilizer in comparison to the control treatment. On the other hand, our study also showed water infiltration measurements to be affected by fertilizer where highly fertilized species had higher water infiltration. Therefore our results indicates improved soil physical properties using potential cover crop forage species has the potential to reduce soil degradation and enhance sustainability of soil quality.
116
Table 22: Monthly mean precipitation recorded at Kongwa Pasture Research Center for consecutive years of 2015 to May 2016 where the experiment ended. Mean rainfall per month
(mm)
Month 2015 2016
January 10.65 13.85
February 21.3 18.84
March 22.47 28.7
April TR 14.16
May 2 0
June 0
July 0
August 0
September 0
October 0
November 16.97
December 16.675
TR=Trace amount; 0= No precipitation
117
Table 23: Mean seedling emergence of cover forage species in (Exp. 2) on February 2016. Means followed with the same letter are not significantly different (P>0.05).
Species Mean Emergence /(m2) t-groupings
Stylosanthes 30 A
Buffel grass 19 B
Rhodes grass 11 B
LSD (0.05) 5.2329
118
Table 24: Mean yield of cover forage species measured on (Exp. 2) in April 2016. Means followed with the same letter were not significantly different (P>0.05). Species Mean yield (kg DM/ha) t-groupings
Buffel grass 1286 A
Rhodes grass 1118 A
Stylo 754 B
Control 335 C
LSD (0.05) 227.85
119
Table 25: Mean yield of cover forage species measured in April 2016 on (Exp. 2) as affected by DAP fertilizer treatment. Means followed with the same letter were not significantly different (P>0.05). Fertilizer level (kg/ha) Mean yield (kg DM/ha) t-grouping
30 1240 A
20 758 B
0 622 B
LSD (0.05) 197.33
120
Table 26: Yield of cover forage species measured in April 2016 on (Exp.2) as affected by species and fertilizer interaction.s
spp DAP Fertilizer rate (kg/ha) yield
Buffel grass 0 931
Buffel grass 20 1137
Buffel grass 30 1791
Rhodes grass 0 661
Rhodes grass 20 1075
Rhodes grass 30 1620
stylo 0 463
stylo 20 592
stylo 30 1209
control 0 435
control 20 231
control 30 340
LSD (0.05) 197.33 227.85*(100.33)
*=Interaction LSD
121
Table 27: Mean population density of cover forage species measured in April 2016 on (Exp.2). Means followed with the same letter are not significantly different (P>0.05). Species Mean population density t-grouping
(plants m-2)
Buffel grass 137 A
Rhodes grass* 58 B
Stylosanthes 54 B
LSD (0.05) 10.288
(*) is the density of the weed population
122
Table 28: Vegetation cover percent measured on (Exp.2) in March 2016. In the parentheses are sown species cover. Means followed with the same letter are not significantly different (P>0.05). Species Cover (%) t-grouping
Buffel grass 74 (40) A
Rhodes grass 55 (1) A
Stylo 54 (14) A
Control 4 B
LSD (0.05) 33.066
123
Table 29: ANOVA for soil penetration resistance measured in April, 2016 on (Exp. 2). The ANOVA for only five depths are shown, since all results >10 were NS.
Depth (cm) Species Fertilizer Species*Fertilizer
2.5 <0.0001 NS NS
5 <0.0001 NS 0.069 (NS)
7.5 <0.0001 NS 0.029
10 <0.0001 NS 0.0501
>10 NS NS NS
NS=No significant difference
124
Table 30: Soil penetration resistance and soil moisture measured in April 2016 on (Exp. 2). Means with the same letter within column are not significantly different (P>0.05).
Species Means Means Means Means Soil
(kPa) (kPa) (kPa) (kPa) moisture
(2.5cm) (5 cm) (7.5 cm) (10 cm) (g/100 g
soil)
(0-15 cm)
Buffel grass 278 c 467 c 770 c 907 c 13
Stylo 428 b 709 b 969 b 1158 b 12
Rhodes 630 a 928 a 1162 a 1344 a 11
Control 655 a 958 a 1201 a 1399 a 12
LSD (0.05) 141.82 92.812 94.18 123.07
125
Table 31: Soil penetration resistance as affected by species and fertilizer interaction measured in April 2016 on (Exp 2).
Species Fertilizer level Mean SPR (kPa)
(kg/ha) 7.5 cm
Buffel grass 30 761
Buffel grass 0 821
Buffel grass 20 728
Rhodes grass 30 1201
Rhodes grass 0 1166
Rhodes grass 20 1119
Control 30 1260
Control 0 1196
Control 20 1146
Stylo 30 809
Stylo 0 997
Stylo 20 1100
LSD (0.05) NS 94.18 *135
(*=Interaction LSD
126
Table 32: Water infiltration measured in April 2016 on (Exp. 2). Means with the same letter within column are not significantly different (P>0.05). Species Means Ks (cm/sec) t-grouping
Buffel grass 5.3948 x10-4 A
Stylo 4.5482 x 10-4 B
Rhodes grass 3.6095 x 10-4 C
Control 2.56 x 10-4 D
LSD (0.05) 3.85 x 10-5
127
Table 33: Water infiltration measured in April 2016 on (Exp. 2). Means with the same letter within column are not significantly different (P>0.05).
Fertilizer level (kg/ha) Means Ks t-grouping
30 4.4014 x10-4 A
20 3.8861 x10-4 B
0 3.7892 x10-4 B
LSD (0.05) 3.33 x10-5
128
Table 34: Soil characteristics in (Exp. 2) measured in January 2016. Soil samples were taken at a depth of 0-15cm.
Reps pH %Clay %sand %Silt Class TN OC P K+
(%) (%) (mg/kg) (Cmol/kg)
1 7.23 28.12 70.96 0.92 SCL 0.08 0.63 7.36 0.79
2 6.10 24.12 74.96 0.92 SCL 0.06 0.64 6.85 0.62
3 6.2 24.12 74.96 0.92 SCL 0.08 0.54 5.05 0.77
4 6.38 24.12 74.96 0.92 SCL 0.07 0.63 4.41 0.78
Mean 6.5 25.12 73.96 0.92 SCL 0.24 0.61 5.92 0.74
129
Table 35: Seedling emergence of cover crop species counted in February 2016 in (Exp. 3). Means followed with the same letter are not significantly different (P>0.05).
Species Mean Emergence (m-2) t-grouping
Sorghum 36 A
Cowpea 16 B
Teff 7 C
LSD (0.05) 4.8781
130
Table 36: Population density of cover crop species measured in April 2016 on (Exp. 3). Means followed with the same letter are not significantly different (P>0.05).
Species Mean population density t-grouping
Sorghum 128 A
Teff* 46 B
Cowpea 42 B
LSD (0.05) 7.6336
(*) Is the density of the weed population
131
Table 37: Yield of cover crop species measured in April 2016 on (Exp. 3). Means followed with the same letter are not significantly different (P>0.05).
Species Mean yield (kgDM/ha) t-grouping
Sorghum 1720 A
Cowpea 1419 B
Teff 732 C
Control 379 D
LSD (0.05) 135.22
132
Table 38: Yield of cover crop species measured in April 2016 as affected by DAP fertilizer on (Exp. 3). Means followed with the same letter are not significantly different (P>0.05).
Fertilizer level (kg/ha) Mean yield (kgDM/ha) t-grouping
30 1208 A
20 1084 B
0 895 C
LSD (0.05) 117.1
133
Table 39: Species by fertilizer interaction on yield of cover crop species measured on April 2014.
Species Fertilizer level LSMEANS
(kg/ha) (kgDM/ha)
Sorghum 30 1854
Sorghum 20 1810
Sorghum 0 1497
Cowpea 30 1603
Cowpea 20 1429
Cowpea 0 1225
Teff 30 847
Teff 20 795
Teff 0 555
Control 30 531
Control 20 303
Control 0 303
LSD (0.05) 117.1 135.22 *101.65
(*=Interaction LSD
134
Table 40: Vegetation cover of crop species measured in March 2016 on (Exp. 3). In the parentheses is the proportional of sown species. Means followed with the same letter are not significantly different (P>0.05).
Species Cover (%) t-grouping
Sorghum 91 (90) A
Cowpea 95 (84) A
Teff 66 A
Control 12 B
LSD (0.05) 32.214
135
Table 41: Vegetation cover percent of cover crop species as affected by DAP fertilizer measured in March 2016 on (Exp. 3). Means followed by the same letter within the column are not significantly different.
DAP Fertilizer level Cover (%) t-groping
(kg/ha)
30 69 A
20 65 AB
0 64 B
LSD (0.05) 3.8296
136
Table 42: ANOVA for soil penetration resistance measured in April, 2016 on Exp. 3. The ANOVA for only 10 depths are shown, since all results >30cm depth were NS. Depth (cm) Species Fertilizer Species*Fertilizer
2.5 0.0364 NS NS
5 NS (0.0903) NS NS
7.5 0.0067 NS NS
10 0.0055 NS NS
12.5 0.0008 0.0177 NS
15 0.0127 NS NS
20 NS NS (0.0782) 0.0484
22.5 NS 0.0233 0.0313
27.5 NS 0.0099 NS
30 NS 0.0385 NS
>30 NS NS NS
NS=Not significant
137
Table 43: oil penetration resistance of cover crop species measured in April 2016 on (Exp. 3). Means with the same letter within column are not significantly different (P>0.05). Species Means Means Means Means Means Soil
SPR SPR SPR SPR SPR moisture
(KPa) (KPa) (KPa) (KPa) (KPa) (g/100g)
2.5cm 7.5cm 10.0cm 12.5cm 15cm soil
0-15cm
Sorghum 214 c 440 b 554 c 686 c 862 c 16
Cowpea 245 bc 502 b 649 bc 827 b 996 bc 14
Teff 285 b 510 b 723 b 858 b 1044 b 11
control 336 a 742 a 916 a 1199 a 1396 a 10
LSD(0.05) 50.076 110.1 134.12 124.38 143.74
138
Table 44: Fertilizer effect on soil penetration resistance measured in April 2016 on (Exp. 3). Means with the same letter within column are not significantly different (P>0.05). Fertilizer level (kg/ha) Mean SPR (KPa) t-grouping
12.5cm
30 985 A
20 852 B
0 840 B
LSD (0.05) 107.71
139
Table 45: Fertilizer by species interaction on soil penetration resistance measured in April 2016 on (Exp. 3).
Species Fertilizer level LSMEANS SPR LSMEANS SPR
(kg/ha) (KPa) (KPa)
20cm 22.5cm
Sorghum 30 1781 1719
Sorghum 20 1254 1274
Sorghum 0 1260 1414
Cowpea 30 1395 1412
Cowpea 20 1405 1262
Cowpea 0 1333 1419
Teff 30 1386 1459
Teff 20 1297 1359
Teff 0 1124 1190
Control 30 1644 1624
Control 20 1181 1216
Control 0 1956 2158
LSD (0.05) 107.71 *103.09 *107.34
(*=Interaction LS
140
Table 46: Water infiltration measured in April, 2016 on (Exp. 3). Means with the same letter within column are not significantly different (P>0.05).
Species Means ks (cm/s) t-grouping
Sorghum 6.49992 x10-4 A
Cowpea 5.3118 x10-4 B
Teff 3.7096 x10-4 C
Control 2.949 x10-4 C
LSD (0.05) 0.0001
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Table 47: Water infiltration measured in April 2016 on (Exp. 3). Means with the same letter within column are not significantly different (P>0.05).
Fertilizer level (kg/ha) Means ks (cm/s) t-grouping
30 5.4197 x10-4 A
20 4.4518 x10-4 B
0 3.9808 x10-4 B
LSD (0.05) 0.0001
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Table 48: Soil characteristics measured on (Exp. 3) in January 2016. Soil samples were taken at a depth of 0-15cm, sampling was done in January, 2016. Reps pH %Clay %sand %Silt Class TN OC P K+
(%) (%) (mg/kg) (Cmol/kg)
1 5.87 26.12 70.96 0.92 SCL 0.09 0.64 3.26 0.9
2 6.02 30.12 68.96 0.92 SCL 0.07 0.66 2.23 0.94
3 6.15 36.12 62.96 0.92 SCL 0.08 0.59 3.13 1.14
4 5.93 28.12 68.96 0.92 SCL 0.1 0.67 3.26 1.06
Mean 5.9 30.12 67.96 0.92 SCL 0.34 0.64 2.97 1.01
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Table 49: Mean seedling emergence planted in a green house, February 2016
Species Mean Emergence (m2) t-grouping
Teff 3904 A
Sorghum 1643 B
Cowpea 382.3 C
Rhodes 345 C
Stylo 273 C
LSD (0.05) 307.39
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Table 50: Mean yield of cover forage species measured in a green house, April 2016.
Species Mean yield (kgDM/ha) t-grouping
Sorghum 2683 A
Cowpea 2447 A
Teff 517 B
Rhodes 444 B
Stylo 72 B
LSD (0.05) 839.08
145
Figure 4: Water infiltration model for determination of unsaturated hydraulic conductivity.
146
Figure 5: Species by fertilizer interaction effect on yield measured in April 2016 on (Exp. 2).
Species by fertilizer interaction effect 2000 1800 1600 1400 1200 buffel 1000 800 rhodes 600 stylo
Yield (kgDM/ha) Yield 400 control 200 0 0 20 30 DAP Fertilizer rate
147
Figure 6: Species by fertilizer interaction effect on soil penetration resistance (7.5cm) depth measured in April 2016 on (Exp. 2).
Fertilizer by species interaction effects on SPR 1400
1200
1000
800 buffel
600 rhodes SPR (kPa) SPR 400 stylo control 200
0 0 20 30 DAP fertilizer rate
148
Figure 7: Fertilizer by species interaction on yield measured on (Exp. 3) in April, 2016. The values are the mean yield value at three fertilizer treatment (fert-0, fert-20 and fert- 30).
Fertilizer by species interaction on yield 2000 1800 1600 1400 1200 sorghum 1000 800 cowpea 600 teff
Yield (kgDM/ha) Yield 400 control 200 0 0 20 30 DAP Fertilizer level
149
Figure 8: Linear regression line for the relationship between soil penetration resistance and water infiltration measured in April 2016 on (Exp. 30). The values are the mean for water infiltration and SPR at 15cm depth.
Linear regression line for the relatoship between SPR and water infiltration 1600 1400 1200 1000 800
600 y = -1E+06x + 1658.6 SPR (kPa) SPR 400 R² = 0.7814 200 0 0.00E+00 1.00E-04 2.00E-04 3.00E-04 4.00E-04 5.00E-04 6.00E-04 7.00E-04 Water infiltrationa
150
Figure 9: Linear regression line for the relatioship between forage mass and water infiltration measured on April 2016 on (Exp. 3). The values are for the respective means.
Linear regression line for the relationship between forage mass and water infiltration 0.0007 y = 3E-07x + 0.0002 0.0006 R² = 0.9875 0.0005 0.0004 0.0003 0.0002 0.0001 0
Water infiltration (cm/sec) infiltration Water 0 500 1000 1500 2000 yield (kgDM/ha)
151
Figure 10: Linear regression line for the relationship between yield and soil penetration resistance measured on (Exp. 3) in April 2016. The values are the respective means where SPR values are for 15cm depth.
Linear regression line for the relationship between yield and SPR 2000 1800 1600 1400 1200 1000 800 600 400 Yield (kgDM/ha) Yield y = -2.4251x + 3668.2 200 R² = 0.8057 0 0 200 400 600 800 1000 1200 1400 1600 SPR (kPa)
152
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