ENVIRONMENTAL EDUCATION, MANAGEMENT
OF PLANT RESOURCES FOR COOKING AND
CLIMATE CHANGE PERCEPTIONS IN SAHEL

Alexis Dzokom, Jules Balna, Roger Darman Djouldé

► To cite this version:

Alexis Dzokom, Jules Balna, Roger Darman Djouldé. ENVIRONMENTAL EDUCATION, MANAGEMENT OF PLANT RESOURCES FOR COOKING AND CLIMATE CHANGE PERCEPTIONS IN SAHEL. 2024. http://04990490

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Distributed under a Creative Commons Attribution 4.0 International License
ENVIRONNEMENTAL
EDUCATION, MANAGEMENT OF PLANT
RESOURCES FOR COOKING AND
CLIMATE CHANGE PERCEPTION IN
THE SAHEL

<figure><img src="image_2.png" /></figure>
Table of contents

<table><tr><td>Table of contents</td><td>ii</td></tr><tr><td>Photo Lists</td><td>xii</td></tr><tr><td>List of Tables</td><td>xiii</td></tr><tr><td>List of Graphs</td><td>xix</td></tr><tr><td>List of Figures</td><td>xxiv</td></tr><tr><td>List of abbreviations and symbols</td><td>xxvii</td></tr><tr><td>Foreword</td><td>xxxi</td></tr><tr><td>Dedication</td><td>xxxii</td></tr><tr><td>INTRODUCTION</td><td>1</td></tr><tr><td>1. Impacts of Climate Change on Plant Resources</td><td>1</td></tr><tr><td>2. Role of Environmental Education</td><td>1</td></tr><tr><td>3. Strategies for the Sustainable Management of Plant Resources</td><td>1</td></tr><tr><td>4. Tools and Approaches for Environmental Education</td><td>2</td></tr><tr><td>5. Collaboration and Partnerships</td><td>2</td></tr><tr><td>PART 1: ENVIRONMENT_MANAGEMENT OF PLANT RESOURCES FOR SOIL RESTORATION</td><td>3</td></tr><tr><td>CHAPITRE 1. OPTIMIZATION OF THE PRODUCTION OF TWO VARIETIES OF SORGUM (FADDA AND SOUMALEMBA) AMENDED WITH COMPOST BASED ON EICHHORNIA CRASSIPES LINKED TO URTICA DIOICA IN SAHEL AREAS NEAR LAKE CHAD</td><td>4</td></tr><tr><td>Abstract</td><td>4</td></tr><tr><td>INTRODUCTION</td><td>4</td></tr><tr><td>I- MATERIALS AND METHOD</td><td>5</td></tr><tr><td>1)- Study sites</td><td>6</td></tr><tr><td>2)- Plant material</td><td>6</td></tr><tr><td>3)- Experimental device and conduct of the test</td><td>6</td></tr><tr><td>II- RESULTS</td><td>8</td></tr><tr><td>II-1)- Study sites</td><td>9</td></tr><tr><td>II-2)- Advantage of compost based on Eichhornia crassipes and Urtica dioica</td><td>10</td></tr><tr><td>CONCLUSION</td><td>24</td></tr><tr><td>REFERENCES</td><td>2</td></tr><tr><td>EXERCISES AND CORRECTIONS ON THE OPTIMIZATION OF THE PRODUCTION OF TWO VARIETIES OF SORGUM (FADDA AND SOUMALEMBA) AMENDED WITH</td><td></td></tr></table>
EXERCISES AND ANSWERS ON ENVIRONMENTAL EDUCATION, MANAGEMENT
OF PLANT RESOURCES FOR COOKING AND CLIMATE CHANGE 48

CHAPITRE 1. EFFECTS OF ECOLOGICAL CHARCOAL PRODUCTION PROCESSES
BASED ON *EICHHORNIA CRASSIPES* ON ITS CHARACTERISTICS AS COOKING
ENERGY 53

ABSTRACT 53

INTRODUCTION 53

1. MATERIALS AND METHODS 54

1.1. Study zone 54

1.2. Eichhornia crassipes briquette manufacturing process 55

1.3. Hygro-calorific characterization of Eichhornia crassipes's charcoal 56

1.4. Chemical characterization of Eichhornia crassipes's charcoal 57

1.5. Combustion tests 58

2. RESULTS AND DISCUSSIONS 58

2.1. *Eichhornia crassipes* briquette manufacturing process 58

CONCLUSION 64

EXERCISES AND CORRECTIONS ON THE EFFECTS OF ECOLOGICAL CHARCOAL
PRODUCTION PROCESSES BASED ON *EICHHORNIA CRASSIPES* ON ITS
CHARACTERISTICS AS COOKING ENERGY 67

CHAPITRE 2. STUDY OF THE PERFORMANCE OF ORGANIC AND INORGANIC
BINDERS FOR THE PRODUCTION OF ECOLOGICAL CHARCOAL FUELS BASED ON
DEAD BIOMASS OF *AZADIRACHTA INDICA* 71

ABSTRACT 71

INTRODUCTION 71

1. MATERIALS AND METHODS 72

1.1. Study zone 72

1.2. Selection, sorting and preparation of dead leaves and leaf stems of Azadirachta indica 73

1.3. Selection, sorting and preparation of binders 73

1.4. Physical chemical characterization of fuel samples based on dry dead leaves of *Azadirachta indica* 74

2. RESULTS AND DISCUSSION 78

2.1. Physical characterization of charcoal 78

2.2. Chemical characterization 80

2.3. Energy efficiency 82

2.4. Cooking test 84

CONCLUSION 86

Bibliographic reference 86
<table><tr><td>EXERCISES AND CORRECTIONS ON THE STUDY OF THE PERFORMANCE OF ORGANIC AND NON-ORGANIC BINDERS FOR THE PRODUCTION OF ECOLOGICAL COAL FUELS BASED ON DEAD BIOMASS OF AZADIRACHTA INDICA</td><td>88</td></tr></table>

<table><tr><td>CHAPITRE 3. PRODUCTION OF BIOETHANOL BASED ON EICHHORNIA CRASSIPES COMBINED WITH THE PULP OF THE RIPE FRUIT OF AZADIRACHTA INDICA</td><td>92</td></tr></table>

<table><tr><td>ABSTRACT</td><td>92</td></tr></table>

<table><tr><td>INTRODUCTION</td><td>92</td></tr></table>

<table><tr><td>I- MATERIALS AND METHOD</td><td>94</td></tr></table>

<table><tr><td>I-1) - Raw material acquisition area and characterization</td><td>94</td></tr></table>

<table><tr><td>I-2) - Pretreatment of the raw material and characterization</td><td>95</td></tr></table>

<table><tr><td>I-3) - Composition of samples of the raw material to be fermented</td><td>96</td></tr></table>

<table><tr><td>I-4) - Processing of the raw material</td><td>96</td></tr></table>

<table><tr><td>I-5) - Alcoholic fermentation of the solution of Eichhornia crassipes associated with fresh fruits and blackberries of Azadirachta indica</td><td>97</td></tr></table>

<table><tr><td>II-) - RESULTS</td><td>99</td></tr></table>

<table><tr><td>II-1) - Taking floristic data on site</td><td>99</td></tr></table>

<table><tr><td>II-2) - Physical characterization of the raw material</td><td>100</td></tr></table>

<table><tr><td>II-3) - Chemical characterization of the raw material</td><td>101</td></tr></table>

<table><tr><td>II-4) - Proportionate mixtures of solution based on the fruits of Azadirachta indica with the solution based on Eichhornia crassipes</td><td>102</td></tr></table>

<table><tr><td>II-5)-Monitoring physicochemical parameters during fermentation</td><td>103</td></tr></table>

<table><tr><td>CONCLUSION</td><td>116</td></tr></table>

<table><tr><td>REFERENCES</td><td>117</td></tr></table>

<table><tr><td>EXERCISES AND CORRECTIONS ON THE PRODUCTION OF BIOETHANOL BASED ON EICHHORNIA CRASSIPES ASSOCIATED WITH THE PULP OF THE RIPE FRUIT OF AZADIRACHTA INDICA</td><td>120</td></tr></table>

<table><tr><td>PARTIE 3: EDUCATION ENVIRONNEMERSEPTION DES CHANGEMENTS CLIMATIQUES</td><td>125</td></tr></table>

<table><tr><td>1. Impact of Environmental Education on the Perception of Climate Change</td><td>126</td></tr></table>

<table><tr><td>2. Approaches to Optimizing Environmental Education on Climate Change</td><td>126</td></tr></table>

<table><tr><td>3. Evaluation of the Effectiveness of Environmental Education</td><td>127</td></tr></table>

<table><tr><td>4. Examples of Good Practices</td><td>127</td></tr></table>

<table><tr><td>CHAPTER 1. ENVIRONMENTAL EDUCATION: COMPARATIVE STUDY OF THE PERFORMANCE OF TWO TRAINING METHODS IN SAHELIAN FARMING ENVIRONMENTS</td><td>129</td></tr></table>

<table><tr><td>ABSTRACT</td><td>129</td></tr></table>

<table><tr><td>INTRODUCTION</td><td>129</td></tr></table>
<table><tr><td>1- MATERIALS AND METHOD</td><td>130</td></tr><tr><td>1-1 Study sites</td><td>130</td></tr><tr><td>1-1 Data collection method</td><td>131</td></tr><tr><td>1-2- Data analysis</td><td>132</td></tr><tr><td>2- RESULTS</td><td>132</td></tr><tr><td>2-1 Characteristics of the trained people surveyed</td><td>132</td></tr><tr><td>2-2 Training objectives via the theoretical andragogy method</td><td>134</td></tr><tr><td>2-3 Training objectives via the practical andragogy method</td><td>135</td></tr><tr><td>2-4 Training objectives via the theoretical teaching method</td><td>136</td></tr><tr><td>2-5 Training objectives via the practical teaching method</td><td>137</td></tr><tr><td>3- Analysis</td><td>138</td></tr><tr><td>3-1 Average participation rate in training sessions</td><td>138</td></tr><tr><td>3-2 Level of satisfaction of those trained</td><td>141</td></tr><tr><td>Discussion</td><td>145</td></tr><tr><td>CONCLUSION</td><td>147</td></tr><tr><td>Bibliographic reference</td><td>148</td></tr><tr><td>EXERCISES AND CORRECTIONS ON ENVIRONMENTAL EDUCATION: COMPARATIVE STUDY OF THE PERFORMANCE OF TWO TRAINING METHODS IN SAHELIAN FARMING ENVIRONMENTS</td><td>148</td></tr><tr><td>CHAPTER 2. STUDY OF THE IMPACT OF GLOBAL WARMING ON THE PRODUCTIVITY AND HUMAN COMFORT OF WORKERS OF FARMERS' ORGANIZATIONS IN THE SAHELIAN ZONE OF CAMEROON</td><td>153</td></tr><tr><td>ABSTRACT</td><td>153</td></tr><tr><td>INTRODUCTION</td><td>153</td></tr><tr><td>1- MATERIALS AND METHOD</td><td>154</td></tr><tr><td>1.1-Study sites</td><td>154</td></tr><tr><td>1.2- Data collection method</td><td>155</td></tr><tr><td>1.3-Data analysis</td><td>156</td></tr><tr><td>1.4- Impacts of heat exposure in the workplace</td><td>158</td></tr><tr><td>1.5- Trends in climate change and heat stress in Sahelian cities</td><td>158</td></tr><tr><td>2-) - RESULT AND DISCUSSION</td><td>159</td></tr><tr><td>2-1) - Characteristics linked to the workers, operators and farms surveyed</td><td>159</td></tr><tr><td>2-2)- Assessment of heat stress in the workplace within GICs and associations</td><td>163</td></tr><tr><td>2-3-) - Metabolic heat generated by human physical activity</td><td>166</td></tr><tr><td>2-4) - Physiological and clinical impacts of heat stress</td><td>174</td></tr><tr><td>2-5) - Impacts of heat exposure in the workplace</td><td>176</td></tr><tr><td>2-6) - Trends in climate change and heat stress in Sahelian cities</td><td>180</td></tr></table>
<table><tr><td>CONCLUSION</td><td>184</td></tr><tr><td>REFERENCE</td><td>185</td></tr><tr><td>EXERCISES AND ANSWERS ON THE STUDY OF THE IMPACT OF GLOBAL WARMING ON THE PRODUCTIVITY AND HUMAN COMFORT OF WORKERS OF PEASANT ORGANIZATIONS IN THE SAHELIAN ZONE OF CAMEROON</td><td>189</td></tr><tr><td>CHAPITRE 3. GENDER, PERCEPTION OF CLIMATE CHANGE IN THE CAMEROONIAN SAHEL AND IMPACTS ON WOMEN'S PEASANT ORGANIZATIONS</td><td>192</td></tr><tr><td>ABSTRACT</td><td>192</td></tr><tr><td>INTRODUCTION</td><td>192</td></tr><tr><td>1- MATERIALS AND METHOD</td><td>193</td></tr><tr><td>1-1- Study sites</td><td>193</td></tr><tr><td>1-2-Data collection method</td><td>194</td></tr><tr><td>1-3-Data analysis</td><td>195</td></tr><tr><td>1-4- Assessment of heat stress in the workplace</td><td>196</td></tr><tr><td>1-5- Physiological and clinical impacts of heat stress</td><td>196</td></tr><tr><td>1-6- Impacts of heat exposure in the workplace</td><td>197</td></tr><tr><td>1-7-Impacts of heat exposure on worker productivity in the workplace</td><td>197</td></tr><tr><td>1-8- Trends in climate change and heat stress in Sahelian cities</td><td>198</td></tr><tr><td>RESULTS</td><td>198</td></tr><tr><td>1- CHARACTERISTICS RELATED TO THE FARMS SURVEYED</td><td>198</td></tr><tr><td>1-1)- Characteristics linked to the workers and operators surveyed</td><td>198</td></tr><tr><td>1-2)- Characteristics linked to the farms surveyed</td><td>199</td></tr><tr><td>1-3)- Main plant species produced, areas exploited and yields</td><td>200</td></tr><tr><td>1-4)- Area covered by the activity and output of producers' work</td><td>201</td></tr><tr><td>2- Perception of rainfall disturbances</td><td>202</td></tr><tr><td>3- Perception of thermal disturbances</td><td>206</td></tr><tr><td>4)- Typology of operations depending on the type of disturbance perceived</td><td>208</td></tr><tr><td>5- Impacts of exposure to heat on climate perceptions within GICs and associations</td><td>210</td></tr><tr><td>5-1)- Assessment of heat stress in the workplace</td><td>210</td></tr><tr><td>5-2)- Metabolic heat generated by human physical activity</td><td>211</td></tr><tr><td>5-3)- Physiological and clinical impacts of heat stress</td><td>220</td></tr><tr><td>5-5)- Trends in climate change and heat stress in Sahelian cities</td><td>226</td></tr><tr><td>CONCLUSION</td><td>230</td></tr><tr><td>REFERENCE</td><td>230</td></tr><tr><td>EXERCISES AND CORRECTIONS ON WOMEN (GENDER), PERCEPTION OF CLIMATE CHANGE IN SAHEL ZONES AND IMPACTS ON WOMEN'S FARMER ORGANIZATIONS</td><td>233</td></tr></table>
<table>
  <tbody>
    <tr>
      <td>CHAPTER 4. CHARACTERISTICS, PERCEPTION OF CLIMATIC CHANGES IN THE HUMID AND SEMI-ARID ZONE AND ADAPTATION STRATEGIES OF FARMER ORGANIZATIONS TO THE EFFECTS OF THE RISE IN AMBIENT TEMPERATURE OF THE SAHELIAN REGION</td>
      <td>237</td>
    </tr>
    <tr>
      <td>ABSTRACT</td>
      <td>237</td>
    </tr>
    <tr>
      <td>INTRODUCTION</td>
      <td>238</td>
    </tr>
    <tr>
      <td>1- MATERIALS AND METHOD</td>
      <td>239</td>
    </tr>
    <tr>
      <td>1-1 Study sites</td>
      <td>239</td>
    </tr>
    <tr>
      <td>1-2 Data collection method</td>
      <td>240</td>
    </tr>
    <tr>
      <td>1-3- Data analysis</td>
      <td>241</td>
    </tr>
    <tr>
      <td>RESULTS</td>
      <td>241</td>
    </tr>
    <tr>
      <td>1) - Characteristics related to the farms of the GICs and associations surveyed</td>
      <td>241</td>
    </tr>
    <tr>
      <td>1-1) - Characteristics related to the workers and operators of the GICs and associations surveyed</td>
      <td>241</td>
    </tr>
    <tr>
      <td>1-2) - Characteristics related to the farms of the GICs and associations surveyed</td>
      <td>243</td>
    </tr>
    <tr>
      <td>1-3) - Main plant species produced, areas exploited and yields</td>
      <td>244</td>
    </tr>
    <tr>
      <td>1-4) - Area covered by the activity and output of the producers' work</td>
      <td>244</td>
    </tr>
    <tr>
      <td>2- Perception of rainfall disturbances</td>
      <td>246</td>
    </tr>
    <tr>
      <td>3- Perception of thermo-periodic disturbances</td>
      <td>248</td>
    </tr>
    <tr>
      <td>4- Typology of farms according to the type of disturbance perceived</td>
      <td>250</td>
    </tr>
    <tr>
      <td>5-Local strategies for adaptation to climate disturbances within GICs and associations</td>
      <td>252</td>
    </tr>
    <tr>
      <td>5-1- Local economic strategies for adaptation to climate disruptions within GICs and associations</td>
      <td>252</td>
    </tr>
    <tr>
      <td>5-2- Local social strategy for adaptation to climate disturbances within GICs and associations</td>
      <td>256</td>
    </tr>
    <tr>
      <td>2-3- Local environmental adaptation strategy to climate disturbances within GICs and associations</td>
      <td>258</td>
    </tr>
    <tr>
      <td>CONCLUSION</td>
      <td>262</td>
    </tr>
    <tr>
      <td>REFERENCES</td>
      <td>264</td>
    </tr>
    <tr>
      <td>CHAPTER 5. ECONOMIC INDEX OF ECOLOGICAL CHARCOAL BASED ON PROSOPIS JULIFLORA_EICHHORNIA CRASSIPES MIX AND THEIR CARBON SEQUESTRATION POTENTIAL</td>
      <td>268</td>
    </tr>
    <tr>
      <td>INTRODUCTION</td>
      <td>268</td>
    </tr>
    <tr>
      <td>I- MATERIALS AND METHOD</td>
      <td>269</td>
    </tr>
    <tr>
      <td>I-1) - Study sites</td>
      <td>269</td>
    </tr>
    <tr>
      <td>I-2) - Sampling of biomass and preparation of ecological charcoal samples</td>
      <td>270</td>
    </tr>
    <tr>
      <td>I-3) Physico-chemical characterization of ecological charcoal samples based on Prosopis juliflora linked to Eichhornia Crassipes</td>
      <td>272</td>
    </tr>
  </tbody>
</table>
<table>
  <tr>
    <td>I-4) Calorific value and energy efficiency of ecological charcoal</td>
    <td>273</td>
  </tr>
  <tr>
    <td>I-5) Economic Value Index of Ecological Coal (EVI)</td>
    <td>274</td>
  </tr>
  <tr>
    <td>I-6) Technological Yield of Ecological Coal</td>
    <td>274</td>
  </tr>
  <tr>
    <td>I-7) Commercial performance</td>
    <td>274</td>
  </tr>
  <tr>
    <td>II-) RESULTS</td>
    <td>275</td>
  </tr>
  <tr>
    <td>II-1) - Invasive floristic composition of the study area</td>
    <td>275</td>
  </tr>
  <tr>
    <td>II-2) - Sampling of biomass and preparation of ecological charcoal samples</td>
    <td>276</td>
  </tr>
  <tr>
    <td>II-3) Physico-chemical characterization of ecological charcoal samples based on Prosopis juliflora linked to Eichhornia crassipes</td>
    <td>282</td>
  </tr>
  <tr>
    <td>II-4) Energy efficiency of ecological charcoal</td>
    <td>283</td>
  </tr>
  <tr>
    <td>II-8) Economic Value Index of ecological charcoal (EVI)</td>
    <td>284</td>
  </tr>
  <tr>
    <td>DISCUSSION</td>
    <td>285</td>
  </tr>
  <tr>
    <td>CONCLUSION</td>
    <td>286</td>
  </tr>
  <tr>
    <td>REFERENCES</td>
    <td>287</td>
  </tr>
  <tr>
    <td>EXERCISES AND CORRECTIONS ON THE ECONOMIC INDEX OF ECOLOGICAL COAL BASED ON THE PROSOPIS JULIFLORA_EICHHORNIA CRASSIPES MIX AND CARBON SEQUESTRATION POTENTIAL</td>
    <td>291</td>
  </tr>
  <tr>
    <td>CHAPITRE 6. IMPACT OF THE PROLIFERATION OF INVASIVE PLANTS ON BIODIVERSITY AND WOMEN'S SOCIO-ECONOMIC ADAPTATION STRATEGIES IN THE LAKE CHAD AREA</td>
    <td>293</td>
  </tr>
  <tr>
    <td>Introduction</td>
    <td>295</td>
  </tr>
  <tr>
    <td>2. MATERIALS AND METHODS</td>
    <td>296</td>
  </tr>
  <tr>
    <td>2.1. Study Area</td>
    <td>296</td>
  </tr>
  <tr>
    <td>3. The productivity of Eichhornia crassipes in Lake Chad</td>
    <td>297</td>
  </tr>
  <tr>
    <td>3.1. The absolute growth rate (TDA)</td>
    <td>297</td>
  </tr>
  <tr>
    <td>3.2. Assessment of multiplication speed</td>
    <td>298</td>
  </tr>
  <tr>
    <td>3.3. Modeling the potential evolution of Eichhornia crassipes in Lake Chad</td>
    <td>298</td>
  </tr>
  <tr>
    <td>3-4. Physico-chemical characterization of water from the Eichhornia crassipes sampling site</td>
    <td>299</td>
  </tr>
  <tr>
    <td>3-5. Assessment of the wildlife biomass of Lake Chad</td>
    <td>299</td>
  </tr>
  <tr>
    <td>3.6. Data analysis</td>
    <td>299</td>
  </tr>
  <tr>
    <td>4. RESULTS AND DISCUSSION</td>
    <td>300</td>
  </tr>
  <tr>
    <td>4.1. Assessment of available invasive biomass and density</td>
    <td>300</td>
  </tr>
  <tr>
    <td>4.2. Biomass of vegetation by city in the Lake Chad area Cameroon</td>
    <td>301</td>
  </tr>
  <tr>
    <td>4.3 Abundance-dominance indices of Eichhornia crassipes on site</td>
    <td>307</td>
  </tr>
  <tr>
    <td>4.4. Presence of Eichhornia crassipes in the sampling sites</td>
    <td>307</td>
  </tr>
</table>
<table>
  <tr>
    <td>4.5. Physico-chemical characterization of water from the Eichhornia crassipes sampling site in the Lake Chad area Cameroon</td>
    <td>308</td>
  </tr>
  <tr>
    <td>4.6. Characterization of Eichhornia crassipes samples</td>
    <td>311</td>
  </tr>
  <tr>
    <td>4.7. The productivity of Eichhornia crassipes in Lake Chad</td>
    <td>311</td>
  </tr>
  <tr>
    <td>4.8. Assessment of multiplication speed</td>
    <td>315</td>
  </tr>
  <tr>
    <td>4.9. Local adaptation strategies for disturbances linked to invasive plants</td>
    <td>324</td>
  </tr>
  <tr>
    <td>CONCLUSION</td>
    <td>327</td>
  </tr>
  <tr>
    <td>REFERENCE</td>
    <td>329</td>
  </tr>
  <tr>
    <td>EXERCISES AND CORRECTIONS ON THE IMPACT OF THE PROLIFERATION OF INVASIVE PLANTS ON BIODIVERSITY AND THE SOCIO-ECONOMIC ADAPTATION STRATEGIES OF WOMEN IN THE LAKE CHAD AREA</td>
    <td>332</td>
  </tr>
  <tr>
    <td>CHAPITRE 7. ECOLOGICAL MODELING, FUEL ECONOMY, ENERGY AUTONOMY AND COMMUNITY ACCEPTABILITY OF IMPROVED STOVE-OVENS</td>
    <td>336</td>
  </tr>
  <tr>
    <td>ABSTRACT</td>
    <td>336</td>
  </tr>
  <tr>
    <td>INTRODUCTION</td>
    <td>337</td>
  </tr>
  <tr>
    <td>1- MATERIAL AND METHOD</td>
    <td>338</td>
  </tr>
  <tr>
    <td>1-1 Study sites</td>
    <td>338</td>
  </tr>
  <tr>
    <td>1-2- Design and dimensioning of the structure of some improved stoves used in the Far North Cameroon</td>
    <td>339</td>
  </tr>
  <tr>
    <td>1-3- Materials for manufacturing the internal components of the hearths</td>
    <td>339</td>
  </tr>
  <tr>
    <td>1-4- Expected calorific and energy yield of combustion chambers</td>
    <td>340</td>
  </tr>
  <tr>
    <td>1-5- Fuel economy and energy autonomy of improved stoves</td>
    <td>346</td>
  </tr>
  <tr>
    <td>2- RESULT AND DISCUSSION</td>
    <td>346</td>
  </tr>
  <tr>
    <td>2-1- Design and dimensioning of the structure of some improved stoves used in the Far North of Cameroon</td>
    <td>346</td>
  </tr>
  <tr>
    <td>2-2- Characteristics of improved hearths</td>
    <td>347</td>
  </tr>
  <tr>
    <td>2-3- Earth and/or ceramic hearth-ovens</td>
    <td>348</td>
  </tr>
  <tr>
    <td>2-4- Metal hearth-ovens</td>
    <td>348</td>
  </tr>
  <tr>
    <td>2-4- Brick and cement hearths</td>
    <td>349</td>
  </tr>
  <tr>
    <td>2-5- The mixed clay-metal hearth-ovens of SAHEL NATURE CONSULTING</td>
    <td>350</td>
  </tr>
  <tr>
    <td>2-6- Expected calorific and energy efficiency of combustion hearths</td>
    <td>351</td>
  </tr>
  <tr>
    <td>2-7- Decontamination of fumes and toxic pollutants in the air</td>
    <td>356</td>
  </tr>
  <tr>
    <td>2-8- Fuel economy and energy autonomy of improved stoves</td>
    <td>359</td>
  </tr>
  <tr>
    <td>CONCLUSION</td>
    <td>361</td>
  </tr>
  <tr>
    <td>Reference</td>
    <td>363</td>
  </tr>
  <tr>
    <td>EXERCISES AND CORRECTIONS ON ECOLOGICAL MODELING, FUEL ECONOMY, ENERGY AUTONOMY AND COMMUNITY ACCEPTABILITY OF IMPROVED STOVE-OVENS</td>
    <td>366</td>
  </tr>
</table>
Table 7: Overall energy efficiency of ecological charcoal based on Azadirachta indica (80%) linked to inorganic matter (sand (20%) or clay (20%)) .................................................. 82

Table 8: Overall energy efficiency of samples of ecological charcoal based on *Azadirachta indica* (90%) linked to organic matter (*Sorghum sp.* stem (10%), or *Zea mays* L. stem (10%), or *Acacia seyal* sap (10%) or *Saccharum officinarum* peel (10%)) .................................................. 82

Table 9: Cooking test with samples of ecological charcoal based on *Azadirachta indica* (80%) bound to inorganic and organic matter (20%) .................................................................................. 84

## CHAPTER 4. PRODUCTION OF BIOETHANOL BASED ON EICHHORNIA CRASSIPES COMBINED WITH THE PULP OF THE RIPE FRUIT OF AZADIRACHTA INDICA .................................................................................................................. 92

Table 1: Estimation of spatial heterogeneity of biomasses .................................................................................. 99

Table 2: Quantification of species present on the sites .................................................................................. 99

Table 3: Average results of physical analyzes .................................................................................................. 100

Table 4: Result of chemical analysis of the raw material .................................................................................. 102

Table 5: Proportioned substrate mixtures........................................................................................................ 102

Table 6: Initial property of solutions.................................................................................................................. 103

Table 7: Weight yield .................................................................................................................................................. 116

## PARTIE 3: EDUCATION ENVIRONNEMERSEPTION DES CHANGEMENTS CLIMATIQUES .................................................................................................................. 125

## CHAPTER 1. ENVIRONMENTAL EDUCATION: COMPARATIVE STUDY OF THE PERFORMANCE OF TWO TRAINING METHODS IN SAHELIAN FARMING ENVIRONMENTS .................................................................................................................. 129

Table 1: Distribution of trained people surveyed .................................................................................. 133

Table 2: Characteristics of the trained people surveyed: gender, average age, level of education and number of years of professional experience .................................................................................. 133

Table 4: Average participation rate for theoretical training sessions with the andragogy method.................................................................................................................................................................................. 134

Table 5: Level of satisfaction of those trained with the progress of the different theoretical training modules via the andragogy method.................................................................................. 134

Table 6: Average participation rate for practical training sessions with the andragogy method.................................................................................................................................................................................. 135

Table 7: Level of satisfaction of people trained during the different practical training modules via the andragogy method.................................................................................. 135

Table 8: Average participation rate for theoretical training sessions with the teaching method.................................................................................................................................................................................. 136

Table 9: Level of satisfaction of those trained with the progress of the different theoretical training modules via the teaching method.................................................................................. 137

Table 10: Average participation rate for practical training sessions with the teaching method.................................................................................................................................................................................. 137
<table>
  <tbody>
    <tr>
      <td>Table 5: Preparation of raw materials</td>
      <td>278</td>
    </tr>
    <tr>
      <td>Table 6: Mass yield before and after carbonization of raw materials</td>
      <td>280</td>
    </tr>
    <tr>
      <td>Table 7: Sized samples of ecological coal</td>
      <td>281</td>
    </tr>
    <tr>
      <td>Table 8: Proportion of raw material-binder mixed</td>
      <td>281</td>
    </tr>
    <tr>
      <td>Table 9: Density of ecological charcoal based on carbonized and ground <i>Prosopis juliflora</i> and <i>Eichhornia crassipes</i> bound to clay</td>
      <td>282</td>
    </tr>
    <tr>
      <td>Table 10: Physico-chemical characteristics</td>
      <td>282</td>
    </tr>
    <tr>
      <td>Table 11: Fuel energy efficiency tests</td>
      <td>283</td>
    </tr>
    <tr>
      <td>Table 12: Economic Value Index of ecological charcoal</td>
      <td>284</td>
    </tr>
    <tr>
      <td>CHAPITRE 5. IMPACT OF THE PROLIFERATION OF INVASIVE PLANTS ON BIODIVERSITY AND WOMEN'S SOCIO-ECONOMIC ADAPTATION STRATEGIES IN THE LAKE CHAD AREA</td>
      <td>293</td>
    </tr>
    <tr>
      <td>Table 1: Density of <i>Eichhornia crassipes</i> samples collected by batch between August-September 2022</td>
      <td>300</td>
    </tr>
    <tr>
      <td>Table 2: Cross-tabulation of types of shrub layer biomass by city</td>
      <td>302</td>
    </tr>
    <tr>
      <td>Table 3: Estimation of the spatial heterogeneity of <i>Eichhornia Crassipes</i> and <i>Prosopis juliflora</i> in the water territories of Lake Chad Cameroon</td>
      <td>307</td>
    </tr>
    <tr>
      <td>Table 4: Quantification of species present on the sites</td>
      <td>308</td>
    </tr>
    <tr>
      <td>Table 5: Density of <i>Eichhornia crassipes</i> samples collected by batch between August-September 2022</td>
      <td>308</td>
    </tr>
    <tr>
      <td>Table 6: Physico-chemical parameters of effluents at the sites (sample collection points</td>
      <td>310</td>
    </tr>
    <tr>
      <td>Table 7: Chemical characterization of <i>Eichhornia crassipes</i> in the Lake Chad area Cameroon</td>
      <td>311</td>
    </tr>
    <tr>
      <td>Table 8: Physico-chemical parameters of growth waters of <i>Eichhornia crassipes</i> samples</td>
      <td>312</td>
    </tr>
    <tr>
      <td>Table 9: Absolute rate of increase (ARI) in the quantity of fresh biomass of Eichhornia crassipes as a function of time</td>
      <td>315</td>
    </tr>
    <tr>
      <td>Table 10: Parameters of the water sample collection locations used to evaluate the rate of multiplication of fresh biomass of Eichhornia crassipes</td>
      <td>315</td>
    </tr>
    <tr>
      <td>Table 11: Evaluation of the multiplication speed of fresh biomass of <i>Eichhornia crassipes</i> as a function of time</td>
      <td>317</td>
    </tr>
    <tr>
      <td>Table 12: Density of <i>Eichhornia crassipes</i> samples collected by batch between August-September 2022</td>
      <td>320</td>
    </tr>
    <tr>
      <td>Table 13: Identification of substrates (% coverage) and speed classes characterizing them</td>
      <td>321</td>
    </tr>
    <tr>
      <td>Table 14: Sampling table</td>
      <td>322</td>
    </tr>
    <tr>
      <td>Table 15: Sensitivity scores of indicator taxa of the Lake Chad Biotic Index (LCBI) and the Biosedimentary Index (BSI)</td>
      <td>322</td>
    </tr>
    <tr>
      <td>Table 16: Quality classes for LCBI and BSI (7 unit samples)</td>
      <td>324</td>
    </tr>
  </tbody>
</table>
<table>
  <tbody>
    <tr>
      <td>Table 17: Economic strategy for adaptation to disturbances linked to invasive plants</td>
      <td>325</td>
    </tr>
    <tr>
      <td>Table 18: Economic strategy for adapting agricultural production to disruptions linked to invasive plants</td>
      <td>325</td>
    </tr>
    <tr>
      <td>Table 19: Economic adaptation strategy linked to the market and the sale of products harvested by season in the face of disturbances linked to invasive plants</td>
      <td>326</td>
    </tr>
    <tr>
      <td>Table 20: Social strategy to adapt field production during the dry season</td>
      <td>327</td>
    </tr>
    <tr>
      <td>CHAPITRE 6. ECOLOGICAL MODELING, FUEL ECONOMY, ENERGY AUTONOMY AND COMMUNITY ACCEPTABILITY OF IMPROVED STOVE-OVENS</td>
      <td>336</td>
    </tr>
    <tr>
      <td>Table 1: Different materials for manufacturing improved earthenware (clay) hearth-ovens</td>
      <td>348</td>
    </tr>
    <tr>
      <td>Table 2: Different materials for manufacturing improved hearth-ovens (in metal)</td>
      <td>349</td>
    </tr>
    <tr>
      <td>Table 3: Different materials for manufacturing improved earthenware (clay) hearths-ovens</td>
      <td>350</td>
    </tr>
    <tr>
      <td>Table 4: Some prototypes of improved hearths studied in Maroua-Cameroon</td>
      <td>350</td>
    </tr>
    <tr>
      <td>Table 5: Different dimensions of improved ecological hearth-ovens made of clay</td>
      <td>351</td>
    </tr>
    <tr>
      <td>Table 6: Calorific value and expected combustion tests in the combustion chamber</td>
      <td>352</td>
    </tr>
    <tr>
      <td>Table 7: Qualitative characteristics of the product efficiency of improved ecological hearth-ovens</td>
      <td>352</td>
    </tr>
    <tr>
      <td>Table 8: Ease of ignition and energy efficiency of combustion chambers</td>
      <td>354</td>
    </tr>
    <tr>
      <td>Table 9: Expected energy yields from the arrangement of fuels in a carbonization pile</td>
      <td>354</td>
    </tr>
    <tr>
      <td>Table 10: Calorific value of the material according to the water content</td>
      <td>355</td>
    </tr>
    <tr>
      <td>Table 12: Sizing and permeability models (empirical model, flow through a random arrangement of fibers)</td>
      <td>356</td>
    </tr>
    <tr>
      <td>Table 13: Brownian diffusion and direct interception diffusion</td>
      <td>357</td>
    </tr>
    <tr>
      <td>Table 14: Diffusion by inertial impaction and sedimentation of particles</td>
      <td>358</td>
    </tr>
    <tr>
      <td>Table 15: Particle collection efficiency and performance of fibrous media in filtration</td>
      <td>358</td>
    </tr>
    <tr>
      <td>Table 16: Analysis of particles collected by smoke filters of improved stoves</td>
      <td>358</td>
    </tr>
    <tr>
      <td>Table 17: Energy efficiency of carbonization in the combustion chamber</td>
      <td>359</td>
    </tr>
    <tr>
      <td>Table 18: Acceptability rate of improved stoves in households</td>
      <td>360</td>
    </tr>
  </tbody>
</table>
Graph 1: Major global physical parameters of ecological charcoal based on *Azadirachta indica* (80%) linked to organic matter (20%) and inorganic matter (20%) ................................. 79

Graph 2: Overall chemical parameters of samples of ecological charcoal based on *Azadirachta indica* (80%) linked to organic matter (20%) ................................................................. 81

Graph 3: Parameters Overall energy efficiency of samples of ecological charcoal based on *Azadirachta indica* (80%) linked to organic matter (*Sorghum sp.* stem (20%)) ................................. 83

Graph 4: Baking test parameters .................................................................................................................. 85

## CHAPTER 3. PRODUCTION OF BIOETHANOL BASED ON *EICHHORNIA CRASSIPES* COMBINED WITH THE PULP OF THE RIPE FRUIT OF *AZADIRACHTA INDICA*.................................................................................................................. 92

Graph 1: Evolution of pH during fermentation .................................................................................. 104

Graph 2: Evolution of density during fermentation ........................................................................ 105

Graph 3: Evolution of the reducing sugar content during fermentation.................................. 107

Graph 4: Evolution of the alcohol content during fermentation.................................................. 108

Graph 5: Volatile Fatty Acid Content of solutions as a function of fermentation duration .................................................................................................................................................................................. 110

Graph 7: Volatile Fatty Acid Content (VFA in mg/g) as a function of fermentation duration in samples from batch 1 (2.5% water +5% substrate +2.5% yeast) ................................. 114

## PARTIE 3: EDUCATION ENVIRONNEMERSEPTION DES CHANGEMENTS CLIMATIQUES.................................................................................................................. 125

## CHAPTER 1. ENVIRONMENTAL EDUCATION: COMPARATIVE STUDY OF THE PERFORMANCE OF TWO TRAINING METHODS IN SAHELIAN FARMING ENVIRONMENTS.................................................................................................................. 129

Graph 1: Average participation rate in theoretical and practical training sessions with the andragogy method .................................................................................................................. 139

Graph 2: Average participation rate in theoretical and practical training sessions with the teaching method .................................................................................................................. 140

Graph 3: Average participation rate in practical training sessions ............................................ 141

Graph 4: Average satisfaction levels of people trained in good environmental practices .................................................................................................................................................................................. 142

Graph 5: Average satisfaction levels of people trained in good environmental practices by andragogy method training modules.................................................................................. 143

Graph 6: Average satisfaction levels of people trained in good environmental practices by training modules with the educational method .................................................................................. 144

Graph 7: Average satisfaction levels of people trained in good environmental practices by training module.................................................................................................................................................. 145

## CHAPTER 2. STUDY OF THE IMPACT OF GLOBAL WARMING ON THE PRODUCTIVITY AND HUMAN COMFORT OF WORKERS OF FARMERS' ORGANIZATIONS IN THE SAHELIAN ZONE OF CAMEROON ................................. 153

Graph 1: Light workplace heat stress during dry and rainy seasons............................................ 164
Graph 2: Thermal stress at the work site medium, intense and very intense during the dry and rainy seasons ..................................................................................................................165

Graph 3: Protection against sunstroke and number of hours of rest in the shade between 10 a.m.-4 p.m. ..................................................................................................................166

Graph 4: Level of protection against sunstroke via hydration and water supply............167

Graph 5: Level of protection against insolation via ventilation systems ........................168

Graph 6: Level of protection against sunstroke via clothing protection systems............169

Graph 8: Activity level according to the average metabolic temperature generated by human physical activity (°C)..................................................................................................................171

Graph 9: Activity level according to the level of protection against sunstroke............173

Graph 10: Evaluation of the heat balance due to work in the dry season ........................174

Graph 11: Evaluation of the heat balance due to work in the dry season ........................175

Graph 14: Wet Bulb Globe Temperature (WBGT) index calculated..................................179

Graph 15: Maximum temporal trends, fitted line and temperature increase for humid and semi-arid areas ..................................................................................................................181

Graph 16: Mean temporal trends, fitted line, and temperature increase for humid and semi-arid areas ..................................................................................................................182

Graph 17: Temporal trends mean minimums, fitted line, and temperature increase for humid and semi-arid areas..................................................................................................................183

## CHAPITRE 3. GENDER, PERCEPTION OF CLIMATE CHANGE IN THE CAMEROONIAN SAHEL AND IMPACTS ON WOMEN'S PEASANT ORGANIZATIONS ..................................................................................................................192

Graph 1: Average area covered by agricultural activity/Farmer ........................................202

Graph 2: Perception of rainfall disturbances ........................................................................203

Graph 3: Perception of the consequences of rainfall disturbances ........................................205

Graph 4: Temperature felt on site during working hours and main professional activities carried out by GIC members (°C)..................................................................................................................207

Graph 5: Correlation between perceived types of disturbance and farmer-related parameters ..................................................................................................................209

Graph 6: Protection against sunstroke and number of hours of rest in the shade between 10 a.m.-4 p.m. ..................................................................................................................212

Graph 7: Level of protection against sunstroke via hydration and water supply............213

Graph 8: Level of protection against insolation via ventilation systems ........................214

Graph 9: Level of protection against sunstroke via clothing protection systems............215

Graph 10: Level of protection against sunstroke depending on the average metabolic temperature generated by human physical activity (°C)..................................................................................................................216

Graph 11: Activity level according to the average metabolic temperature generated by human physical activity (°C)..................................................................................................................217

Graph 12: Activity level according to the level of protection against sunstroke............219
<table>
  <tbody>
    <tr>
      <td>Graph 13: Evaluation of the heat balance due to work</td>
      <td>221</td>
    </tr>
    <tr>
      <td>Graph 14: Work intensity during light and medium work</td>
      <td>223</td>
    </tr>
    <tr>
      <td>Graph 15: Work intensity during heavy and very heavy work</td>
      <td>224</td>
    </tr>
    <tr>
      <td>Graph 16: Wet Bulb Globe Temperature (WBGT) index calculated</td>
      <td>225</td>
    </tr>
    <tr>
      <td>Graph 17: Maximum temporal trends, fitted line, temperature increase for humid and semi-arid areas</td>
      <td>227</td>
    </tr>
    <tr>
      <td>Graph 19: Temporal trends mean minimums, fitted line and temperature increase for humid and semi-arid areas</td>
      <td>229</td>
    </tr>
    <tr>
      <td>CHAPTER 4. CHARACTERISTICS, PERCEPTION OF CLIMATIC CHANGES IN THE HUMID AND SEMI-ARID ZONE AND ADAPTATION STRATEGIES OF FARMER ORGANIZATIONS TO THE EFFECTS OF THE RISE IN AMBIENT TEMPERATURE OF THE SAHELIAN REGION</td>
      <td>237</td>
    </tr>
    <tr>
      <td>Graph 1: Average area covered by agricultural activity/Operator</td>
      <td>245</td>
    </tr>
    <tr>
      <td>Graph 2: Perception of rainfall disturbances</td>
      <td>246</td>
    </tr>
    <tr>
      <td>Graph 3: Perception of the consequences of rainfall disturbances</td>
      <td>248</td>
    </tr>
    <tr>
      <td>Graph 4: Temperature felt on site during working hours and main professional activities carried out by GIC members (°C)</td>
      <td>249</td>
    </tr>
    <tr>
      <td>Graph 5: Correlation between perceived disturbance types and parameters related to farmers</td>
      <td>251</td>
    </tr>
    <tr>
      <td>Graph 6: Economic strategy for adapting field production during the dry season</td>
      <td>253</td>
    </tr>
    <tr>
      <td>Graph 7: Economic strategy for adapting field production during the rainy season</td>
      <td>254</td>
    </tr>
    <tr>
      <td>Graph 8: Economic adaptation strategy linked to the sale of products harvested by season</td>
      <td>255</td>
    </tr>
    <tr>
      <td>Graph 9: Social strategy to adapt field production during the dry season</td>
      <td>257</td>
    </tr>
    <tr>
      <td>Graph 10: Social strategy for adapting field production during the rainy season</td>
      <td>258</td>
    </tr>
    <tr>
      <td>Graph 11: Average rates of local environmental adaptation strategic elements to climate disturbances within the GICs and association during the dry season</td>
      <td>259</td>
    </tr>
    <tr>
      <td>Graph 12: Average rates of local environmental strategic elements for adaptation to climate disturbances within the GICs and association during the rainy season</td>
      <td>261</td>
    </tr>
    <tr>
      <td>CHAPTER 5. ECONOMIC INDEX OF ECOLOGICAL CHARCOAL BASED ON PROSOPIS JULIFLORA EICHHORNIA CRASSIPES MIX AND THEIR CARBON SEQUESTRATION POTENTIAL</td>
      <td>268</td>
    </tr>
    <tr>
      <td>CHAPTER 6. IMPACT OF THE PROLIFERATION OF INVASIVE PLANTS ON BIODIVERSITY AND WOMEN'S SOCIO-ECONOMIC ADAPTATION STRATEGIES IN THE LAKE CHAD AREA</td>
      <td>293</td>
    </tr>
    <tr>
      <td>Graph 1: Quantitative evolution and absolute rate of increase in the quantity of fresh biomass of Eichhornia crassipes in the dry and rainy season by quadrats</td>
      <td>314</td>
    </tr>
    <tr>
      <td>Graph 2: Quantitative evolution of Eichhornia crassipes in dry and rainy seasons</td>
      <td>316</td>
    </tr>
  </tbody>
</table>
<table>
  <tbody>
    <tr>
      <td>Figure 3: Schematic of the interception collection mechanism (Bémer et al., 2006 and Colin, 2013)</td>
      <td>345</td>
    </tr>
    <tr>
      <td>Figure 4: Schematic of the inertial impaction collection mechanism (Bémer et al., 2006; Colin, 2013).</td>
      <td>345</td>
    </tr>
    <tr>
      <td>Figure 5: Mechanisms of particle capture on a collector fiber by sieving (Laurence, 2006)</td>
      <td>346</td>
    </tr>
    <tr>
      <td>Figure 6: Particle capture mechanisms on a collector fiber by electrostatic effects (Laurence, 2006)</td>
      <td>346</td>
    </tr>
    <tr>
      <td>Figure 7: Improved stoves in Maroua-Cameroon</td>
      <td>347</td>
    </tr>
    <tr>
      <td>Figure 9: Geometric characterization of pleated filters by pitch and pleat height (Colin, 2013).</td>
      <td>357</td>
    </tr>
  </tbody>
</table>
List of abbreviations and symbols

* PM<sub>2.5</sub>: Fine airborne particles that have a diameter of 2.5 micrometers or less.

* CO: Carbon monoxide

* CO<sub>2</sub>: Carbon dioxide

* CH<sub>4</sub>: methane

* NGO: Non-Governmental Organization

* LWF: Lutheran World Federation

* CRBD: Complete Randomized Block Device

* IPCC: Intergovernmental Panel on Climate Change

* SOM: Soil Organic Matter

* NPK: Nitrogen Phosphorus Potassium

* C: Carbone

* H: Hydrogen

* O: Oxygen

* N: Azote

* S: Sulfur

* NIS: National Institute of Statistics

* LCBC: Lake Chad Basin Commission

* LSD: Least Significant Difference

* ANOVA: Analysis of variance (ANOVA)

* CRBD: Completely Randomized Block Design

* SPSS20.0: Statistical Package for the Social Sciences 20.0

* BA: Aerial Biomass

* BS: Underground biomass

* BT: Total biomass

* SC: Carbon stockEqC : Equivalent carbon

* PCI: Lower Calorific Value

* PCS: Higher Calorific Value

* CB: Compost_Biochar

* TGP: Treatments germination Percentage

* GM: Mega Joule

* J.A.F. Eichhorn: Johann Albrecht Friedrich Eichhorn

* ASTME711-87: "Standard Test Method for Determining the Amount of Water Soluble Chloride in Concrete and Concrete Raw Materials"

* MA Protocol, 108-P.Ca: Analysis Method Protocol, "P.Ca" could refer to the analysis of calcium (P for "Protocol" and "Ca" for "Calcium").

* BS EN 14 protocol: BS EN: This prefix indicates that the standard is a European standard adopted in the United Kingdom. European Standards
(EN) are often adopted as British Standards (BS) after publication. 14: This number could correspond to a specific code for a standard or protocol in a series.

* MOV: Volatile matter rate

* WHO: World Health Organization

* IUCN: International Union for Conservation of Nature

* MINEPAT: Ministry of the Economy, Planning and Regional Development.

* MINFOF: Ministry of Forests and Wildlife

* CRI: Impact Resistance Index

* NF: French Standard

* VFA: Volatile Fatty Acid

* COP28: 28th Conference of the Parties

* IPCC: Inter-governmental Panel on Climate Change

* RM: Average Recovery

* Pi: Presence index

* H': Shannon-Weaver index

* R: Regularity index

* AFNOR: French Standardization Association

* Saccharomyces cerevisiae ATCC 9763: a commercial enzyme with 7 FPU/g dry mass

* S. cerevisiae NBRC 2346: Saccharomyces cerevisiae strain NITE Biological Resource Center 2346

* pH: Hydrogen potential or negative logarithm of the concentration of hydrogen ions [H+] in a solution

* $NH_2CONH_2$: Carbamide or Urea

* $H_2SO_4$: Sulfuric Acid

* OIML method: Standards developed by the International Organization of Legal Metrology

* ST₁: Control Solution 1

* VFA: Volatile Fatty Acid

* CESNU: United Nations Commission on Higher Studies

* MS: Dry matter

* C/N ratio: Carbon/Nitrogen ratio

* MARPP: Active Method of Research and Participation Planning

* UNFCCC: United Nations Framework Convention on Climate Change

* UNFCCC: United Nations Framework Convention on Climate Change

* IDS: Investigative Data Services

* GIC: Common Initiative Groups

* WBGT: Wet Bulb Globe Temperature Index
* USDAAF: United States Department of Army Air Forces

* NIOSH: National Institute for Occupational Safety and Health

* Ha: Hectare

* MOC: Community workforce

* MOS: Employee workforce

* MOF: Family Labor

* %: Frequency or Percentage

* Km: Kilometer

* s: Second

* Km/h: kilometers per hour

* Km/s: kilometers per second

* Km/min: kilometers per minute

* KG/Season: Kilogram/Season

* kJ/kg/K: kilojoules / kilogram / Kelvin

* FCFA: Franc of the African Financial Community

* MOV: Volatile matter rate

* IVEC: Index of the Economic Value of Ecological Coal

* RMP: Weighted Mass Yield

* RC: Commercial Performance

* IVPC: Index of the Physical-Calorific Value of Ecological Coal

* USA: United States of America

* SE4ALL: Sustainable Energy for All

* KES: Kenyan Shilling

* USD: United States Dollar

* EIC: Economic Index of ecological charcoal

* IBS: Biosedimentary Index

* IBLT: the Biotic Index of Lake Chad

* RM: Average Recovery

* TDA: Absolute Growth Rate

* Pi: Presence index

* H': Shannon-Weaver index

* R: Regularity index

* MES: Suspended Matter

* $NH_4^+$: ammonium ion

* $NO_3^-$: nitrate ion

* N.T.K. : Potassium nitrate

* D.C.O. : Chemical Oxygen Demand

* BOD<sub>5</sub>: Biological Oxygen Demand in 5 days

* Total P: Total phosphate

* NP: Unpolluted Site;
* PMO: Site Polluted with Organic Matter;

* PMNO: Site Polluted with Non-Organic Matter

* EM: Metabolic energy

* MS: Dry Matter

* mg/l: Milligram per liter

* (NH₄) HCO₃: ammonium bicarbonate

* Na₂CO: Sodium carbonate

* H₂O: Water

* NaCO₃: Sodium carbonate
## Foreword

The growing awareness of the environmental challenges facing our planet pushed me to undertake the writing of this book ENVIRONMENTAL EDUCATION, MANAGEMENT OF PLANT RESOURCES FOR COOKING AND CLIMATE CHANGE PERCEPTIONS IN SAHEL was born from a deep reflection on the impact of our daily practices, in particular those linked to the use of plant resources for cooking, on our environment.

This book is part of a global context where deforestation, inadequate management of natural resources and climate change have become major concerns. The way we use and manage these resources has direct repercussions not only on our immediate environment but also on the climate balance on a global scale.

My objective with this work is to raise awareness, inform and propose concrete strategies for better management of so-called invasive plant resources. By emphasizing environmental education, I hope to offer readers, whether students, researchers, professionals or simply passionate about nature, tools to understand and act effectively in the face of these challenges.

I would like to express my gratitude to the administrative and technical staff of the NGO SAHEL NATURE CONSULTING FOR COMMUNITIES whose support and encouragement were essential to the realization of this project. Their expertise and dedication have enriched this work in an invaluable way.

I would also like to thank everyone who contributed to collecting data, proofreading the texts, and disseminating the ideas presented in this book. Their collaboration was a true source of inspiration.

This book is an invitation to rethink our practices, to adopt more sustainable cooking methods, and to become aware of the crucial importance of managing plant resources in the fight against climate change. I hope that the ideas presented here will inspire new initiatives and contribute to a future that is more respectful of our environment.

I now invite you to explore these pages, with the hope that this journey to the heart of environmental education and the management of plant resources will provoke reflection and action.

Happy reading.
Dedication

To all those for whom the environment is the only source
of wonder worth exploring
<figure><img src="image_3.png" /></figure>
# INTRODUCTION

Climate change has significant impacts on the environment, ecosystems, and plant resources. Environmental education plays a crucial role in raising awareness of climate issues and promoting sustainable practices for the management of plant resources.
Here's how these elements interact and approaches to tackling them:

## 1. Impacts of Climate Change on Plant Resources

- **Changing Climate Regimes:** Climate change leads to variations in temperatures, precipitation, and extreme events, affecting plant growth and distribution.

- **Risk for Biodiversity:** Climate change can threaten biodiversity by modifying natural habitats and endangering sensitive plant species.

- **Agricultural Yield Issues:** Increasing temperatures and changes in precipitation patterns can reduce agricultural yields, affecting food security.

- **Water Stress:** Variations in precipitation patterns can lead to water stress for crops and plant ecosystems.

<figure><img src="image_4.png" /></figure>

## 2. Role of Environmental Education

- **Climate Change Awareness:** Environmental education helps inform individuals and communities about the causes and consequences of climate change, with a focus on specific impacts on plant resources.

- **Promotion of Good Agricultural Practices:** Teach sustainable agricultural practices, such as integrated crop management, agroforestry, and water conservation, to mitigate the effects of climate change.

- **Training on Sustainable Management Techniques:** Train farmers, natural resource managers, and decision-makers on sustainable management techniques for plant resources, including the selection of resilient crops and soil conservation methods.

- **Climate Adaptation Skills Development:** Deliver educational programs on adaptation to climate change, including planning for variable climate conditions and implementing mitigation measures.

## 3. Strategies for the Sustainable Management of Plant Resources

- **Conservation of Plant Biodiversity:** Establish conservation programs to protect threatened plant species and maintain the genetic diversity of crops.

- **Water Management:** Implement water management techniques such as efficient irrigation, rainwater harvesting, and reuse of treated wastewater to support crop production.
**- Ecosystem Restoration:** Encourage the restoration of degraded ecosystems to improve the resilience of natural habitats and support plant biodiversity.

**- Sustainable Land Use:** Practice soil conservation through methods such as minimum tillage, plant cover, and moisture conservation techniques.

<figure><img src="image_5.png" /></figure>

**4. Tools and Approaches for Environmental Education**

**- School Programs and Curricula:** Integrate climate issues and sustainable management of plant resources into school programs and curricula to raise awareness from an early age.

**- Workshops and Seminars:** Organize workshops for agricultural sector professionals, natural resource managers, and local communities on climate impacts and sustainable management strategies.

**- Educational Resources:** Develop and disseminate guides, manuals, and training materials on sustainable agricultural practices and the management of plant resources in relation to climate change.

**- Awareness Campaigns:** Launch awareness campaigns to inform the general public about the impacts of climate change on plant resources and encourage them to adopt more sustainable behaviors

**5. Collaboration and Partnerships**

**- Partnerships with Non-Governmental Organizations (NGOs):** Collaborate with NGOs to develop and implement training programs and initiatives for sustainable management of plant resources.

**- Engagement of Local Communities:** Involve local communities in plant resource management projects and adaptation strategies to climate change, taking into account traditional knowledge and local practices.

In sum, climate change has significant effects on plant resources, and environmental education plays a crucial role in preparing individuals and communities for these challenges. By integrating sustainable management strategies and resilient practices, and promoting effective awareness, it is possible to minimize negative impacts and strengthen the resilience of plant ecosystems in the face of climate challenges.
# PART 1:
## ENVIRONMENT_MANAGEMENT OF
### PLANT RESOURCES FOR SOIL
#### RESTORATION
# CHAPITRE 1. OPTIMIZATION OF THE PRODUCTION OF TWO VARIETIES OF SORGUM (FADDA AND SOUMALEMBA) AMENDED WITH COMPOST BASED ON EICHHORNIA CRASSIPES LINKED TO URTICA DIOICA IN SAHEL AREAS NEAR LAKE CHAD

Alexis Dzokom¹, Jules Balna², Joël Tizé Koda³, Félix Watang Zieba², Roger Djouldé Darman⁴

¹Department of Environmental Sciences, National Advanced School of Engineering, University of Maroua, Cameroon

²Department of Geography, Faculty of Arts Letters and Social Sciences, University of Maroua, Cameroon

³Department of Renewable Energy, National Advanced School of Engineering, University of Maroua, Cameroon

⁴Department of Agriculture Animal Husbandry and By-Products, National Advanced School of Engineering, University of Maroua, Cameroon

## Abstract

Sorghum production during the rainy season in the Lake Chad basin presents yield difficulties linked to soil degradation and a difficult or catastrophic start to the season due to the late arrival of the rains. This problem often leads producers to desperately use chemical fertilizer amendments which ultimately contribute to further impoverishing the soil with inadequate yields. The objective here is to elucidate the responses of two varieties of sorghum (Fadda and Soumalemba) to nuanced additions of compost based on *Eichhornia crassipes* which could be oriented by meteorological information. The method based on tests on two experimental sites in split plot with six repetitions from 2021-2023 were conducted on two sites on sandy soils in rainfed conditions. Two varieties of sorghum were subjected to six fertilization treatment methods T₀, T₁, T₂, T₃, T₄, and T₅. Grain yields (1012.83± 303.18kg/ha on site 1 and 1018.75±296.01 kg/ha on site 2) varied depending on the interactive effect of the environment (805.33 ±158.35mm of water received on site 1 and 822± 211.08mm of water received on site 2) and fertilization. Late fertilization allowed stressed plants to resume their growth in the same way as if the additions were made early in the season. The staggered intake of the recommended dose (T₃) was more beneficial than the T₄ and T₅ treatments. The two varieties showed different responses from each other, with the Soumalemba variety responding better to late additions. Late additions of compost varied depending on the site and the increase in grain yield due to the late application of compost fluctuated over the years, depending on the meteorological parameters of the Sahelian localities.

**Keywords:** Compost, Sorghum, *Eichhornia crassipes*, *Urtica dioica*, Sahelian Zones

## INTRODUCTION
Agriculture in general is considered the human activity most dependent on climatic variations (Oram, 1989; Hansen, 2002). Sorghum (Sorghum bicolor (L.) Moench)) is one of the staple foods of millions of people in Africa (Gueye et al., 2016). The cultivation of sorghum, particularly in the Sudano-Sahelian zones of Africa, is faced with a certain number of constraints including low soil fertility (soil nutrient deficiencies) (Vanlauwe et al., 2010) and the non-use or low rate of use of agricultural inputs (compost, improved varieties, etc.) (Gerstenmier and Choho, 2015).

In the Sahelian zone of Cameroon, particularly in the Lake Chad basin, precisely in Makary and Hilé Alifa, the soils used for sorghum cultivation are made up of silt and sand from arid zones. These soils, characterized by low organic matter and nitrogen contents, are very poor in nutrients and have low cation exchange capacities (Doh, 2018). Furthermore, these soils are depleted by their overexploitation in continuous cultivation linked to demographic pressure (Koutouan et al., 2017). Indeed, the use of new cultural practices, such as the use of organic residues in compost, integrating into the principles of sustainable development (Attrasi et al., 2005), becomes imperative. Thus, the use of compost in these sandy soils presents numerous advantages such as the reduction of greenhouse gas emissions through carbon sequestration, the reduction in the volume of waste (Houot et al., 2003), the limitation of the use of mineral fertilizers and soil restoration (Movahedi and Cook, 2010). These beneficial effects of composts depend on the quality of the materials used and the degree of maturity of the compost (Pigozzo et al., 2006).

The impacts of climate on agriculture vary from one region of the globe to another with particularly significant socio-economic consequences in developing countries in tropical latitudes (Benjamin S., et al.; 2021.). Given their geographic location, many Sahel countries in Africa are characterized by already warmer climates, marginal areas more exposed to climatic risks such as rainfall instability, poor soils and floodplains (UNESC, 2008). Added to this are inter- and intra-annual variabilities in rainfall (Hansen, 2002). Indeed, the climate in Africa is varied and variable (Ganyo et al., 2018). It is varied because it ranges from humid equatorial regimes, arid tropical and subtropical Mediterranean-type climates, and varying because all of these climates exhibit different degrees of temporal variability, particularly with regard to rainfall (Hulme and al., 2001). The average surface temperature of the earth is expected to reach or exceed 1.5°C of warming compared to pre-industrial times in the short term (by 2040) (IPCC, 2021). The Intergovernmental Panel on Climate Change predicts that due to global warming, the frequency and intensity of heavy rainfall will increase across most of tropical Africa (while parts of Africa North and South will become drier).

# I- MATERIALS AND METHOD
## 1) - Study sites

Two tests were conducted during the rainy seasons of 2021 and 2023 in two experimental sites of SAHEL NATURE CONSULTING located in Hilé Alifa at the coordinates 12° 42' 01" North Latitude (Site 1) and 14° 19' 01" East Longitude (Site 2). The two production sites are characterized by a Sudano-Sahelian climate with a monomodal rainfall regime which extends from June to October, with a peak in August. The cumulative rainfall during the experiments was 945 mm and 933 mm respectively, and the average temperatures during the experiments were 28.56°C and 29.53°C respectively. The following figure 1 shows the rainfall totals and decadal average temperatures.

## 2)- Plant material

Two (2) improved varieties of sorghum including a hybrid were used in this study (Table 2).

<table><caption>Table 1: Characteristics of the two sorghum varieties used</caption><thead><tr><th>Name</th><th>Origin</th><th>Race</th><th>Cycle</th><th>Sensibility to Photoperiod</th><th>Architecture</th><th>Use</th></tr></thead><tbody><tr><td>Soumalemba</td><td>Cameroun</td><td>Guinea</td><td>Long</td><td>Sensitive</td><td>Large size</td><td>Grain</td></tr><tr><td>Fadda</td><td>Mali</td><td>Guinea-hybrid</td><td>Medium</td><td>Sensible</td><td>Large size</td><td>Dual use</td></tr></tbody></table>

Cycle: Average: 105 to 135 days; Long: > 135 days; Architecture: Large size: > 3 m

## 3)- Experimental device and conduct of the test

The experimental design on the two sites was a split plot with six repetitions. The experiments on this level only differed in the randomization of the treatments. There were 20 treatments, resulting from combinations of four (4) varieties of sorghum with five (5) different fertilization methods in terms of dose and period of application, which are described below:

### 3-1)- Experimental device for germination

The trial was conducted using a randomized Fisher block design comprising three (3) blocks and six (6) treatments which are:

* T0 = no fertilizer;

* T1 = 50 kg/ha of NPK (15-15-15) (50%) at emergence + 100 kg/ha of compost 0 (33.33%) at tillering + 150 Kg/ha of compost 1 (16.67%) at the rise;

* T2 = 275 kg/ha of compost 1 (52.38%) at emergence + 125 kg/ha of compost 2 (23.81%) at tillering + 125 Kg/ha of compost 3 (23.81%) at emergence;

* T3 = 350 kg/ha of compost 1 (58.33%) + 125 kg/ha of compost 2 (20.83%) at bolting + 125 kg/ha of compost 3 (20.83%) at heading;

* T4 = 475 kg/ha of compost 1 (65.52%) + 125 kg/ha of compost 2 (17.24%) at bolting + 125 Kg/ha of compost 3 (17.24%) at heading;
$T_5 = 725 \text{ kg/ha of compost } 1 (74.36\%) + 125 \text{ kg/ha compost } 2 (12.82\%)$ at bolting + 125
$\text{Kg/ha of compost } 3 (12.82\%)$ at heading

The test was carried out on an area of 768 m2 (48 m x 16 m) (Figure 2). Each elementary plot, measuring 20 m2 (2m x 10m), included 2 ridges, each 9.5 m long and oriented widthwise (Figure 3).

<figure><img src="image_6.png" /><figcaption>Figure 1: Experimental setup</figcaption></figure>

Except for the T<sub>2</sub> modality which is the recommended practice in terms of dose and
period of application, the other modalities were determined by considering possible
scenarios of use and application of fertilizers resulting from climatic and/or rainfall
forecasts observed at the start of the campaign. Thus T<sub>4</sub> and T<sub>5</sub> type modalities could
be practiced in the hypothesis (h<sub>1</sub>) where the forecasts are uncertain but where
ultimately the season starts normally and seems to be good: in this case we do not add
anything at the start, then we make adjustments late contributions. For logistical
reasons, there was no method tested corresponding to the opposite hypothesis (h<sub>2</sub>)
where the season would become catastrophic after a good start, which would lead
farmers not to apply compost after having made an addition initial compost. However,
we can consider that this situation is generally framed by the T<sub>1</sub> and T<sub>3</sub> modalities.
Fertilization treatments were assigned to main plots. The two sorghum varieties were
assigned to elementary plots. Bunds were built around the main plots to prevent
compost runoff between plots.
<figure><img src="image_7.png" /><figcaption>Figure 2: Plan of an elementary plot</figcaption></figure>

Each elementary plot consisted of 2 lines of 9.5 m spaced 1 m apart; the inter-pocket space was 0.4 m. Five (5) to six (6) grains per pocket were sown and separated from two plants per pocket upon emergence, giving a density of 62,500 plants per hectare. The plants were transplanted onto the ridges, at a rate of 20 plants each, or 40 plants per elementary plot. The spacings were 0.5 m between plants and 1 m between rows, with 1 plant per hole, i.e. a density of 20,000 plants per hectare.

Compost was applied at different stages of development of each variety. The tests were conducted in rainy conditions on both sites. Before the installation of each test, a cross plowing of 30 cm depth was done. Cultivation operations (weeding, hilling and phytosanitary treatments) were carried out regularly and as necessary to maintain optimal cultivation conditions.

## 3-2)-Data collection of growth parameters

Vegetative biomass (leaves + stems) was collected before late fertilization (at tillering, B1) and after late fertilization (full flowering, B2). On each elementary plot, 4 pockets were chosen randomly on the 2 central lines to be sampled. The dry matter was evaluated after drying

# II- RESULTS
## II-1)- Study sites

The tests were carried out on similar soils, of the leached tropical ferruginous type, with a sandy texture and fragmentary structure. Composite soil samples were taken before each test to be analyzed at the soil and plant laboratory of the University Institute of Technology of the University of Ngaoundéré in Cameroon.

The average daily temperature was slightly higher at Site 1 (37.5±0.45°C) than at Site 2 (32.3±0.18°C). Site 2 received more water (822±211.08 mm) than Site 1 (805.33±158.35 mm) and the season started more slowly on site 1 (Figure 1). Due to their difference in cycle, the different varieties received varying amounts of rain: thus, the Fadda variety received on average 34% (43 and 25%) and Soumalemba 49.5% (74 and 25%) of the cumulative amount of rain before late fertilizer applications.

<figure><img src="image_8.png" /><figcaption>Graph 1: Rainfall and average temperature during the experiments on sites 1 and 2</figcaption></figure>

The analysis results are presented in Table 1.

<table><caption>Table 2: Physico-chemical characteristics of the soil before the experiment in the 0-40 cm horizon</caption><thead><tr><th>Sites</th><th>Horizon (cm)</th><th>Clay (%)</th><th>Limon (%)</th><th>Sand (%)</th><th>pH</th><th>Assimilable phosphorus (ppm)</th><th>Total nitrogen (%)</th><th>Organic matter (%)</th></tr></thead><tbody><tr><td rowspan="3">Site 1</td><td>0-10</td><td>1.46</td><td>3.43</td><td>95.12</td><td>6.38</td><td>8.686</td><td>0.052</td><td>1.14</td></tr><tr><td>0-20</td><td>5.19</td><td>3.72</td><td>91.06</td><td>6.67</td><td>4.685</td><td>0.038</td><td>1.03</td></tr><tr><td>20-40</td><td>3.43</td><td>2.82</td><td>92.69</td><td>6.76</td><td>5.264</td><td>0.065</td><td>1.04</td></tr><tr><td rowspan="3">Site 2</td><td>0-10</td><td>2.53</td><td>4.21</td><td>93.08</td><td>6.36</td><td>2.968</td><td>0.040</td><td>0.93</td></tr><tr><td>0-20</td><td>2.71</td><td>4.15</td><td>93.22</td><td>6.79</td><td>2.785</td><td>0.035</td><td>0.84</td></tr><tr><td>20-40</td><td>2.98</td><td>3.46</td><td>93.60</td><td>6.51</td><td>2.511</td><td>0.037</td><td>0.92</td></tr></tbody></table>
From these analyses, it appears that the soil is acidic on both sites (pH <7); the levels of nitrogen, assimilable phosphorus and organic matter are low overall but slightly higher in site 1. The previous crop on both sites was Vigna unguiculata (cowpea or white bean in flood recession cultivation).

## II-2- Advantage of compost based on *Eichhornia crassipes* and *Urtica dioica*

### II-2-1)- Mineralogical analysis of compost based on *Eichhornia crassipes* and *Urtica dioica*

Table 3 presents the chemical characteristics of the applied organic fertilizers. The analysis shows a richness in major nutrients, nitrogen (32.47 g/kg/DM), phosphorus (20.10 g/kg/DM) and potassium (25.20 g/kg/DM), of compost 1 (enriched with chicken dung and droppings, Eichhornia crassipes and Urtica dioica) compared to compost 2 (enriched with ox dung; water hyacinths and pollen hulls) respectively 14.60; 3.72 and 13.14 g/kg/MS.

<table><caption>Table 3: Chemical element and Nutrient content of composts</caption><thead><tr><th colspan="6">Chemical element content of composts</th></tr><tr><th>Parameters</th><th>pH eau</th><th>C (g/kg/MS)</th><th>N (g/kg/MS)</th><th>MO (%MS)</th><th>C/N</th></tr></thead><tbody><tr><td>Compost 0</td><td>6.7</td><td>318.14</td><td>27,29</td><td>29.08</td><td>15</td></tr><tr><td>Compost 1</td><td>8.15±0.35</td><td>354.05±16.24</td><td>33,09±0,88</td><td>34.62±1.27</td><td>40±5</td></tr><tr><td>Compost 2</td><td>7.9±0.25</td><td>357.07±7.18</td><td>33,05±0,68</td><td>39.87±2.82</td><td>41.25±5.25</td></tr><tr><td>Compost 3</td><td>7.97±0.82</td><td>376.17±7.16</td><td>36,60±0,67</td><td>48.85±1.16</td><td>35.50±2.25</td></tr><tr><td>Average</td><td>7.90±0.66</td><td>359.02±20.73</td><td>33,71±2,71</td><td>40.19±7.12</td><td>37.07±8.68</td></tr></tbody><thead><tr><th colspan="5">Nutrient content of composts</th></tr><tr><th>Parameters</th><th>P (g/kg/MS)</th><th>K (g/kg/MS)</th><th>Ca (g/kg/MS)</th><th>Mg (g/kg/MS)</th></tr></thead><tbody><tr><td>Compost 0</td><td>15.31</td><td>18.49</td><td>21.91</td><td>9.79</td></tr><tr><td>Compost 1</td><td>22.34±0.14</td><td>24.87±1.21</td><td>39.74±0.14</td><td>10.36±0.18</td></tr><tr><td>Compost 2</td><td>22.40±0.22</td><td>22.37±1.00</td><td>37.87±1.82</td><td>10.57±0.16</td></tr><tr><td>Compost 3</td><td>22.60±0.24</td><td>28.85±1.16</td><td>38.85±1.16</td><td>10.60±0.24</td></tr><tr><td>Average</td><td>21.89±1.99</td><td>24.83±3.56</td><td>37.52±4.96</td><td>10.45±0.31</td></tr></tbody></table>

The results in Table 5 showed, on the one hand, that the Mg2+ levels of compost 3 are higher (10.60±0.24 g/kg/DM) than those of compost 2 (10.57±0.16 g/kg/DM) and which are higher than those of compost 1 (10.36±0.18 g/kg/DM) while on the other hand, the Ca+ levels of compost 1 are higher (39.74±0.14 g/kg/DM) to those of compost 3 (38.85±1.16 g/kg/DM) and which are in turn higher than those of compost 2 (37.87±1.82 g/kg/DM). Overall, the average levels of Mg2+ (10.45±0.31 g/kg/DM) and Ca+
(37.52±4.96 g/kg/DM) of the two composts remain below international standards (Zdanevitch. I., 2012). In other words, composts can be applied to the soil without major risks.

The overall average of the C/N ratio of compost based on Eichhornia crassipes allows us to see that carbon is on average (37.85±6.80) times more important than nitrogen. Which corroborates those found by Yveline M. (2015) which indicates that the C/N ratio is ideally between 20/1 and 30/1 and a maximum of 50/1.

<figure><img src="image_9.png" /><figcaption>Photo 1: Dried Compost</figcaption></figure>

The minimum average temperature is 27.31±1.03°C while the maximum average temperature is 62.54±1.45°C. The average raw humidity of the compost before drying is 67.31±1.03% while the average dry humidity of the compost after drying is 55±1%.

<table><caption>Table 4: Physico-chemical analyzes of compost based on *Eichhornia crassipes*</caption><thead><tr><th rowspan="2">Compostièr e</th><th colspan="2">Moisture content</th><th colspan="2">Average Temperature</th><th rowspan="2">pH</th><th rowspan="2">Ratio C/N</th></tr><tr><th>Raw Moisture content (%)</th><th>Dry Moisture content (%)</th><th>Minimum Temperature (C°)</th><th>Maximum temperature (C°)</th></tr></thead><tbody><tr><td>Compost 0</td><td>67</td><td>56</td><td>27</td><td>39</td><td>6.7</td><td>15</td></tr><tr><td>Compost 1</td><td>68.00±0.50</td><td>54.25±0.75</td><td>28±0,5</td><td>62.75±0.87</td><td>8.15±0.35</td><td>40±5</td></tr><tr><td>Compost 2</td><td>66.75±0.87</td><td>55.75±0.75</td><td>26.75±0.87</td><td>63.25±1.75</td><td>7.90±0.25</td><td>41.25±5.25</td></tr><tr><td>Compost 3</td><td>67.25±0.75</td><td>54.75±0.37</td><td>27.25±0.75</td><td>61.75±0.75</td><td>7.97±0.82</td><td>35.50±2.25</td></tr><tr><td>Average</td><td>67.31±1.03</td><td>55±1</td><td>27.31±1.03</td><td>62.54±1.45</td><td>7.91±0.66</td><td>37.85±6.80</td></tr></tbody></table>
The pHs evolved following three phases. The first phase which lasts up to 12 days has an average pH of 6.14±0.5 while the second phase lasts approximately 08 days with an average pH of 8.29±1.54. The third phase lasts approximately 05 days with an average pH of 7.64±0.

## II-2-2)- Effect of environment, fertilization and variety on yields and IR and RF indices

They were chosen because of their contrasting characteristics in terms of phenology (short and medium cycle), architecture (small and medium size), response to fertilization (hybrid reacts better) and use (grain and dual use: fodder and grain). The above results made it possible to evaluate the responses of two varieties of sorghum to contrasting compost supply plans based on *Eichhornia crassipes* and *Urtica dioica*.

<figure><img src="image_10.png" /><figcaption>Graph 2: Effect of the environment on the production of sorghum based on *Eichhornia crassipes* compost</figcaption></figure>

Thus, considering the development parameter which is biomass, the late addition of compost allowed the sorghum plants initially affected by the non-addition of fertilizer at the start, to recover normal development
with quantities of dry matter, similar between inputs during normal periods and periods delayed due to rain delays (Table 3).

The "environment" factor had a significant effect (P<0.05) on B1, RB and RF while fertilization showed a significant effect on B1, RG and RB. Variety had a significant effect on all variables except B1 and RF (Table 6).

<table><caption>**Table 5: Summary of the analysis of variance on biomass before (B₁) and after (B₂) late fertilization, grain yield (RG), biomass (RB) and harvest index (IR) and response index to fertilization (RF)**</caption><thead><tr><th rowspan="2">Sources</th><th colspan="2">Growth parameters</th><th colspan="3">Performance parameters</th></tr><tr><th>B₁</th><th>B₂</th><th>RG</th><th>RB</th><th>IR</th><th>RF</th></tr></thead><tbody><tr><td>Environnement (E)</td><td>&lt; 0.0001</td><td>0.0697</td><td>0.8082</td><td>0.0483</td><td>0.3266</td><td>0.0131</td></tr><tr><td>Fertilization (F)</td><td>&lt; 0.0001</td><td>0.1388</td><td>0.0005</td><td>0.0004</td><td>0.7989</td><td>0.7412</td></tr><tr><td>Variety T (V)</td><td>0.0547</td><td>&lt; 0.0001</td><td>&lt; 0.0001</td><td>&lt; 0.0001</td><td>&lt; 0.0001</td><td>0.3002</td></tr><tr><td>E∩F</td><td>0.3477</td><td>0.3143</td><td>0.05</td><td>0.0073</td><td>0.9320</td><td>0.4119</td></tr><tr><td>E∩V</td><td>0.6997</td><td>0.0047</td><td>0.0005</td><td>0.0417</td><td>0.2192</td><td>0.1218</td></tr><tr><td>F∩V</td><td>0.4459</td><td>0.3686</td><td>0.0176</td><td>0.2665</td><td>0.6184</td><td>0.8853</td></tr><tr><td>E∩F∩V</td><td>0.9854</td><td>0.5797</td><td>0.8647</td><td>0.4612</td><td>0.5022</td><td>0.8139</td></tr></tbody></table>

B1: Biomass before late fertilization, B2: Biomass after late fertilization, RG: Grain yield, RB: Biomass yield, IR: Harvest index, RF: Fertilization response index

Furthermore, the interaction of fertilization on the environment (E∩F) showed a significant effect on the response index to fertilization (0.9320) and the harvest index (0.4119).

The effect of the interaction of the environment on Variety (E∩V) was significant on B1 (0.6997), B2 (0.0047), RG (0.0005) and RB (0.0417).

The interaction of fertilization on Variety (F∩V) was only significant on RG (0.0176) and IR (0.6184).

The triple interaction of fertilization on environment and on Variety (E∩F∩V) showed a significant effect on RG (0.8647) (Table 5).
<table><caption>Table 6: Effect of environment, fertilization and variety on biomass, grain yield, harvest index and fertilization response index</caption><thead><tr><th rowspan="2">Sources</th><th colspan="2">Growth parameters</th><th colspan="2">Performance parameters</th><th rowspan="2">IR</th><th rowspan="2">RF</th></tr><tr><th>B<sub>1</sub> (kg/ha)</th><th>B<sub>2</sub> (kg/ha)</th><th>RG (kg/ha)</th><th>RB (kg/ha)</th></tr></thead><tbody><tr><td>Environnement (E)</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Site 1</td><td>91<sup>c</sup></td><td>5613</td><td>839</td><td>4905<sup>a</sup></td><td>0.17</td><td>0.81<sup>a</sup></td></tr><tr><td>Site 2</td><td>12<sup>d</sup></td><td>6513</td><td>894</td><td>4192<sup>b</sup></td><td>0.21</td><td>1.93<sup>b</sup></td></tr><tr><td>Fertilization (F)</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>T1</td><td>56<sup>a</sup></td><td>5043</td><td>710<sup>c</sup></td><td>3425<sup>b</sup></td><td>0.20</td><td>1.17<sup>h</sup></td></tr><tr><td>T2</td><td>102<sup>c</sup></td><td>6562</td><td>1229<sup>b</sup></td><td>5309<sup>a</sup></td><td>0.20</td><td>1.20</td></tr><tr><td>T3</td><td>109<sup>d</sup></td><td>6509</td><td>971<sup>adf</sup></td><td>5012<sup>a</sup></td><td>0.17</td><td>1.24</td></tr><tr><td>T4</td><td>62<sup>a</sup></td><td>5928</td><td>992<sup>ca</sup></td><td>5461<sup>a</sup></td><td>0.19</td><td>1.06</td></tr><tr><td>T5</td><td>58<sup>b</sup></td><td>5270</td><td>746<sup>cd</sup></td><td>3722<sup>b</sup></td><td>0.22</td><td>1.87</td></tr><tr><td>Varieties (V)</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Fadda</td><td>65</td><td>7937<sup>b</sup></td><td>1195<sup>a</sup></td><td>6096<sup>a</sup></td><td>0.20<sup>a</sup></td><td>0.67</td></tr><tr><td>Soumalembe</td><td>91</td><td>5455<sup>c</sup></td><td>809<sup>a</sup></td><td>7294<sup>b</sup></td><td>0.20<sup>a</sup></td><td>1.11</td></tr><tr><td>Interactions</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>E∩F</td><td>ns</td><td>ns</td><td>ns</td><td>**</td><td>ns</td><td>**</td></tr><tr><td>E∩V</td><td>*</td><td>**</td><td>*</td><td>*</td><td>ns</td><td>ns</td></tr><tr><td>F∩V</td><td>ns</td><td>ns</td><td>*</td><td>ns</td><td>*</td><td>ns</td></tr><tr><td>E∩F∩V</td><td>ns</td><td>ns</td><td>**</td><td>ns</td><td>ns</td><td>ns</td></tr></tbody></table>

Values in a column followed by the same letter are not significantly different at the 5% threshold:

B1: Biomass before late fertilization;

B2: Biomass after late fertilization;

RG: Grain yield;

RB: Biomass yield;

IR: Harvest index;

RF: Response to fertilization;

T0 = no fertilizer;

T1 = 50 kg/ha of NPK (15-15-15) (50%) at emergence + 100 kg/ha of compost 0 (33.33%) at tillering + 150 Kg/ha of compost 1 (16.67%) at the rise;

T2 = 275 kg/ha of compost 1 (52.38%) at emergence + 125 kg/ha compost 2 (23.81%) at tillering + 125 Kg/ha of compost 3 (23.81%) at emergence;

T3 = 350 kg/ha of compost 1 (58.33%) + 125 kg/ha of compost 2 (20.83%) at bolting + 125 kg/ha of compost 3 (20.83%) at heading;

T4 = 475 kg/ha of compost 1 (65.52%) + 125 kg/ha compost 2 (17.24%) at bolting + 125 Kg/ha of compost 3 (17.24%) at heading;

T5 = 725 kg/ha of compost 1 (74.36%) + 125 kg/ha compost 2 (12.82%) at bolting + 125 Kg/ha of compost 3 (12.82%) at heading;

ns: not significant, * significant at P < 0.05, ** significant at P < 0.01.

## II-2-3)- Effect of the Environment on Fertilization Indices

Yields following the E∩F interaction (combining varieties) varied from 491 kg/ha to 1299 kg/ha on site 1 and from 469 to 1309 kg/ha on site 2.
The yields from late T<sub>5</sub> applications were better on site 2 than on site 1. Comparing the recommended treatment in the context of this work (T<sub>2</sub>, dose and period of application) to the treatment to be introduced late (T<sub>4</sub>, intake late of the same dose), it appears that the Soumalemba variety which reacted less well to late fertilization on the two sites because, the addition of the 100% dose of compost gave performances above the average yield (1166 .67±1.24 kg/ha) of sorghum in Logone and Chari/Far North Cameroon from 2017 to 2023 when the cumulative rainfall before late fertilization (montage stage) is less than 80% of the cumulative water during the cultivation period and/or performances higher than the yield of T<sub>2</sub> when the latter is lower than the national average of 1500 kg/ha.

<figure><img src="image_11.png" /><figcaption>Graph 3: Grain yield in response to environment-fertilization interaction</figcaption></figure>
T0 = no fertilizer;

T1 = 50 kg/ha of NPK (15-15-15) (50%) at emergence + 100 kg/ha of compost 0 (33.33%) at tillering + 150 Kg/ha of compost 1 (16.67%) at the rise;

T2 = 275 kg/ha of compost 1 (52.38%) at emergence + 125 kg/ha compost 2 (23.81%) at tillering + 125 Kg/ha compost 3 (23.81%) at emergence;

T3 = 350 kg/ha of compost 1 (58.33%) + 125 kg/ha of compost 2 (20.83%) at bolting + 125 kg/ha of compost 3 (20.83%) at heading;

T4 = 475 kg/ha of compost 1 (65.52%) + 125 kg/ha compost 2 (17.24%) at bolting + 125 Kg/ha of compost 3 (17.24%) at heading;

T5 = 725 kg/ha of compost 1 (74.36%) + 125 kg/ha compost 2 (12.82%) at bolting + 125 Kg/ha of compost 3 (12.82%) at heading;

For a minimum total of 300kg/ha of compost, 15 g/plant of compost applied corresponds to approximately 0.32 g of nitrogen (N); 0.09 g of phosphorus (P) and 0.17 g of potassium (K) while for a maximum of 725 kg/ha of compost, 36.25g/plant of composts applied corresponds to approximately 0.77 g of nitrogen (NOT); 0.22 g of phosphorus (P) and 0.42 g of potassium (K) which contrasts with the data obtained by Aristil (2019) which uses compost (2.53 t/ha) for the production of sorghum.

<table><caption>Table 7: Doses of inputs provided per experimental unit</caption><thead><tr><th rowspan="2">Treatments</th><th rowspan="2">Designation</th><th rowspan="2">Amendment period</th><th colspan="2">Intake</th></tr><tr><th>Dose (g/m²)</th><th>Dose (g/plant)</th></tr></thead><tbody><tr><td>T₀ Compost 0 (100%) Absolute witness</td><td>Organic</td><td>During season</td><td>-</td><td>-</td></tr><tr><td rowspan="3">T₁ NPK (15-15-15) (50%) + Compost 0 (33.33%) + Compost 1 (16.67%)</td><td>NPK</td><td rowspan="3">During season</td><td>19</td><td>3.33</td></tr><tr><td>Urea</td><td>09</td><td>1.91</td></tr><tr><td>Potassium sulfate</td><td>18</td><td>3.33</td></tr><tr><td rowspan="2">T₂ Compost 1 (52.38%) + Compost 2 (23.81%) + Compost 3 (23.81%)</td><td rowspan="2">Organic</td><td>Start of season</td><td>1600</td><td>10</td></tr><tr><td>Late intake</td><td>7500</td><td>29.63</td></tr><tr><td rowspan="2">T₃ Compost 1 (58.33%) + Compost 2 (20.83%) + Compost 3 (20.83%)</td><td rowspan="2">Organic</td><td>Start of season</td><td>1900</td><td>15</td></tr><tr><td>Late intake</td><td>7500</td><td>36.25</td></tr><tr><td rowspan="2">T₄ Compost 1 (65.52%) + Compost 2 (17.24%) + Compost 3 (17.24%)</td><td rowspan="2">Organic</td><td>Start of season</td><td>2200</td><td>19</td></tr><tr><td>Late intake</td><td>7500</td><td>41.59</td></tr><tr><td rowspan="2">T₅ Compost 1 (74.36%) + Compost 2 (12.82%) + Compost 3 (12.82%)</td><td rowspan="2">Organic</td><td>Start of season</td><td>2300</td><td>21</td></tr><tr><td>Late intake</td><td>7500</td><td>53.14</td></tr></tbody></table>

Table 7 presents the average values of biomass (before and after late fertilization and at harvest), grain yield and harvest and response to fertilization indices by environment, fertilization and variety. According to Ganyo et al., 2018, the conventional and recommended practical need in Senegal for sorghum was estimated
at 150 kg/ha of NPK (15-15-15) at emergence + 50 kg/ha of urea (46%) at tillering + 50 kg/ha of urea at bolting. From these doses and the results of the chemical analyses, the quantities of each compost and manure to be applied to obtain the envisaged treatments were defined (Table 7).

<figure><img src="image_12.png" /><figcaption>Graph 4: Effect of fertilization on the production of sorghum based on *Eichhornia crassipes* compost</figcaption></figure>

## II-2-4) - Effect of the Environment on Biomass Yield

B1 was significantly greater on site 1 than on site 2. The plants before the late application of fertilizer were stressed with significantly less biomass production on the late treatments (T4 and T5) than on the treatments normal (T2 and T3). Indeed, the biomass under T4 was lower than that under T2 and that under T5 also lower than T3. After late fertilization, no significant effect of fertilization on biomass was observed.
<figure><img src="image_13.png" /><figcaption>Graph 5: Effect of compost based on *Eichhornia crassipes*, fertilization on the production of sorghum varieties</figcaption></figure>

We deduce from this that the plants under T<sub>4</sub> and T<sub>5</sub> have recovered their normal development with biomasses statistically equivalent to those under T<sub>2</sub> and T<sub>3</sub> when compared two by two, with a significant threshold P ≤ 0.2398.
<figure><img src="image_14.png" /><figcaption>Photo 2: a) Soumalemba biomass; b) Biomass of Fadda</figcaption></figure>

Furthermore, the biomass after late fertilization varied depending on the varieties: Fadda (7584 kg/ha) gave significantly more biomass than Soumalemba (5382 kg/ha). The vegetative biomass at harvest was greater on site 1 than on site 2. The Soumalemba variety gave a significantly higher straw yield than that of the Fadda variety. Graph 6-a shows the values of straw yield depending on the fertilization methods on each site. It appears that on site 1, the 100% compost additions ($T_2$ and $T_4$) and the addition ($T_3$) during the normal time induced biomass levels higher than those of the other two treatments ($T_1$ and $T_5$). However, on site 2, the forage yields of all the treatments with compost addition and the control without additions are statistically identical to each other. Late additions of 100% compost gave higher straw yields than without compost additions (Graph 5).

This renewed growth shows that even with a difficult or catastrophic start to the season, a late addition of compost can help boost the growth of the plants. Plants can therefore use and benefit from these compost contributions. Plant growth could be attributed on the one hand to the supply of nitrogen nutrients which would have affected plant growth by accelerating cell division and cell enlargement (Stals and Inzé
2001; Ganyo et al., 2018). On the other hand, soil humidity induced by water received after late fertilization can affect the expression of macroelements provided to plants and vice versa (Ganyo et al., 2018). This would have stimulated development by adjusting the supply of nitrogen elements to the ground level.

<figure><img src="image_15.png" /><figcaption>Graph 6: a) Biomass yields before and after fertilization; b) Grain yield and biomass yield</figcaption></figure>

The effect of the E∩F interaction is not significant on biomass before and after late fertilization (Ganyo et al., 2018). However, this interaction is significant on straw at harvest. Nitrogen fertilization significantly affects aboveground biomass from a humidity threshold (Mon et al., 2016). Which could explain the observed effects of this interaction at the different sampling dates.

II-2-5) - Effect of the Environment on Grain Yield
On site 1, it was the 100% compost dose, applied during the normal period, which induced the highest yield (T<sub>2</sub>, 1299 kg/ha for the Fabba variety and 1281 kg/ha for the Soumalemba variety) followed by 16.67% chemical fertilizer and 83.33% compost of the total amendment dose (T<sub>1</sub>, 1291 kg/ha for the Fabba variety and 1232 kg/ha for the Soumalemba variety) and the 100% dose compost applied late (T<sub>3</sub>, 1271 kg/ha for the Fabba variety and 998 kg/ha for the Soumalemba variety) and (T<sub>4</sub>, 1192 kg/ha for the Fabba variety and 992 kg/ha for the Soumalemba variety). The late application of 100% of the compost (T<sub>5</sub>, 746 kg/ha for the Fabba variety and 865 kg/ha for the Soumalemba variety) gave a yield while the control 0% of the compost (T<sub>0</sub>, 491 kg/ha for the Fabba variety and 496 kg/ha for the Soumalemba variety).

On site 2, applications of 100% of the compost dose, during normal time (T<sub>2</sub>, 1309 kg/ha for the Fabba variety and 1287 kg/ha for the Soumalemba variety) and late time (T<sub>4</sub>, 1161 kg/ha for the Fabba variety and 994 kg/ha for the Soumalemba variety) induced the highest yields, respectively 1298±11 kg/ha (T<sub>2</sub>) and 1077.5±83.5 kg/ha (T<sub>4</sub>), followed by the others 100% compost treatments during the normal time of the production cycle (T<sub>3</sub>, 1212 kg/ha for the Fabba variety and 976 kg/ha for the Soumalemba variety) and late (T<sub>5</sub>, 1022 kg/ha for the Fabba variety and 803 kg/ha for the Soumalemba variety) and the control (T<sub>0</sub>, 469 kg/ha for the Fabba variety and 484 kg/ha for the Soumalemba variety) (Graph 7).

<figure><img src="image_16.png" /><figcaption>Graph 7: Grain yield of the 2 varieties of sorghum depending on fertilization methods</figcaption></figure>
Grain yield varied depending on the interactive effect of the environment (water received) and fertilization. Late additions of compost varied depending on the sites and the increase in grain yield due to the late application of compost fluctuated over the years and following the meteorological parameters of the Sahelian localities, as confirmed by our results. For Woolfolk et al. (2002), Blandino et al. (2015) and Ganyo et al. (2018), the increase in grain yield due to late application is not constant over years and localities.

The leaching of nutrients due to the quantity and high intensities of rain received at both sites could explain the poorer yield performance. Indeed, on this site we had recorded heavy rains ranging from 71 to more than 104 mm per day, which would be bad for the plants on sandy soil with strong leaching. Furthermore, the good performances obtained from late inputs have been reported on sorghum in semi-arid zones of Iran (Amiri et al., 2014), on rice in the plains of the Philippines (Perez et al., 1996) and on winter wheat in pots (Xue et al., 2016). Indeed, Amiri et al. (2014) report higher sorghum yields with the addition of 25% N at sowing, 50% N at bolting and 25% N at flowering. However, the results on the good performance of "late" treatments contrast with those obtained on rice by Fageria and Baligar (1999). These authors obtained low yield levels with two fertilization treatments including late additions at heading and flowering defined as

(i) a third of N supplied at sowing, a third of N at panicle initiation and a third of N at flowering and

(ii) a supply of zero N at sowing, one third of N at panicle initiation, one third of N at heading and one third of N at flowering.

Furthermore, the response of the two varieties to fertilization was variable; Fadda having responded better to fertilization in general while Soumalemba responded better to late fertilization ($T_2$). This variation in response to fertilization through different yields can be attributed to a combined effect of varietal character (genetic characteristic for example) and environment (climate, soil). These results are similar to those of Blandino et al. (2015) who reported variable and contrasting yields of two wheat varieties with late nitrogen fertilization and those of Kante et al. (2017) who report variable yields of sorghum (hybrids and local sorghum accessions) in Mali.

## II-2-6)-Effect of fertilization on sorghum variety

On sites 1 and 2, the staggered addition of 100% compost during the season gave satisfactory yield levels. Graph 4 illustrates the grain yield of the 2 varieties of sorghum depending on the fertilization methods. At Fadda and Soumalemba, the application of the 100% dose during the normal cycle ($T_2$) gave the best performance in average grain yield (1304 kg/ha) and average biomass yield (5309 kg/ha) followed by $T_3$ and $T_4$.
Fadda was the variety that responded best to compost fertilization. The results of the interactions E∩F and F∩V (Graph 8, 2 and 4) also showed that the late additions of the 100% compost dose prove beneficial compared to the control without the addition of compost which is the common peasant practice, observed today in the locality due to rainfall uncertainties even if surprisingly certain witness results remain high At Soumalemba, it was the late additions of compost (T₄ and T₅) which induced maximum yields (1118 and 942 kg/ha), but no significant difference was observed between them. Additions of 100% and 50% of the recommended dose of compost during the normal time of the sorghum production cycle gave poor performance for this variety. T₄ and T₅ of Soumalemba present an increase of 74% and 71% respectively compared to the recommendation (T₂).

<figure><img src="image_17.png" /><figcaption>Graph 8: Comparison of the quantities of rain (in percentage) received before late applications of compost according to grain yield</figcaption></figure>

## II-2-7)- Effect of the Environment on the Harvest Index and the Fertilization Index

Only the variety factor had a significant effect on the harvest index. Thus, the Fadda variety gave the maximum grain-total aerial biomass ratio which is higher than that of
Soumalemba while the response index to fertilization (RF), varied only depending on the environment with the best response on site 2.

<figure><img src="image_18.png" /><figcaption>Graph 9: Harvest Index and Fertilization Response Index</figcaption></figure>

Although the difference was not significant for fertilization, the defined strategies nevertheless show numerically higher indices than that of T₂.

The harvest index only varied depending on the varieties. Which demonstrates that it is linked to the genetic character of the plant material used. The non-significance of fertilization on the RF reflects the potential of the late and/or reduced fertilization strategy (Ganyo et al., 2018). In particular, nitrogen additions between after tillering and heading increase wheat yield (Finney et al., 1957). The E∩F∩V interactions were not significant for all the variables studied (Table 6). Which means that the sorghum varieties behaved similarly with respect to fertilization in both environments. The strategy of adding compost, in particular 100% of the recommended dose depending on weather forecasts or the course of the season, made it possible to obtain yields above the national average and the current peasant practice of sorghum production (no addition of compost). Late fertilization turns out to be one of the strategies to maximize or optimize sorghum yields in the Sahelian zones of the Lake Chad basin Cameroon.

CONCLUSION

Compost based on *Eichhornia crassipes* linked to *Urtica Dioica* has a very short maturity time of 16±01 days. The late addition of compost based on *Eichhornia crassipes* linked to *Urtica Dioica* during treatment (T₂) with the mixture of Compost 1 (52.38%),
Compost 2 (23.81%) and Compost 3 (23.81%) had a significant effect on plant growth. With this treatment, plants stressed at the start of the season due to delayed rains and high temperatures regained normal development in the same way as plants having received compost early in the season. The period of compost addition combined with water distribution had an effect on yields. The late fertilization strategy was beneficial with the addition of large quantities of compost which gave yields above peasant practice (no compost addition) and higher when the quantity of water received before late fertilization is less than 50% of the totals received throughout the cultivation period and a low potential of the site for T₂. The response to particularly late fertilization of sorghum varieties was variable. Adjusting fertilization to the rainfall regime could help optimize sorghum productivity.

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Zdanevitch. I., 2012. Comparative study of compost and digestate quality issued from the fermentable portion of domestic wastes, separately collected or mixed. Final report. Study report. Ineris Paris (France), 124 p
## EXERCISES AND CORRECTIONS ON THE OPTIMIZATION OF THE PRODUCTION OF TWO VARIETIES OF SORGUM (FADDA AND SOUMALEMBA) AMENDED WITH COMPOST BASED ON EICHHORNIA CRASSIPES LINKED TO URTICA DIOICA IN SAHEL AREAS NEAR LAKE CHAD

Here is a series of exercises accompanied by their corrections on the optimization of the production of two varieties of sorghum (Fadda and Soumalemba) amended with compost based on *Eichhornia crassipes* linked to *Urtica dioica* (nettle) in Sahelian areas close to the lake Chad.

---

### Exercise 1: Understanding the Raw Materials Used for Compost

**Objective:** Identify the properties of *Eichhornia crassipes* and *Urtica dioica* that make them effective components for compost and understand their potential impact on sorghum production.

**Instructions:**

1. Describe the beneficial properties of *Eichhornia crassipes* and *Urtica dioica* which justify their use in the preparation of compost.

2. Explain how this compost can influence the growth and productivity of sorghum varieties Fadda and Soumalemba.

**Correction:**

**1. Properties of raw materials:**

* *Eichhornia crassipes*: This aquatic plant is rich in nutrients such as nitrogen, phosphorus, and potassium. It also contains organic matter which, once decomposed, enriches the soil and improves its structure.

* *Urtica dioica*: Nettle is a plant rich in minerals (nitrogen, iron, magnesium) and trace elements. It has bio-stimulating properties, promoting plant growth and increasing their resistance to disease.

**2. Impact of compost on sorghum:**

- Compost made from *Eichhornia crassipes* and *Urtica dioica* improves soil fertility by increasing the availability of essential nutrients for sorghum.

- It improves water retention in sandy soils in Sahelian areas, which is crucial for crop growth in periods of drought.
- Compost can also promote root development, thereby increasing the capacity of plants to absorb water and nutrients, leading to better productivity of Fadda and Soumalemba varieties.

---

**Exercise 2: Experimenting with Compost Application**

**Objective:** Evaluate the effect of different doses of compost on the growth of the two varieties of sorghum.

**Instructions:**

**1. You have four experimental plots:**

- Plot A: 0 ton/ha (control, without compost)

- Plot B: 5 tons/ha

- Plot C: 10 tons/ha

- Plot D: 15 tons/ha

- Measure the average heights of sorghum plants in each plot after 8 weeks of growth.

**2. Analyze the results and determine the optimal dose of compost to maximize the growth of the Fadda and Soumalemba varieties.**

**Correction:**

**1. Hypothetical results (average plant height after 8 weeks):**

- Plot A (0 t/ha): 50 cm

- Plot B (5 t/ha): 70 cm

- Plot C (10 t/ha): 90 cm

- Plot D (15 t/ha): 88 cm

**2. Analysis of results:**

- The growth of sorghum plants increases with the application of compost, reaching a maximum with 10 tons/ha.

- From 15 tons/ha, growth seems to stagnate, suggesting that a higher dose does not provide additional benefit and could even harm growth in the event of saturation or excess of nutrients.

**Conclusion:** The optimal dose of compost to maximize the growth of Fadda and Soumalemba varieties is 10 tons/ha.
## Exercise 3: Productivity Impact Study

**Objective:** Quantify the impact of compost on the grain yield of the two varieties of sorghum.

**Instructions:**

1. for each plot (A, B, C, D), measure the grain yield per hectare (kg/ha) after harvest.

2. Compare the yields obtained with and without compost to determine the improvement provided by the amendment.

**Correction:**

**1. Hypothetical results (grain yield):**

- Plot A (0 t/ha): 800 kg/ha

- Plot B (5 t/ha): 1200 kg/ha

- Plot C (10 t/ha): 1600 kg/ha

- Plot D (15 t/ha): 1500 kg/ha

**2. Analysis of returns:**

- The application of compost significantly increases grain yield, with a maximum observed at 10 tons/ha.

- Increasing the dose beyond 10 tons/ha (Plot D) does not seem to further improve yield, which could indicate nutrient saturation or another factor limiting production.

**Conclusion:** Compost at 10 tons/ha optimizes the grain yield of both varieties of sorghum, with a substantial gain compared to cultivation without compost.

---

## Exercise 4: Environmental and Economic Impact

**Objective:** To evaluate the environmental and economic implications of the use of compost based on *Eichhornia crassipes* and *Urtica dioica* in sorghum crops.

**Instructions:**

1. Identify the environmental benefits of using this compost, particularly in the Sahelian areas near Lake Chad.
2. Analyze the costs associated with the production and application of this compost, and discuss its economic viability for local farmers.

**Correction:**

**1. Environmental benefits:**

- **Fight against invasion:** The use of *Eichhornia crassipes* for compost reduces the proliferation of this invasive plant in aquatic areas, contributing to the management of the ecosystems of Lake Chad.

- **Improvement of soil fertility:** The addition of compost improves the structure and fertility of degraded soils in Sahelian areas, increasing their capacity to retain water and nutrients.

- **Reduction of organic waste:** The valorization of *Urtica dioica* and other local biomasses into compost makes it possible to reduce organic waste, while providing a sustainable solution to the fertilization of crops.

**2. Cost analysis:**

- **Production costs:** The collection, transport and transformation of Eichhornia crassipes and Urtica dioica into compost can represent significant costs, especially if the resources are far from the production sites.

- **Application costs:** The application of compost requires labor and material resources, but it can be justified by the increase in yields.

- **Economic viability:** To be economically viable, the benefits from increased yields and soil quality must offset the costs of producing and applying compost.

**Recommendations:**

- **Support for farmers:** Subsidy or technical aid programs could be put in place to encourage the use of compost, thus reducing costs for farmers.

- **Resource optimization:** Developing local strategies for small-scale compost production could reduce transport costs and increase economic viability.

---

These exercises allow us to explore the multiple dimensions of optimizing sorghum production in a Sahelian context, with emphasis on the impact of the use of innovative compost based on *Eichhornia crassipes* and *Urtica dioica*.
# CHAPITRE 2. EFFECT OF MIXED BIOCHAR-COMPOST BASED ON DEAD BIOMASSES OF *PROSOPIS JULIFLORA* AND *EICHHORNIA CRASSIPES* ON THE PRODUCTIVITY AND BIODIVERSITY OF ARID SANDY SOILS IN THE SAHELIAN ZONE

Alexis Dzokom¹, Roger Djouldé Darman²

¹Department of Environmental Sciences, National Advanced School of Engineering, University of Maroua, Cameroon

²Department of Agriculture Animal Husbandry and By-Products, National Advanced School of Engineering, University of Maroua, Cameroon

## ABSTRACT

The Biochar-Compost mixture based on the dead biomass of *Prosopis juliflora* and *Eichhornia crassipes* can be used as an input in agricultural production. The objective of this study is to determine the capacity of the Biochar-Compost mixture based on the dead biomass of *Prosopis juliflora* and *Eichhornia crassipes* on the restoration and productivity of degraded arid soils in the Cameroonian Sahel. A randomized complete block design (RCBD) was used to test the effect of the Biochar-Compost mixture on a sandy-clay soil (95%-05%) with and without Compost_Biochar based on *Prosopis juliflora_Eichhornia crassipes*. The Berkley rapid composting method was used to produce the compost while the carbonization method developed by SAHEL NATURE CONSULTING FOR COMMUNITIES was used to produce the biochar. In this experiment, the Biochar-Compost mixture based on the dead biomass of *Prosopis juliflora* and *Eichhornia crassipes* was applied to the cultures of Zea mays and Solanum lycopersicum L. above at 5, 10, 15, and 20 t/ha with and without Compost_Biochar based on *Prosopis juliflora_Eichhornia crassipes*. The results showed a significant increase in seed germination percentage as we applied more of 15 t/ha of Compost_Biochar 2 (47.36-52.63)% based on *Prosopis juliflora_Eichhornia crassipes* to agricultural land abandoned due to its degradation due to aridity and silting. The study also showed an increase in crop biomass using Biochar (100%) based on *Prosopis juliflora_Eichhornia crassipes* alone and/or in combination with Compost based on *Prosopis juliflora_Eichhornia crassipes* on sandy clay soil T03 (95%-05%). The application of this Compost_Biochar based on *Prosopis juliflora_Eichhornia crassipes* on sandy clay soil T03 (95%-05%) also increases the growth of shoots and roots of crops, then improves crop yield by improving the physicochemical properties and biological soils, which is probably the reason why Compost_Biochar based on *Prosopis juliflora_Eichhornia crassipes* on sandy clay soil T03 (95%-05%) could contribute to plant productivity. In view of the percentage of leaching obtained due to runoff water, we conclude that, even
content in biochars is between 40 and 50% for biochars coming from agricultural residues compared to 70 to 90% for biochars made from wood, hulls or bark. Chemically, biochar is not pure carbon, but rather a mixture of carbon (C), hydrogen (H), oxygen (O), nitrogen (N), sulfur (S) and ashes in different proportions (Wang et al., 2020).).

Biochar improves soils and their productivity. It is a carbon-rich porous material with multifaceted physico-biochemical properties such as retention capacity and cation exchange capacity (Arroyo and Ryan, 2018). By converting agricultural waste into a powerful soil amendment that retains carbon and makes soils more fertile, we can increase food security, discourage deforestation and preserve cropland diversity (Kazmi et al., 2010). The burning and natural decomposition of trees and agricultural materials contributes to a large amount of CO2 released into the atmosphere (Tomczyk, 2020). Biochar can store this carbon in the soil, potentially leading to a significant reduction in atmospheric levels of greenhouse gases; at the same time, its presence in the land can improve water quality, increase soil fertility, increase agricultural productivity and reduce pressure on old-growth forests (Lompo et al., 2021; Kazmi et al., 2010). Biochar as a soil amendment faces the challenge that it must be beneficial to soil health because it cannot in any way be separated from soils once added (Bodjona et al., 2023; Lone et al., 2015); soils can be considered as complex communities of organisms) which continually change in response to soil characteristics, climatic and management factors and especially in response to the addition of organic matter (Chen et al., 2013; Thies and Rillig, 2009). However, the application of biochar to soils is subject to have different change effects on soil biota compared to the addition of fresh organic matter, which can affect the abundance, activity and diversity of soil biotic communities (Lehmann et al., 2011). The objective of this study is to determine the capacity of the Biochar-Compost mixture based on the dead biomass of *Prosopis juliflora* and *Eichhornia crassipes* on the restoration and productivity of degraded arid soils in the Cameroonian Sahel.

# 2. MATERIAL AND METHODS

## 2.1. Study Area

The study was carried out in the Lake Chad area, in the Far North of Cameroon, around 10 sites, including 5 sites which are affected by the invasion of water by *Eichhornia Crassipes* and 5 other sites on dry land which are concerned by the invasion by *Prosopis juliflora*.
<figure><img src="image_19.png" /><figcaption>**Figure 1:** Map of the Study Area</figcaption></figure>

**2.2. Biomass sampling**

The dry dead biomasses of Prosopis juliflora and Eichhornia crassipes were collected in bulk in nature. Then, via a manual selective sorting process described by (MEPN, 1998). They were separated then arranged into dry dead biomasses on the one hand and live biomasses on the other hand. Using the methodologies developed by (ASTMD5142-02, 2002), (MEPN, 1998), (Benjamin, 1996), (Wenny et al., 2019), the very selective sorting of the raw material is preferably done manually, using individual protective equipment (nose covers, gloves, etc.). The fork, the pickaxe, the rakes, the garbage excavations, the shovels were used to dig and separate the raw material from the organic deposits. Wheelbarrows and bags are tools that made it possible to collect, transport and store this raw material (MEPN, 1998), (Benjamin, 1996), (Wenny et al., 2019).

**2.3. Preparation of biochar and germination test**

The preparation of biochar was done by anaerobic pyrolysis of the biomass in a traditional pyrolization device. It consisted of heating the dry mixture of dry dead biomasses of *Prosopis juliflora* and *Eichhornia crassipes*, between 350°C and 600°C in a metallic medium in the absence of oxygen. The biomass (*Prosopis juliflora* and *Eichhornia crassipes*) was introduced into a carbonizer consisting of two metal drums intertwined one on top of the other following the diagram in Figure 2.
<figure><img src="image_20.png" /><figcaption>**Figure 2: Traditional carbonizer**</figcaption></figure>

The first metal drum is placed in another larger metal drum. The empty space (flame chamber) between the two metal barrels is the source of the pyrolysis flame powered by fuel (Wood) (Figure 2). The device is covered by a metal cover fitted with a chimney to allow the fumes to escape (Figure 2). The metal lid is of the same alloy as the barrel. Continuous pyrolysis for 5 hours made it possible to obtain biochar, samples of which were characterized (Figure 2). 2.4. Preparation of compost and germination test The Berkley rapid composting method was used in the work. It involves shredding the materials to a size of 1.25 cm to 3.75 cm, with frequent turning which allows compost to be produced in three weeks following the steps:

- Cleaning the site which must be sheltered from wind and bad weather.

- Once the site was clean, a storage area for raw materials was demarcated.

- The composting zone being in dry Sahelian zones, the arrangement of the composting device is done according to the most suitable composting method which is pit composting, the characteristics of which are:

<table><caption>**Table 1: Characteristics of the pit composting site**</caption><thead><tr><td>Type of composting</td><td>Installation location</td><td>Number of pits/tank per locality</td><td>Device dimensions</td></tr></thead><tbody><tr><td>Ditch</td><td>Non-floodable soil</td><td>3</td><td>- length: 2 m;<br/>- width: 2 m;<br/>- depth: 1 m.</td></tr></tbody></table>

### 2.4.1. The community experimental system and preparation of Biochar

The community experimental device used for this work consists of a carbonizer, a crusher and sieves designed in a traditional way specifically for this work. The carbonizer consists of two metal barrels which were used; one of 50 cm in diameter serving as the external walls of the pyrolyzer and the other of 25 cm serving as a carbonization chamber.
<figure><img src="image_21.png" /><figcaption>**Figure 3:** Biochar preparation device</figcaption></figure>

The device is equipped with a chimney and a sheet metal cover, allowing the channeling and escape of fumes. 2.4.2. Experimental Design and Treatments The trial was conducted using a randomized Fisher block design comprising three (3) blocks and six (6) treatments which are:

* T₀ = no biochar, no compost, no fertilizer;

* T₁ = 50 kg/ha of NPK (15-15-15) (50%) at emergence + 100 kg/ha of compost 0 (33.33%) at tillering + 150 Kg/ha of Compost_Biochar 1 (16.67%) at the rise;

* T₂ = 275 kg/ha of Compost_Biochar 1 (52.38%) at emergence + 125 kg/ha of Compost_Biochar 2 (23.81%) at tillering + 125 Kg/ha of Compost_Biochar 3 (23.81%) at emergence;

* T₃ = 350 kg/ha of Compost_Biochar 1 (58.33%) + 125 kg/ha of Compost_Biochar 2 (20.83%) at bolting + 125 kg/ha of Compost_Biochar 3 (20.83%) at heading;

* T₄ = 475 kg/ha of Compost_Biochar 1 (65.52%) + 125 kg/ha of Compost_Biochar 2 (17.24%) at bolting + 125 Kg/ha of Compost_Biochar 3 (17.24%) at heading;

* T₅ = 725 kg/ha of Compost_Biochar 1 (74.36%) + 125 kg/ha of Compost_Biochar 2 (12.82%) at bolting + 125 Kg/ha of Compost_Biochar 3 (12.82%) at heading;

The test was carried out over an area of 500 m² (50 m x 10 m) (Figure 2). Each elementary plot, measuring 10.85 m² (7.75m x 1.40m), included 2 ridges, each 7.25 m long and oriented widthwise (Figure 3). Except for the T₂ modality which is the recommended practice in terms of dose and application period, the other modalities were determined by considering possible scenarios of use and application of fertilizers resulting from climatic and/or rainfall forecasts observed at the start of the campaign. Thus T₄ and T₅ type modalities could be practiced in the hypothesis (h₁) where the forecasts are uncertain but where ultimately the season starts normally and seems to be good: in this case we do not add anything
at the start, then we make adjustments as late contributions. For logistical reasons there was no modality tested corresponding to the opposite hypothesis ($h_2$) where the season would become catastrophic after a good start, which would lead farmers not to apply compost after having made a contribution initial compost.

<figure><img src="image_22.png" /><figcaption>**Figure 4:** Experimental setup</figcaption></figure>

However, we can consider that this situation is generally framed by the $T_1$ and $T_3$ modalities. Fertilization treatments were assigned to main plots. The two sorghum varieties were assigned to elementary plots. Bunds were built around the main plots to prevent compost runoff between plots.

<figure><img src="image_23.png" /><figcaption>**Figure 5:** Plan d'une parcelle élémentaire</figcaption></figure>

Each elementary plot consisted of 2 lines of 7.75 m spaced 1 m apart; the inter-pocket space was 0.25 m. Five (5) to six (6) grains per pocket were sown and separated from two plants per pocket upon emergence, giving a density of 64,500 plants per hectare. The plants were transplanted onto the ridges, at a rate of 30±01 plants/ridge, or 60±02 plants per elementary plot. The spacings were 0.25 m
between plants and 0.25 m between rows, with 1 plant per hole, i.e. a density of 36,000±0018 plants per hectare method consisted of wrapping the seeds to be sown in biochar-compost and sowing it after spreading compost on the plots to be cultivated. In both cases, biochar-compost was applied at different stages of development of each variety. The tests were conducted in rainy conditions on both sites. Before the installation of each test, a cross plowing of 30 cm depth was done. Cultivation operations (weeding, hilling and phytosanitary treatments) were carried out regularly and as necessary to maintain optimal cultivation conditions.

### 2.4.3. Sowing and furnishing plots

Two methods were used when using Biochar-compost. The first method consisted of spreading compost on the cultivated plots and the second method consisted of wrapping the seeds to be sown in biochar-compost and sowing it after spreading compost on the plots to be cultivated. In both cases, biochar-compost was applied at different stages of development of each variety. The tests were conducted in rainy conditions on both sites. Before the installation of each test, a cross plowing of 30 cm depth was done. Cultivation operations (weeding, hilling and phytosanitary treatments) were carried out regularly and as necessary to maintain optimal cultivation conditions.

## 2.5. Data collection of growth parameters

Vegetative biomass (leaves + stems) was collected before late fertilization (at tillering, B₁) and after late fertilization (full flowering, B₂). On each elementary plot, 4 pockets were chosen randomly on the 2 central lines to be sampled. The dry biomass was evaluated after drying

2.5.1. Weekly plant growth

Growth was measured every 06 days during the dry season and the rainy season according to the Tom'Pousse method (Lambert et al., 2003): the plant per experimental unit was chosen according to the representativeness of the eight plants in the culture tank and all measures were taken on this plan (Jamal, et al., 2023). The parameters measured are weekly stem growth, length of a fully stretched mature leaf, flowering height, number of leaves and stem diameter. The weekly growth of the stem is obtained by measuring the distance between the apex and the mark left the previous week corresponding to the growth point and is taken using a measuring tape (Lambert et al., 2003; Jamal, et al., 2023). The diameter of the stem was taken at the growth point of the previous week using a vernier and represented the vigor of the plant. The mature leaf generally corresponded to the fifth leaf from the apex or the leaf immediately below the last
cluster having at least one set fruit. Its length was taken using a tape measure
from the tip of the leaf to the petiole. Flowering height was the distance measured
between the last flowering cluster and the apex. All these measurements were
useful in monitoring the progress of the plants and analyzing the growing
conditions (Lambert et al., 2003).

**2.5.1. Fruit yield**

Fruit yield was assessed weekly (or according to crop stage) during fruit harvest.
During the most productive summer months, two harvests per week were
required. Thus, at each harvest, a classification of the fruits was carried out in
order to evaluate the external quality of the fruits (Lambert et al., 2003; Jamal, et
al., 2023). For each class, the number and total weight of fruits were measured for
each experimental unit. The fruit classes were as follows: fruit in good condition,
fruit with apical rot, fruit with presence of macrocracks or microcracks,
misshapen fruit, small fruit, green fruit and other (uneven color, calcium oxalate
spots, fruit soft or stylar scar). A fruit in good condition was considered a salable
fruit on the market unlike fruits with physiological abnormalities or diseases. One
of the main physiological disorders encountered was apical rot which generally
occurs during a calcium deficiency manifesting itself in the form of a spot initially
white and becoming blackish at the apical end of the fruit. Like growth
measurements, yield information is a good indicator of crop health (Lambert et
al., 2003).

**2.5.1. Destructive growth**

Destructive growth measurements were also taken at the end of each change in
growing conditions, i.e. twice in July 2024 and September 2024, on one plant per
experimental unit. Parameters measured included total plant leaf area, number of
leaves and fruits, fresh and dry mass of leaves, fruits and stem, and stem length.
These measurements provided, in support of weekly growth and fruit yield
measurements, an index of plant vigor and crop health. The leaf area was
measured using a planimeter, the first step of which consisted of calibrating the
device using calibration disks (Lambert et al., 2003). All the leaves of the plant
were cut and carefully passed through a planimeter. The next step was to count
the fruits and bunches. When the stem was completely devoid of its leaves and
fruit, its length was measured using a measuring tape. All the fresh biomass was
then divided (leaves, fruits and stem) into brown paper bags and then weighed.
Subsequently, this fresh biomass contained in the bags was dried at 65°C for
approximately 15 days and the dry mass was then weighed. On the other hand,
each time the plants were stripped of leaves for maintenance purposes, the
biomass of cut leaves was weighed fresh and dry as well as the biomass of fruits
harvested at each harvest. This biomass in leaves and fruits was compiled and cumulated with the biomass of destructive growth measurements in order to obtain their total biomass converted into units per plant for the two reference periods, i.e. for cultivation weeks 1 to 11 (May to July 2024) and for cultivation weeks 12 to 24 (August to October 2024) (Lambert et al., 2003; Jamal, et al., 2023)

**2.6. Data analysis**

Means were compared using the least significant difference (LSD) test and presented values followed by letters in a column as not significantly different (P ≤ 0.05). Statistical differences between treatments were determined by analysis of variance (ANOVA) for completely randomized block designs (CRBD) and by Tukey's honestly significant difference test (P < 0.05) using of Excel and SPSS20.0.

**3. RESULTS AND DISCUSSION**

**3.1. Biomass sampling**

The samples are taken by manual harvesting on five sites with homogeneous multi-specific vegetation located within the territory of the waters of Lake Chad: in the town of Makary (12°33'45.98 north latitude and 14°26'51.3 east longitude, 1845 km²); in the town of Logone Birni (11°46'41.3 north latitude and 15°6'13.61 east longitude.), in the town of Fotokol (12°22'39.74 north latitude and 14°13'30.22 east longitude. 3285 Km²) , in the town of Darack (10°37'53.61" north latitude and 14°39'31.62" east longitude, 658.60 km2 ), in the town of Hilé Alifa (12° 42' 0" North latitude, 14 ° 19' 0" east longitude) and in the town of Blangoua (12°44'57" North Latitude and 14°34'49" East Longitude, 2116 Km²) (INS, 2005). The watercourses from Lake Chad cross these towns and villages which cover an area of approximately 110 km² out of a little more than 37,500 km² of the Cameroonian part of Lake Chad and the depth does not exceed 4 meters (LCBC, 2010). Annual variations in humidity and temperature lead to the subdivision of the climate into: Cool and dry season (mid-October to February), a hot and dry season from March to June; a hot and humid season called the "rainy season" which lasts from mid-June to mid-September with maximum values in August. The weakly ferralitic red soils of Lake Chad in the Logone and Chari area are characterized by thorny vegetation dominated by: *Eichhornia crassipes*, *Acacia seyal*, *Lannea humilis*, *Balanites aegyptiaca*, *Acacia senegal* and *Acacia sieberiana*. The grassy carpet is poorly developed. In the rainy season, these low permeability soils retain precipitation and the water stagnates in small pools. The collection of raw materials is an operation which consists of mowing *Eichhornia crassipes* plants, waste from other invasive plants or any other from
the place of their proliferation to a place of final elimination. It begins with the identification of raw materials in proliferation sites.

### 3.1.1. Living biomass and CO₂ stock

In the study sites, the average diameter of the trunks and stems of the species studied varies. The average diameter of the main trunks of Prosopis juliflora is 23.404±5.253 cm. The basal area covered by Prosopis juliflora is 3.978±1.391 m²/Ha with a coverage of 955.8±1.391m²/Ha and a biomass volume of 7.956±0.512 m³.

<figure><img src="image_24.png" /><figcaption>**Photo 1:** a) Living biomass of *Prosopis juliflora*; b) Dry dead biomass of *Prosopis juliflora*</figcaption></figure>

The average diameter of the main stems of *Eichhornia crassipes* is 5.914±0.893 cm with a covered basal area of 2.872±0.449 m²/Ha and biomass volume of 1.436±0.603 m³ (Table 2).

<table><caption>**Table 2:** Determination of aboveground biomass (BA)</caption><thead><tr><th>Species</th><th>Average diameter of the main trunks (and stems) of the species (cm)</th><th>Basal area covered by species (m²/Ha)</th><th>Density (Ind. No./Km²)</th><th>Volume of species biomass (m³)</th></tr></thead><tbody><tr><td><i>Prosopis juliflora</i></td><td>23.404±5.253<sup>a, g</sup></td><td>3.978±1.391<sup>d</sup></td><td>16.507±1.768<sup>a</sup></td><td>7.956±0.512<sup>e, f</sup></td></tr><tr><td><i>Eichhornia crassipes</i></td><td>5.914±0.893<sup>e</sup></td><td>2.872±0.449<sup>c</sup></td><td>151.573±21.171<sup>b</sup></td><td>1.436±0.603<sup>d</sup></td></tr></tbody></table>

The total average biomass of *Prosopis juliflora* and *Eichhornia crassipes* studied is variable. However, the total average biomass of *Prosopis juliflora* is 16.80±1.54 T/Ha, lower than the total average biomass of *Eichhornia crassipes* which is
197.77±0.79 T/Ha.

<figure><img src="image_25.png" /><figcaption>**Photo 2:** a) Live biomass of *Eichhornia crassipes*; b) Dry dead biomass of *Eichhornia crassipes*</figcaption></figure>

The average carbon stock by *Prosopis juliflora* is 7.896±0.183 T/Ha with an average Carbon Equivalent of 15.06±0.35 T/Ha while the average carbon stock by *Eichhornia crassipes* is 92.952±1.547 T/Ha with an average Carbon Equivalent of 22.36±0.13 T/Ha (Table 3).

<table><caption>**Table 3:** Total living biomass and Carbon stock of each species</caption><thead><tr><th>Species</th><th>Aboveground biomass of species (BA,T/Ha)</th><th>Belowground biomass of species (BS,T/Ha)</th><th>Total biomass of species (BT,T/Ha)</th><th>Carbon stock of species (SC, T/Ha)</th><th>Carbon equivalent (EqC, T/Ha)</th></tr></thead><tbody><tr><td><em>Prosopis juliflora</em></td><td>2.65±0.71<sup>a</sup></td><td>14.15±0.83<sup>a</sup></td><td>16.80±1.54<sup>a</sup></td><td>7.896±0.183<sup>f</sup></td><td>15.06±0.35<sup>d</sup></td></tr><tr><td><em>Eichhornia crassipes</em></td><td>67.15±0.03<sup>c</sup></td><td>130.62±0.76<sup>b</sup></td><td>197.77±0.79<sup>a</sup></td><td>92.952±1.547<sup>a</sup></td><td>22.36±0.13<sup>e</sup></td></tr></tbody></table>

### 3.1.2. Preparation of dry dead biomass and bioenergy stock

The average weight of the trunk of the dry dead biomass of *Prosopis juliflora* is 17.02±3.00 kg/m² while its average weight is 58.27±4.56 kg/m². The average PCI of the dry dead biomass of *Prosopis juliflora* is 17.92±0.02 MJ/kg with its average dry stock is 75.29±6.18 kg/m² and the average stock of its bioenergy is 1.35±0.101 GJ/m². These values are distributed in the table below:

<table><caption>**Table 4:** Dry dead biomass and bioenergy stock</caption><thead><tr><th>Species</th><th>Trunk weight (kg/m²)</th><th>Plant weight (kg/m²)</th><th>PCI (MJ/kg)</th><th>Biomass stock (kg/m²)</th><th>Bioenergy stock (GJ/m²)</th></tr></thead><tbody><tr><td><em>Eichhornia crassipes</em></td><td>14.13±2.76<sup>a</sup></td><td>54.472±4.872<sup>b</sup></td><td>18.52±0.02<sup>a</sup></td><td>68.602±5.456<sup>c</sup></td><td>1.27±0.10<sup>a</sup></td></tr><tr><td><em>Prosopis juliflora</em></td><td>17.022±2.738<sup>b</sup></td><td>58.268±3.745<sup>a</sup></td><td>17.928±0.54<sup>b</sup></td><td>75.29±5.32<sup>a</sup></td><td>1.35±0.09<sup>c</sup></td></tr></tbody></table>

The average weight of the stems of the dry dead biomass of *Eichhornia crassipes* is 14.13±3.50 kg/m² while its average weight is 54.47±4.06 kg/m². The average
PCI of the dry dead biomass of Eichhornia crassipes is 18.52±0.02MJ/kg with its average dry stock is 72.22±6.19 kg/m² and the average stock of its bioenergy is 1.31±0.103 GJ/m².

### 4.1.3. Preparation of Biochar and germination test
#### a- Community experimental system

Four composters (1 m wide, 2 m long and 0.3 m high) were dug. In each composter, a total of 5kg of raw material was introduced:

<table><caption>**Table 5:** Experimental content of each Compost_Biochar</caption><thead><tr><th>Raw material</th><th></th><th>Compost_Biochar 0<br>(100-0)%</th><th>Compost_Biochar 1<br>(64.28-35.71)%</th><th>Compost_Biochar 2<br>(47.36-52.63)%</th><th>Compost_Biochar 3<br>(50-50)%</th></tr></thead><tbody><tr><td rowspan="5">Compost<br>based on</td><td>Fresh <i>Eichhornia crassipes</i> (kg)</td><td>2.5</td><td>5</td><td>5</td><td>10</td></tr><tr><td>Dry <i>Pennisetum villosum</i> (kg)</td><td>1</td><td>2</td><td>2</td><td>3</td></tr><tr><td>Fresh <i>Urtica dioica</i> (kg)</td><td>0.5</td><td>0.5</td><td>0.5</td><td>0.5</td></tr><tr><td>Beef dung (kg)</td><td>0.5</td><td>0.5</td><td>0.5</td><td>0.5</td></tr><tr><td>Urine (L)</td><td>1</td><td>1</td><td>1</td><td>1</td></tr><tr><td>Biochar based on dry <i>Prosopis juliflora</i></td><td></td><td>0</td><td>5</td><td>10</td><td>15</td></tr></tbody></table>

Each composter was treated with *Urtica dioica*, then covered with various other layers of raw material so as to alternate fresh material with dry material. The composter was placed in the shade in a secure location away from rodents and other animals and to prevent moisture loss.

The humidity content of the composter was maintained and adjusted to around 80% daily. Using a thermometer, temperature readings were taken daily to monitor the progress of the maturation of the compost. After maturation, a sample of the compost was taken from each composter, then air-dried at room temperature in the shade and stored in a plastic bag for later analysis.

<figure><img src="image_26.png" /><figcaption>**Photo 3:** a) Collection of *Eichhornia crassipes* biomass; b) Sorting of dry dead biomass of *Eichhornia crassipes* c) Compost based on *Eichhornia crassipes* d) Biochar based on dry *Prosopis juliflora*, e) Compost_Biochar based on *Prosopis juliflora* _Eichhornia crassipes* left to dry.</figcaption></figure>
The tests were carried out on the plots developed in bocage and stone bunds of the NGO SAHEL NATURE CONSULTING FOR COMMUNITIES. The surface texture of these soils was clay-sandy type (clay = 38.3%; silt = 24.4% and sand = 37.3%).

<table><caption>Table 6: Physico-chemical characteristics of the soil before setting up the test.</caption><thead><tr><th>Characteristics</th><th>Soil</th><th>Biochar</th><th>Compost_Biochar 0 (100-0)%</th><th>Compost_Biochar 1 (64.28-35.71)%</th><th>Compost_Biochar 2 (47.36-52.63)%</th><th>Compost_Biochar 3 (50-50)%</th></tr></thead><tbody><tr><td>Total clay (%)</td><td>38.3</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td></tr><tr><td>Total silt (%)</td><td>24.4</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td></tr><tr><td>Total sand (%)</td><td>37.3</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td></tr><tr><td>Organic carbon (g/kg)</td><td>6</td><td>74.5</td><td>38</td><td>89.8</td><td>93.2</td><td>91.1</td></tr><tr><td>Total nitrogen (g/kg)</td><td>0.7</td><td>1.5</td><td>1.8</td><td>3.5</td><td>3.9</td><td>3.4</td></tr><tr><td>C/N</td><td>9</td><td>-</td><td>21.1</td><td>25.6</td><td>23.9</td><td>26.8</td></tr><tr><td>Assimilable phosphorus (mg/kg)</td><td>12</td><td>32</td><td>34</td><td>36</td><td>41</td><td>35</td></tr><tr><td>Available potassium (mg/kg)</td><td>177</td><td>141</td><td>138</td><td>144</td><td>148</td><td>146</td></tr><tr><td>Ca (mg/kg)</td><td>714</td><td>140</td><td>174</td><td>185</td><td>115</td><td>117</td></tr><tr><td>Mg (mg/kg)</td><td>171</td><td>20</td><td>87.6</td><td>80.2</td><td>43.1</td><td>41.3</td></tr><tr><td>pH-water</td><td>6.7</td><td>9.8</td><td>8.8</td><td>9.9</td><td>8.7</td><td>7.8</td></tr><tr><td>pH-KCl</td><td>5,1</td><td>-</td><td>5.7</td><td>-</td><td>-</td><td>-</td></tr><tr><td>CEC (mEq/100 g of soil)</td><td>3.9</td><td>-</td><td>5.2</td><td>-</td><td>-</td><td>-</td></tr><tr><td>WHC</td><td>-</td><td>336.7</td><td>375.4</td><td>365.4</td><td>367.1</td><td>353.6</td></tr><tr><td>Apparent density</td><td>-</td><td>70</td><td>74</td><td>73</td><td>71</td><td>70.7</td></tr><tr><td>Specific surface area (m²/g)</td><td>-</td><td>1.7</td><td>1.9</td><td>2.1</td><td>2.6</td><td>2.4</td></tr></tbody></table>

It is a soil with moderate acidity (pH-water = 6.7 and pH-KCl = 5.1) and poorly provided with essential nutrients from plants and insects, with an average cation exchange capacity equal to 3.9 mEq/100 g (table 6). The total nitrogen content is <1 g/kg of soil; the contents of Ca²⁺ and Mg²⁺ cations on the exchange complex are respectively 714 and 171 mg/kg of soil. The initial organic carbon content was 6 g/kg of soil

### 4.1.4. Effect of Compost_Biochar based on Prosopis juliflora_Eichhornia crassipes after 8 days of seed germination on the test culture.

A significant difference was noted in the percentage of crop germination between the treatments at 15 ton/ha (Table 8). The germination of Zea mays and Solanum lycopersicum L. was significantly stimulated by different doses of Compost_Biochar based on Prosopis juliflora_Eichhornia crassipes (P=0:01) and (P=0:02), respectively.
<table><caption>**Table 7:** Percentage of germination after 8 days during treatment with Compost_Biochar based on *Prosopis juliflora_Eichhornia crassipes* (CB)</caption><thead><tr><th colspan="7">Sandy clay soil T<sub>01</sub> (95%-05%) without Compost and without Biochar based on <i>Prosopis juliflora_Eichhornia crassipes</i></th></tr></thead><tbody><tr><th colspan="7">Control treatments T<sub>01</sub> (sand/clay) %</th></tr><tr><td>TGP (%) of Zea mays</td><td>95/05</td><td>90/10</td><td>85/15</td><td>80/20</td><td>75/25</td><td>70/30</td></tr><tr><td>TGP (%) of <i>Solanum lycopersicum</i> L</td><td>36.3±0.47<sup>a</sup></td><td>39.4±0.43<sup>b</sup></td><td>43.4±0.39<sup>a</sup></td><td>44.3±0.94<sup>c</sup></td><td>46.5±0.79<sup>a</sup></td><td>47.8±0.65<sup>a</sup></td></tr><tr><td></td><td colspan="6">100% biochar based on <i>Prosopis juliflora_Eichhornia crassipes</i> on sandy clay soil T<sub>01</sub> (95%-05%)</td></tr><tr><th colspan="7">Control treatments T<sub>02</sub> (Biochar/Soil) %</th></tr><tr><td>TG (%) of Zea mays</td><td>05/95</td><td>10/90</td><td>15/85</td><td>20/80</td><td>25/75</td><td>30/70</td></tr><tr><td>TG (%) of <i>Solanum lycopersicum</i> L</td><td>43.6±0.47<sup>a</sup></td><td>45.9±0.48<sup>c</sup></td><td>47.6±0.94<sup>a</sup></td><td>49.2±0.45<sup>c</sup></td><td>49.8±0.87<sup>a</sup></td><td>52.3±0.49<sup>a</sup></td></tr><tr><td></td><td colspan="6">100% compost based on <i>Prosopis juliflora_Eichhornia crassipes</i> on sandy clay soil T<sub>01</sub> (95%-05%)</td></tr><tr><th colspan="7">Control treatments T<sub>03</sub> (Compost/Soil) %</th></tr><tr><td>TGP (%) of Zea mays</td><td>05/95</td><td>10/90</td><td>15/85</td><td>20/80</td><td>25/75</td><td>30/70</td></tr><tr><td>TGP (%) of <i>Solanum lycopersicum</i> L</td><td>63.4±0.64<sup>a</sup></td><td>64.9±0.36<sup>c</sup></td><td>67.3±0.59<sup>a</sup></td><td>69.3±0.86<sup>c</sup></td><td>71.3±0.33<sup>a</sup></td><td>72.8±0.57<sup>a</sup></td></tr></tbody></table>

The highest germination percentage (97.9±0.96%) was recorded with 35 t/ha of Compost_Biochar 2 (47.36-52.63)% based on *Prosopis juliflora_Eichhornia crassipes* on sandy clay soil T<sub>02</sub> (95%-05%) for Zea mays and *Solanum lycopersicum* L. cultures, respectively. While the lowest germination percentage (33.6±0.75%) for *Solanum lycopersicum* L was on sandy clay soil T<sub>01</sub> (95% sand/05% clay) without Compost and without Biochar based on *Prosopis juliflora_Eichhornia crassipes*, and which was one of the control groups.

<table><caption>**Table 8:** Percentage of germination after 8 days during treatment with Compost_Biochar based on *Prosopis juliflora_Eichhornia crassipes* (CB)</caption><thead><tr><th colspan="7">Compost_Biochar 1 (64.28-35.71)% based on <i>Prosopis juliflora_Eichhornia crassipes</i> on sandy clay soil T01 (95%-05%)</th></tr></thead><tbody><tr><th>T<sub>1</sub> treatments (ton/ha)</th><td>5</td><td>10</td><td>15</td><td>20</td><td>25</td><td>30</td></tr><tr><td>TGP (%) of Zea mays</td><td>86.3±0.55<sup>a</sup></td><td>88.6±0.74<sup>c</sup></td><td>91.1±0.1<sup>a</sup></td><td>93.5±0.43<sup>c</sup></td><td>93.7±0.8<sup>a</sup></td><td>94.1±0.8<sup>a</sup></td></tr><tr><td></td><td colspan="6">TGP (%) of <i>Solanum lycopersicum</i> L</td></tr><tr><td></td><td>94.1±0.18<sup>c</sup></td><td>94.6±0.83<sup>b</sup></td><td>94.8±0.5<sup>d</sup></td><td>95.5±0.61<sup>b</sup></td><td>96.2±0.7<sup>a</sup></td><td>96.7±0.6<sup>a</sup></td></tr></tbody></table><table><thead><tr><th colspan="7">Compost_Biochar 2 (47.36-52.63)% based on <i>Prosopis juliflora_Eichhornia crassipes</i> on sandy clay soil T02 (95%-05%)</th></tr></thead><tbody><tr><th>T<sub>2</sub> treatments (ton/ha)</th><td>5</td><td>10</td><td>15</td><td>20</td><td>25</td><td>30</td></tr><tr><td>TGP (%) of Zea mays</td><td>81.5±0.43<sup>b</sup></td><td>81.9±0.33<sup>c</sup></td><td>83.2±0.3<sup>a</sup></td><td>83.8±0.02<sup>d</sup></td><td>85.2±0.5<sup>a</sup></td><td>86.9±0.3<sup>a</sup></td></tr><tr><td></td><td colspan="6">TGP (%) of <i>Solanum lycopersicum</i> L</td></tr><tr><td></td><td>72.3±0.18<sup>c</sup></td><td>72.6±0.44<sup>b</sup></td><td>72.8±0.6<sup>d</sup></td><td>74.5±0.39<sup>b</sup></td><td>76.4±0.4<sup>a</sup></td><td>76.4±0.8<sup>a</sup></td></tr></tbody></table><table><thead><tr><th colspan="7">Compost_Biochar 3 (50-50)% based on <i>Prosopis juliflora_Eichhornia crassipes</i> on sandy clay soil T03 (95%-05%)</th></tr></thead><tbody><tr><th>T<sub>3</sub> treatments (ton/ha)</th><td>5</td><td>10</td><td>15</td><td>20</td><td>25</td><td>30</td></tr><tr><td>TG (%) of Zea mays</td><td>83.5±0.44<sup>b</sup></td><td>84.1±0.12<sup>c</sup></td><td>86.1±0.2<sup>a</sup></td><td>86.2±0.83<sup>d</sup></td><td>89.1±0.1<sup>a</sup></td><td>90.5±0.6<sup>a</sup></td></tr><tr><td></td><td colspan="6">TG (%) of <i>Solanum lycopersicum</i> L</td></tr><tr><td></td><td>83.2±0.42<sup>c</sup></td><td>84.7±0.44<sup>b</sup></td><td>84.8±0.6<sup>d</sup></td><td>85.1±0.54<sup>b</sup></td><td>86.3±0.1<sup>a</sup></td><td>86.5±0.1<sup>a</sup></td></tr></tbody></table>

Obviously, the capacity of Compost_Biochar 1 (64.28-35.71)% based on *Prosopis juliflora_Eichhornia crassipes* on sandy clay soil T<sub>01</sub> (95%-05%) to retain humidity in the success of germination would have played a role preponderant as described by Kammann et al. (2011). This result would have been amplified by the combined effects of Compost_Biochar 1 (64.28_35.71)% based on *Prosopis juliflora_Eichhornia crassipes* which would have amplified the germination capacity of the sandy clay soil T<sub>01</sub> (95%-05%) and which perhaps corroborates the findings of Rillig et al., 2010, Ali et al., 2023, and Free et al., 2010, who reported that increasing biochar content proportionally increased germination. In other words, seeds sown in T<sub>01</sub> sandy_clayey soils (95%-05%) amended with Compost_Biochar 1,2 and 3 germinate more quickly than in T<sub>01</sub> sandy_clayey soils (95%-05%) without
Compost and without Biochar based on *Prosopis juliflora* *Eichhornia crassipes* and better than Biochar/Soil and Compost/soils.

<table><caption>**Table 9:** Physical parameters of seed germination after 8 days of treatment with Compost_Biochar (CB) based on *Prosopis juliflora* *Eichhornia crassipes*</caption><thead><tr><th>Type of soil</th><th>pH</th><th>Humidity (%)</th><th>Soil permeability/soil (mm.h<sup>-1</sup>)</th><th>Soil reflectance (mg/m<sup>-3</sup>)</th><th>Maximum ground temperature (°C)</th><th>Soil conductivity (µS/cm)</th></tr></thead><tbody><tr><td>Sandy_clayey soil (95%-05%)</td><td>7.9±0.1<sup>a</sup></td><td>31±0.6<sup>b</sup></td><td>19.7±5.3<sup>a, b</sup></td><td>567.7±35.3<sup>a, b</sup></td><td>15.3±0.4<sup>c</sup></td><td>237.92±42.01<sup>a</sup></td></tr><tr><td>Compost/ Soil</td><td>8.2±0.6<sup>b, c</sup></td><td>39±0.8<sup>c</sup></td><td>17.3±2.8<sup>a, c</sup></td><td>571.3±28.2<sup>a, c</sup></td><td>13.5±0.1<sup>b</sup></td><td>254.82±53.06<sup>a, c</sup></td></tr><tr><td>Biochar/ Soil</td><td>9.8±0.3<sup>b</sup></td><td>94±0.3<sup>b, c</sup></td><td>12.4±1.3<sup>a, c</sup></td><td>582.4±31.5<sup>a, c</sup></td><td>14.7±0.8<sup>c</sup></td><td>279.38±22.53<sup>b</sup></td></tr><tr><td>Compost_Biochar 1(64.28_35.71)%</td><td>9.2±0.1<sup>a, c</sup></td><td>98±0.1<sup>c, d</sup></td><td>17.8±5.1<sup>b, d</sup></td><td>587.8±45.1<sup>b, d</sup></td><td>15.3±0.6<sup>c</sup></td><td>279.82±50.91<sup>a, c</sup></td></tr><tr><td>Compost_Biochar 2 (47.36-52.63)%</td><td>8.7±0.4<sup>d</sup></td><td>95±0.2<sup>a, d</sup></td><td>15.5±1.2<sup>c, d</sup></td><td>591.5±21.8<sup>c, d</sup></td><td>16.8±0.8<sup>c</sup></td><td>288.07±20.74<sup>d</sup></td></tr><tr><td>Compost_Biochar 3 (50-50)%</td><td>7.8±0.5<sup>c</sup></td><td>96±0.7<sup>a</sup></td><td>15.3±2.7<sup>a, b</sup></td><td>589.7±42.6<sup>a, b</sup></td><td>15.7±0.4<sup>c</sup></td><td>287.98±40.65<sup>c</sup></td></tr></tbody></table>

The change in reflectance of the Compost_Biochar substrate surface results in a substantial increase in soil temperature (Licht and Al-Kaisi, 2005; Ali et al., 2023).

<figure><img src="image_27.png" /><figcaption>**Graph 1:** Reflectance of the surface of the Compost_Biochar substrate</figcaption></figure>

An increase in soil temperature, due to the application of biochars, would have had positive impacts on seed germination, crop establishment and early growth (Genesio et al., 2012; Ali et al., 2023).

Ecologically, Compost_Biochar 2 (47.36-52.63)% has the highest number of Lumbricina (16.43±01.92) with the number of other animal species averaging
09.15±00.22 while the lowest number Lumbricina (01.97±00.53) was observed on sandy-clayey soil (95%-05%).

<table><caption>**Table 10:** Ecological parameters of seed germination after 8 days of treatment with Compost_Biochar (CB) based on *Prosopis juliflora_Eichhornia crassipe*</caption><thead><tr><th>Soil type</th><th>Number of Lumbricina</th><th>Number of other plant species</th><th>Number of other animal species</th><th>Frequency of each species</th><th>Diversity index</th><th>Biomass abundance index</th></tr></thead><tbody><tr><td>Sandy_clayey soil (95%-05%)</td><td>01.97±00.53<sup>a,b</sup></td><td>03.77±00.53<sup>a,b</sup></td><td>01.92±00.04<sup>a</sup></td><td>01.93±00.66<sup>b</sup></td><td>03.44±00.79<sup>a,b</sup></td><td>02.37±00.73<sup>a,b</sup></td></tr><tr><td>Compost/ Soil</td><td>07.33±01.28<sup>a,c</sup></td><td>03.23±00.82<sup>a,c</sup></td><td>02.58±00.56<sup>a,c</sup></td><td>02.39±00.38<sup>c</sup></td><td>05.99±00.54<sup>a,c</sup></td><td>02.53±00.32<sup>a,c</sup></td></tr><tr><td>Biochar/ Soil</td><td>08.22±01.13<sup>a,c</sup></td><td>05.82±00.31<sup>a,c</sup></td><td>03.29±00.23<sup>b</sup></td><td>04.94±00.53<sup>a,c</sup></td><td>06.59±00.53<sup>a,c</sup></td><td>04.55±00.43<sup>a,c</sup></td></tr><tr><td>Compost_Biochar 1(64.28_35.71)%</td><td>14.78±00.51<sup>b,d</sup></td><td>08.87±00.45<sup>b,d</sup></td><td>03.82±00.91<sup>a,c</sup></td><td>05.98±00.41<sup>c,d</sup></td><td>09.89±00.88<sup>b,d</sup></td><td>06.07±00.85<sup>b,d</sup></td></tr><tr><td>Compost_Biochar 2 (47.36-52.63)%</td><td>16.43±01.92<sup>c,d</sup></td><td>09.15±00.22<sup>c,d</sup></td><td>03.87±00.74<sup>d</sup></td><td>06.95±00.52<sup>a,d</sup></td><td>11.15±00.78<sup>c,d</sup></td><td>06.95±00.32<sup>c,d</sup></td></tr><tr><td>Compost_Biochar 3 (50-50)%</td><td>15.73±02.27<sup>a,b</sup></td><td>08.97±00.43<sup>a,b</sup></td><td>03.78±00.64<sup>c</sup></td><td>05.56±00.27<sup>a</sup></td><td>09.97±00.11<sup>a,b</sup></td><td>05.55±00.65<sup>a,b</sup></td></tr></tbody></table>

The highest number of other plant species is 03.87±00.74 with a frequency of each species highest of 06.95±00.52%. The highest diversity index is 11.15±00.78 and a biomass abundance index of 06.95±00.32 in Compost_Biochar 2 (47.36-52.63)%.

Biochar improves soil fertility by increasing soil pH, organic carbon, phosphorus and potassium which stimulate seed germination (Asai et al., 2009; Ali et al., 2023). Furthermore, Steiner et al. (2008), Wardle et al. (2008) and Ali et al., 2023 observed that the application of biochar alters the mineralization of organic matter, which is linked to the release of nutrients such as nitrogen, the reduction of which by 60% by leaching, requires 1 addition of 20% fertilizer to minimize loss of seeds before germination and a possibility of 10% seed savings achievable through the application of biochar (Lehmann et al., 2003.). As biochar increases, seed and nutrient saving efficiency or absorption/leaching ratio will be higher (Steiner et al., 2008 and Ali et al., 2023). In short, in our case, the germination of seeds could be explained by the fertilization of seedlings and the beginnings of crops tested with Compost_Biochar.

### 4.1.5. Effect of Compost_Biochar based on Prosopis juliflora_Eichhornia crassipes on the biomass of the shoots of the crops tested after 04 weeks of plant growth on the test crop.

Cultivated under the same conditions, the fresh and dry weights of the young shoots of *Zea mays* and *Solanum lycopersicum* L which were recorded, showed significant differences between the treatments of the control group and the test group with Compost_Biochar (CB) at basis of *Prosopis juliflora_Eichhornia crassipes* on the test culture (Table 2). The results also showed that the application of a single dose of Compost_Biochar (15 t/ha) based on *Prosopis juliflora_Eichhornia crassipes* on sandy clay soil (95%-05%), increased the weight of young shoots of
*Zea mays* by 35.04±2.89%, and *Solanum lycopersicum* L 19.24±1.81% compared to the weight of the control groups.

<table><caption>**Table 11:** Weight gain of plants after 04 weeks of growth and treatment with Compost_Biochar (CB) based on *Prosopis juliflora* *Eichhornia crassipes* on the test culture</caption><thead><tr><th colspan="3">Sandy clay soil T<sub>01</sub> (95%-05%) without Compost and without Biochar based on <i>Prosopis juliflora</i> <i>Eichhornia crassipes</i></th></tr></thead><tbody><tr><th colspan="3">Control treatments T<sub>01</sub> (sand/clay) %</th></tr><tr><td></td><td>Fresh weight (g)</td><td>Dry weight (g)</td></tr><tr><td><i>Zea mays</i></td><td>68.71±02.66</td><td>13.22±07.45</td></tr><tr><td><i>Solanum lycopersicum</i> L</td><td>18.04±06.72</td><td>03.48±00.76</td></tr><tr><th colspan="3">100% biochar based on <i>Prosopis juliflora</i> <i>Eichhornia crassipes</i> on sandy clay soil T<sub>01</sub> (95%-05%)</th></tr><tr><th colspan="3">Control treatments T<sub>02</sub> (Biochar/Soil) %</th></tr><tr><td></td><td>Fresh weight (g)</td><td>Dry weight (g)</td></tr><tr><td><i>Zea mays</i></td><td>184.75±06.26</td><td>64.73±03.75</td></tr><tr><td><i>Solanum lycopersicum</i> L</td><td>78.01±06.72</td><td>15.09±01.12</td></tr><tr><th colspan="3">100% compost based on <i>Prosopis juliflora</i> <i>Eichhornia crassipes</i> on sandy clay soil T<sub>01</sub> (95%-05%)</th></tr><tr><th colspan="3">Control treatments T<sub>03</sub> (Compost/Soil) %</th></tr><tr><td></td><td>Fresh weight (g)</td><td>Dry weight (g)</td></tr><tr><td><i>Zea mays</i></td><td>192.87±02.66</td><td>67.58±01.23</td></tr><tr><td><i>Solanum lycopersicum</i> L (after 20 days)</td><td>80.41±02.39</td><td>15.47±01.38</td></tr><tr><td><i>Solanum lycopersicum</i> L (after 28 days)</td><td>197.9±10.96<sup>e</sup></td><td>37.23±05.18<sup>c</sup></td></tr></tbody></table>

Although an insignificant increase was observed with single dose treatments of Compost (100%) based on *Prosopis juliflora* *Eichhornia crassipes*, and half, there was a slight decrease (3.47±0.77%) with Biochar (100%) in double dose.

During the cultivation of *Zea mays* and *Solanum lycopersicum* L, Compost_Biochar 2 (47.36-52.63)% based on *Prosopis juliflora* *Eichhornia crassipes*, in single and double doses, contributed to increasing the weight of the shoots by approximately 64.58±02.22% and 56.41±05.30%, respectively of *Zea mays* and *Solanum lycopersicum* L. Although an insignificant increase was observed with single and half dose treatments, there was had a slight decrease (3%) between all treatments with Compost_Biochar 1 and 3 at double dose
<table><caption>**Table 12:** Weight gain of plants after 04 weeks of growth and treatment with Compost_Biochar (CB) based on *Prosopis juliflora_Eichhornia crassipes* on the test culture</caption><thead><tr><th colspan="4">Compost_Biochar 1 (64.28-35.71)% based on <i>Prosopis juliflora_Eichhornia crassipes</i> on sandy clay soil T01 (95%-05%)</th></tr><tr><th>T<sub>1</sub> treatments (15 ton/ha)</th><th>Density (plants/m<sup>2</sup>)</th><th>Fresh weight (g)</th><th>Dry weight (g)</th></tr></thead><tbody><tr><td><i>Zea mays</i></td><td>7.11±20.21<sup>a</sup></td><td>196.11±20.21<sup>a</sup></td><td>67.75±05.09<sup>c</sup></td></tr><tr><td><i>Solanum lycopersicum</i> L</td><td>3.18±10.76<sup>d</sup></td><td>84.18±10.76<sup>d</sup></td><td>36.54±05.62<sup>d</sup></td></tr></tbody><thead><tr><th colspan="4">Compost_Biochar 2 (47.36-52.63)% based on <i>Prosopis juliflora_Eichhornia crassipes</i> on sandy clay soil T02 (95%-05%)</th></tr><tr><th>T<sub>2</sub> treatments (15 ton/ha)</th><th>Density (plants/m<sup>2</sup>)</th><th>Fresh weight (g)</th><th>Dry weight (g)</th></tr></thead><tbody><tr><td><i>Zea mays</i></td><td>7.11±20.21<sup>a</sup></td><td>197.14±10.61<sup>e</sup></td><td>69.81±10.18<sup>b</sup></td></tr><tr><td><i>Solanum lycopersicum</i> L</td><td>3.18±10.76<sup>d</sup></td><td>89.15±08.87<sup>e</sup></td><td>38.86±10.11<sup>a</sup></td></tr></tbody><thead><tr><th colspan="4">Compost_Biochar 3 (50-50)% based on <i>Prosopis juliflora_Eichhornia crassipes</i> on sandy clay soil T03 (95%-05%)</th></tr><tr><th>T<sub>3</sub> treatments (15 ton/ha)</th><th>Density (plants/m<sup>2</sup>)</th><th>Fresh weight (g)</th><th>Dry weight (g)</th></tr></thead><tbody><tr><td><i>Zea mays</i></td><td>7.11±20.21<sup>a</sup></td><td>194.9±10.22<sup>a</sup></td><td>68.51±07.43<sup>b</sup></td></tr><tr><td><i>Solanum lycopersicum</i> L</td><td>3.18±10.76<sup>d</sup></td><td>79.91±10.96<sup>e</sup></td><td>37.23±05.18<sup>c</sup></td></tr></tbody></table>

Compost_Biochar 2 (47.36-52.63)% based on *Prosopis juliflora_Eichhornia crassipes* on sandy clay soil T02 (95%-05%) contributed effectively to the growth of young shoots.

Biochar can also improve the water retention capacity of the soil (Laird et al., 2010.), thereby facilitating seedling biomass gain (Kammann et al., 2011.). Plant growth responses can be altered by biochar-induced changes in soil nutritional conditions, particularly P and K cycling (Taghizadeh-Toosi et al., 2012.). Plant resistance was greater with biochar additions to the soil (31.32±02.01%_32.31±00.21%) (Elad et al., 2010; Elmer and Pignatello, 2011; Ali et al., 2023). Similar studies confirmed that better seed germination (30% improvement), better shoot height (24%) and better biomass production (13%) among seven native woody plants on soils subjected to charcoal from kilns have been reported compared to unamended soils (Chidumayo, 1994.).

Similar to our results, it was reported that the use of biochar resulted in an approximately 20-30% increase in durum wheat biomass compared to the use of mineral fertilizer alone (Alburquerque et al., 2013; Ali et al., 2023) and maize biomass yield increased by 44% on charcoal site soils compared to adjacent field soils (Oguntunde et al., 2004; Ali et al., 2023). Additionally, not all soils respond the same to biochar, and it may take time to observe significant changes in soil and crop attributes after biochar addition (Nair, 2015).

**5. Effect of Compost_Biochar based on *Prosopis juliflora_Eichhornia crassipes* after 08 weeks of plant growth on the test culture.**

**5.1. Effect of Compost_Biochar on root growth parameter.**
The greatest root length of *Zea mays* (39.71±01.16 cm) was recorded at 15 t/ha of Compost_Biochar 2 (47.36-52.63) % based on *Prosopis juliflora_Eichhornia crassipes* on sandy clay soil T02 (95%-05%) followed by the lowest root length (07.65±00.59 cm) recorded during the control of the treatment at 15 t/ha of Compost_Biochar 1 (64.28-35.71) % based on *Prosopis juliflora_Eichhornia crassipes* on T01 sandy clay soil (95%-05%).

<table><caption>**Table 13:** Effect of treatment with Compost_Biochar (CB) based on *Prosopis juliflora_Eichhornia crassipes* on root growth parameters.</caption><thead><tr><th colspan="3">Compost_Biochar 1 (64.28-35.71) % based on <i>Prosopis juliflora_Eichhornia crassipes</i> on sandy clay soil T01 (95%-05%)</th></tr><tr><th>T<sub>1</sub> treatments (15 ton/ha)</th><th>Highest root length (cm)</th><th>Lowest root length (cm)</th></tr></thead><tbody><tr><td><i>Zea mays</i></td><td>38.26±01.29<sup>a</sup></td><td>07.65±00.59<sup>c</sup></td></tr><tr><td><i>Solanum lycopersicum</i> L</td><td>18.84±07.16<sup>d</sup></td><td>01.36±00.54<sup>d</sup></td></tr></tbody><thead><tr><th colspan="3">Compost_Biochar 2 (47.36-52.63) % based on <i>Prosopis juliflora_Eichhornia crassipes</i> on sandy clay soil T02 (95%-05%)</th></tr><tr><th>T<sub>2</sub> treatments (15 ton/ha)</th><th>Fresh weight (g)</th><th>Dry weight (g)</th></tr></thead><tbody><tr><td><i>Zea mays</i></td><td>39.71±01.16<sup>e</sup></td><td>09.18±01.81<sup>b</sup></td></tr><tr><td><i>Solanum lycopersicum</i> L</td><td>19.85±07.87<sup>e</sup></td><td>01.83±11.86<sup>a</sup></td></tr></tbody><thead><tr><th colspan="3">Compost_Biochar 3 (50-50) % based on <i>Prosopis juliflora_Eichhornia crassipes</i> on sandy clay soil T03 (95%-05%)</th></tr><tr><th>T<sub>3</sub> treatments (15 ton/ha)</th><th>Fresh weight (g)</th><th>Dry weight (g)</th></tr></thead><tbody><tr><td><i>Zea mays</i></td><td>39.49±01.22<sup>a</sup></td><td>08.65±01.43<sup>b</sup></td></tr><tr><td><i>Solanum lycopersicum</i> L</td><td>17.99±01.96<sup>e</sup></td><td>01.37±00.38<sup>c</sup></td></tr></tbody></table>

Furthermore, the greatest root length of *Solanum lycopersicum* L (19.85±07.87 cm) was recorded at 15 t/ha of Compost_Biochar 2 (47.36-52.63)% based on *Prosopis juliflora_Eichhornia crassipes* on sandy clay soil T02 (95%-05%) followed by the lowest root length (17.99±01.96 cm) recorded during treatment control at 15 t/ha Compost_Biochar 1 (64.28-35.71)% based on *Prosopis juliflora_Eichhornia crassipes* on sandy clay soil T01 (95%-05%), and was (Table 3). These results showed that there is a significant difference between different treatments and plant root length (P ≤ 0.04) and contrasts with the results obtained by Ali et al. (2023) which indicates that the greatest maize root length was recorded in 5 t/ha BC + NPS (39.8 cm) followed by 10 t/ha BC (37.2 cm), and the root length the lowest was recorded during treatment monitoring.

According to Ali et al. (2023), this can be attributed to the ability of biochar to improve soil properties, consistent with this study, not only a significant increase in root biomass (47%), but also in the number of root tips (64%) increased in a layer of char from a forest fire with buried larch twigs, birch twigs and dwarf bamboo shoots. in a dystric Cambisol (Makoto et al., 2010; Ali et al. 2023). Others observed that the number of asparagus storage roots also increased with the addition of coconut biochar to tropical soil (Matsubara et al., 2002; Ali et al., 2023). This could be due to the enhanced symbiotic associations of mycorrhizal fungi
(Makoto et al., 2010; Ali et al., 2023) and terrestrial plants. Demonstrations of positive response in plant growth and nutrient availability due to increased mycorrhizal colonization following Biochar additions to soils have been reported (Makoto et al., 2010).

## 5.2. Effect of Compost_Biochar on the height growth of crops.

The results recorded between weeks 2 and 8 after sowing allowed us to deduce the average maximum height of *Zea mays* (143.26±20.19 cm), which was recorded with 15 t/ha of Compost_Biochar 1 (64.28-35.71)% based on *Prosopis juliflora_Eichhornia crassipes* on T02 sandy clay soil (95%-05%) followed by the average minimum height of *Zea mays* (103.65 ±06.43 cm), which was recorded during the treatment with 15 t/ha of Compost_Biochar 3 (50-50)% based on *Prosopis juliflora_Eichhornia crassipes* on sandy clay soil T01 (95%-05%). Between weeks 2 and 8 after sowing, the growth percentage was 34.62±05.73% in height and 13.64±02.88% in stem volume of *Zea mays*. Furthermore, the maximum height of *Solanum lycopersicum* L (83.95±07.87 cm) was recorded at 15 t/ha of Compost_Biochar 2 (47.36-52.63)% based on *Prosopis juliflora_Eichhornia crassipes* on sandy clay soil T02 (95%-05%) followed by the minimum height of *Solanum lycopersicum* L (21.06±04.05 cm) recorded during the treatment at 15 t/ha Compost_Biochar 1 (64.28-35.71)% based on *Prosopis juliflora_Eichhornia crassipes* on sandy soil clayey T01 (95%-05%), and was (Table 3). These results recorded between weeks 1 and 8 after sowing allowed us to deduce the growth percentage was 38.77±02.93% in height and 10.37±01.43% in volume of the stem of *Solanum lycopersicum* L.

<table><caption>**Table 14:** Effect of treatment with Compost_Biochar (CB) based on *Prosopis juliflora_Eichhornia crassipes* on plant growth parameters.</caption><thead><tr><th colspan="5">Compost_Biochar 1 (64.28-35.71)% based on <i>Prosopis juliflora_Eichhornia crassipes</i> on sandy clay soil T01 (95%-05%)</th></tr><tr><th>T<sub>1</sub> treatments (15 ton/ha)</th><th>Maximum height (cm)</th><th>Minimum height (cm)</th><th>Maximum volume (cm<sup>3</sup>)</th><th>Minimum volume (cm<sup>3</sup>)</th></tr></thead><tbody><tr><td><i>Zea mays</i></td><td>143.26±20.19<sup>a</sup></td><td>107.56±09.05<sup>c</sup></td><td>07.84±00.77<sup>a</sup></td><td>07.16±00.93<sup>c</sup></td></tr><tr><td><i>Solanum lycopersicum</i> L</td><td>81.84 ±16.07<sup>d</sup></td><td>21.06±04.05<sup>d</sup></td><td>02.65 ±00.83<sup>d</sup></td><td>01.94±00.82<sup>d</sup></td></tr></tbody><thead><tr><th colspan="5">Compost_Biochar 2 (47.36-52.63)% based on <i>Prosopis juliflora_Eichhornia crassipes</i> on sandy clay soil T02 (95%-05%)</th></tr><tr><th>T<sub>2</sub> treatments (15 ton/ha)</th><th>Maximum height (cm)</th><th>Minimum height (cm)</th><th>Maximum volume (cm<sup>3</sup>)</th><th>Minimum volume (cm<sup>3</sup>)</th></tr></thead><tbody><tr><td><i>Zea mays</i></td><td>139.71±60.11<sup>e</sup></td><td>109.98±11.08<sup>b</sup></td><td>07.22±00.32<sup>a</sup></td><td>07.07±00.79<sup>c</sup></td></tr><tr><td><i>Solanum lycopersicum</i> L</td><td>83.95±07.87<sup>e</sup></td><td>23.01±01.68<sup>a</sup></td><td>03.84 ±00.16<sup>d</sup></td><td>01.02±00.45<sup>d</sup></td></tr></tbody><thead><tr><th colspan="5">Compost_Biochar 3 (50-50)% based on <i>Prosopis juliflora_Eichhornia crassipes</i> on sandy clay soil T03 (95%-05%)</th></tr><tr><th>T<sub>3</sub> treatments (15 ton/ha)</th><th>Maximum height (cm)</th><th>Minimum height (cm)</th><th>Maximum volume (cm<sup>3</sup>)</th><th>Minimum volume (cm<sup>3</sup>)</th></tr></thead><tbody><tr><td><i>Zea mays</i></td><td>140.99±10.22<sup>a</sup></td><td>103.65 ±06.43<sup>b</sup></td><td>08.26±00.12<sup>a</sup></td><td>07.56±00.95<sup>c</sup></td></tr><tr><td><i>Solanum lycopersicum</i> L</td><td>80.79±06.19<sup>e</sup></td><td>22.37 ±04.08<sup>c</sup></td><td>04.84 ±00.17<sup>d</sup></td><td>04.06±00.45<sup>d</sup></td></tr></tbody></table>
The maximum volume gain is 08.26±00.12 cm³ for *Zea mays* and 04.84 ±00.17 cm³ for *Solanum lycopersicum* L recorded with 15 t/ha of Compost_Biochar 3 (50-50)% based on *Prosopis juliflora_Eichhornia crassipes* on sandy clay soil T₀₂ (95%-05%), followed by the average minimum volume of *Zea mays* (07.07±00.79 cm³) and *Solanum lycopersicum* L (01.02±00.45 cm³), which was recorded during treatment with 15 t/ha of Compost_Biochar 2 (47.36-52.63)% based on *Prosopis juliflora_Eichhornia crassipes* on sandy clay soil T₀₁ (95%-05%). It is noted that growth in volume and height depends on several factors which are more or less controlled by the substrate supply of Compost_Biochar

Our results contrast with those obtained by Ali et al. (2023), which showed that the highest shoot growth was recorded with the treatment with NPS fertilizers (16.36, 27, 34.28, 45.18, 62.1, 81.2 and 102, 13 cm) between weeks 2 and 8 after planting, respectively, and the lowest was recorded in the control treatment after planting. Results also showed a significant difference in wheat plant height growth between treatments by measuring height every week after planting. The highest shoot growth was recorded in the 10 t/ha biochar treatment, while the lowest shoot growth was recorded in the control treatment. Hoshi, (2001) reported an increase of 20% in volume and 40% in height of tea trees after the addition of biochar. Idem, Zhang et al. (2013) also reported that net photosynthetic rates of rice in biochar treatments were higher than in control treatments.

**5.3. Effect of Compost_Biochar on the number of leaves.**

The results recorded between weeks 2 and 8 after sowing allowed us to deduce the average maximum number of leaves/Zea mays plant (21.87±02.26 leaves/Zea mays plant), which was recorded with 15 t/ha of Compost_Biochar 1 (64.28-35.71)% based on Prosopis juliflora_Eichhornia crassipes on sandy clay soil T₀₂ (95%-05%) followed by the average minimum leaf number/Zea mays plant (14.04±01.23 leaves /plant of Zea mays), which was recorded during the treatment with 15 t/ha of Compost_Biochar 3 (50-50)% based on Prosopis juliflora_Eichhornia crassipes on sandy clay soil T01 (95%-05%). Between weeks 2 and 8 after sowing, the maximum weight of 100 dry leaves of Zea mays was 245.82±12.44 gr while that of Solanum lycopersicum L is 21.19±02.27 gr obtained with 15 t/ha Compost_Biochar 2 (47.36 - 52.63)% based on Prosopis juliflora_Eichhornia crassipes on sandy clay soil T₀₂ (95%-05%).
<table><caption>**Table 15:** Effect of treatment with Compost_Biochar (CB) based on *Prosopis juliflora_Eichhornia crassipes* on the leaves during plant growth</caption><thead><tr><th colspan="5">Compost_Biochar 1 (64.28-35.71) % based on <i>Prosopis juliflora_Eichhornia crassipes</i> on sandy clay soil T01 (95%-05%)</th></tr><tr><th>Control treatments T01<br>(sand/clay) %</th><th>Maximum number of<br>leaves/plant</th><th>Minimum number of<br>leaves/plant</th><th>Weight of 100 dry<br>leaves (g)</th><th>CO2 sequestered by<br>leaves/m² (kg<br>CO2/m²/h)</th></tr></thead><tbody><tr><td><i>Zea mays</i></td><td>21.87±02.26</td><td>17.98±03.45</td><td>218.65±22.26</td><td>14.04±03.45</td></tr><tr><td><i>Solanum lycopersicum L</i></td><td>18.04±06.72</td><td>03.48±00.76</td><td>19.79±01.69<sup>c</sup></td><td>07.23±00.18<sup>c</sup></td></tr></tbody><thead><tr><th colspan="5">Compost_Biochar 2 (47.36-52.63) % based on <i>Prosopis juliflora_Eichhornia crassipes</i> on sandy clay soil T02 (95%-05%)</th></tr><tr><th>Control treatments T02<br>(Biochar/Soil) %</th><th>Maximum number of<br>leaves/plant</th><th>Minimum number of<br>leaves/plant</th><th>Weight of 100 dry<br>leaves (g)</th><th>CO2 sequestered by<br>leaves/m² (kg<br>CO2/m²/h)</th></tr></thead><tbody><tr><td><i>Zea mays</i></td><td>18.75±06.26</td><td>14.73±03.75</td><td>245.82±12.44</td><td>17.55±04.46</td></tr><tr><td><i>Solanum lycopersicum L</i></td><td>19.01±06.72</td><td>18.09±01.12</td><td>21.19±02.27<sup>a</sup></td><td>08.37±00.85<sup>c</sup></td></tr></tbody><thead><tr><th colspan="5">Compost_Biochar 3 (50-50) % based on <i>Prosopis juliflora_Eichhornia crassipes</i> on sandy clay soil T03 (95%-05%)</th></tr><tr><th>Control treatments T03<br>(Compost/Soil) %</th><th>Maximum number of<br>leaves/plant</th><th>Minimum number of<br>leaves/plant</th><th>Weight of 100 dry<br>leaves (g)</th><th>CO2 sequestered by<br>leaves/m² (kg<br>CO2/m²/h)</th></tr></thead><tbody><tr><td><i>Zea mays</i></td><td>19.87±02.66</td><td>14.04±01.23</td><td>225.68±09.92</td><td>15.21±05.88</td></tr><tr><td><i>Solanum lycopersicum L</i></td><td>18.94±02.03</td><td>15.47±01.38</td><td>20.11±01.93<sup>a</sup></td><td>08.54±00.67<sup>c</sup></td></tr></tbody></table>

Furthermore, the CO₂ sequestered at the maximum by the leaves of *Zea mays* /m² is 17.55±04.46 kg CO₂/m²/h on substrate with Compost_Biochar 2 (47.36-52.63) %, while the CO₂ sequestered at the minimum by these *Zea mays* leaves /m² is 14.04±03.45 kg CO₂/m²/h on Compost_Biochar 1 (64.28-35.71) % substrate. The CO₂ sequestered at the maximum by the leaves of *Solanum lycopersicum* L/m² is 08.54±00.67 kg CO₂/m²/h on Compost_Biochar 3 (50-50) % substrate, while the CO₂ sequestered at the minimum by these leaves of *Solanum lycopersicum* L/m² is 07.23±00.18 kg CO₂/m²/h on Compost_Biochar 1 (64.28-35.71) % substrate based on *Prosopis juliflora_Eichhornia crassipes* on sandy clay soil T01 (95%-05%).

Our results contrast with those obtained by Ali et al. (2023), which shows that the highest number of plant leaves was recorded in the treatment 10 t/ha + NPS fertilizer followed by 10 t/ha 8 weeks after planting and the lowest number of leaves was recorded in the control treatment. The application of biochar as a corn seed treatment significantly (P ≤ 0.05) affected the leaf number of corn plants (Ali et al., 2023). Corn plants treated with 10 t/ha of BC and NPS fertilizer showed moderately better performance (14.05 leaves/plant) than any other treatment. The average number of leaves of untreated corn plants (controls) was 12.7 leaves/plant (Ali et al., 2023).

### 5.4. Effect of Compost_Biochar on plant productivity.

The results recorded between weeks 2 and 8 after sowing allowed us to deduce the average maximum number of ears developed per m²/week of *Zea mays* (19.87±02.66 ears developed per m²/week), which was recorded with 15 t/ha of Compost_Biochar 3 (50-50)% based on *Prosopis juliflora_Eichhornia crassipes* on
sandy clay soil T₀₂ (95%-05%) followed by a maximum of 80.41±02.39 fruits of *Solanum lycopersicum* L developed per m²/week recorded during treatment with 15 t/ha of Compost_Biochar 3 (50-50)% based on *Prosopis juliflora_Eichhornia crassipes* on sandy clay soil T₀₁ (95%-05%).

At the time of harvest, a maximum of 67.58±01.23 total ears/m² of *Zea mays* was recorded while that of *Solanum lycopersicum* L was 85.47±01.38 total fruits/m² obtained with 15 t/ha Compost_Biochar 2 (47.36-52.63)% based on *Prosopis juliflora_Eichhornia crassipes* on T₀₂ sandy clay soil (95%-05%). The maximum weight of 100 ears of *Zea mays* is 38.65±02.33 gr while the maximum weight of 100 fruits of *Solanum lycopersicum* L is 156.07±02.48 gr.

<table><caption>**Table 16:** Effect of treatment with Compost_Biochar (CB) based on *Prosopis juliflora_Eichhornia crassipes* on the number of ears (or fruits) developed during plant growth</caption><thead><tr><th colspan="5">Compost_Biochar 1 (64.28-35.71)% based on <i>Prosopis juliflora_Eichhornia crassipes</i> on sandy clay soil T01 (95%-05%)</th></tr><tr><th>Control treatments T01<br>(sand/clay) %</th><th>Number of ears (or fruit)<br>developed per m²/week</th><th>Number of total<br>ears (or fruit) /m²</th><th>Weight of 100 ears (or<br>fruits) (g)</th><th>CO₂ sequestered per plant/m²<br>(kg CO₂/m²/h)</th></tr></thead><tbody><tr><td><i>Zea mays</i></td><td>16,07±02,06</td><td>32.31±00,45</td><td>31,93±03,45</td><td>982.76×10<sup>-3</sup>±04.96×10<sup>-3</sup></td></tr><tr><td><i>Solanum lycopersicum</i> L</td><td>58,41±06,72</td><td>83,04±00,24</td><td>156,07±02,48</td><td>51.67×10<sup>-3</sup>±02.48×10<sup>-3</sup></td></tr></tbody></table><table><thead><tr><th colspan="5">Compost_Biochar 3 (50-50)% based on <i>Prosopis juliflora_Eichhornia crassipes</i> on sandy clay soil T03 (95%-05%)</th></tr><tr><th>Control treatments T02<br>(Biochar/Soil) %</th><th>Number of ears (or fruit)<br>developed per m²/week</th><th>Number of total<br>ears (or fruit) /m²</th><th>Weight of 100 ears (or<br>fruits) (g)</th><th>CO₂ sequestered per plant/m²<br>(kg CO₂/m²/h)</th></tr></thead><tbody><tr><td><i>Zea mays</i></td><td>17,75±06,26</td><td>64,73±03,75</td><td>38,65±02,33</td><td>992.87×10<sup>-3</sup>±02.49×10<sup>-3</sup></td></tr><tr><td><i>Solanum lycopersicum</i> L</td><td>78,01±06,72</td><td>85,09±01,12</td><td>154,63±03,55</td><td>56.17×10<sup>-3</sup>±00.25×10<sup>-3</sup></td></tr></tbody></table><table><thead><tr><th colspan="5">Compost_Biochar 3 (50-50)% à base du <i>Prosopis juliflora_Eichhornia crassipes</i> sur Sol sableux argileux T03 (95%-05%)</th></tr><tr><th>Control treatments T03<br>(Compost/Soil) %</th><th>Number of ears (or fruit)<br>developed per m²/week</th><th>Number of total<br>ears (or fruit) /m²</th><th>Weight of 100 ears (or<br>fruits) (g)</th><th>CO₂ sequestered per plant/m²<br>(kg CO₂/m²/h)</th></tr></thead><tbody><tr><td><i>Zea mays</i></td><td>19,87±02,66</td><td>67,58±01,23</td><td>35.44±02,76</td><td>994.09×10<sup>-3</sup>±02.55×10<sup>-3</sup></td></tr><tr><td><i>Solanum lycopersicum</i> L</td><td>80,41±02,39</td><td>85,47±01,38</td><td>155.49±02.35</td><td>52.39×10<sup>-3</sup>±00.44×10<sup>-3</sup></td></tr></tbody></table>

However, *Zea mays* sequestered a maximum of (994.09±02.55) × 10⁻³ kg CO₂/m²/h with an amendment to the substrate with Compost_Biochar 3 (50-50) % based on *Prosopis juliflora_Eichhornia crassipes*, while *Solanum lycopersicum* L a sequestered to the maximum (56.17±00.25) × 10⁻³ kg CO₂/m²/h with an amendment to the substrate of Compost_Biochar 2 (47.36-52.63) % based on *Prosopis juliflora_Eichhornia crassipes*.

**5.5. Effect of Compost_Biochar on supplied water consumption and plant productivity.**

The highest seed number yield in *Zea mays* is 912.87±60.26 seeds/plant which was recorded with 15 t/ha of Compost_Biochar 3 (50-50)% based on *Prosopis juliflora_Eichhornia crassipes* on sandy clay soil T₀₂ (95%-05%) followed by a maximum of 15.76±03.88 fruits of *Solanum lycopersicum* L developed and recorded
during treatment with 15 t/ha of Compost_Biochar 2 (47.36-52.63)% based of *Prosopis juliflora* Eichhornia crassipes on sandy clay soil T01 (95%-05%).

<table><caption>**Table 17:** Effect of treatment with Compost_Biochar (CB) based on *Prosopis juliflora* Eichhornia crassipes on seed number yield, plant productivity and water consumption provided during plant growth</caption><thead><tr><th colspan="6">Compost_Biochar 1 (64.28-35.71)% based on <i>Prosopis juliflora</i> Eichhornia crassipes on sandy clay soil T01 (95%-05%)</th></tr><tr><th>Control treatments T01<br>(sand/clay) %</th><th>Yield in number of<br>seeds (or<br>fruits)/plant</th><th>Average size of<br>seeds/fruits<br>harvested (mm)</th><th>Production<br>(kg/m²<br>harvested /<br>week)</th><th>Consumption of<br>water supplied<br>(liters / plant /<br>day)</th><th>% leaching of<br>the substrate</th></tr></thead><tbody><tr><td><i>Zea mays</i></td><td>868.71±02.66</td><td>01.32±00.04</td><td>04.35±00.09</td><td>02.01±00.02</td><td>01.33±00.58<sup>c</sup></td></tr><tr><td><i>Solanum lycopersicum</i> L</td><td>14.08±06.72</td><td>00.05±00.06</td><td>02.15±00.03</td><td>02.01±00.04</td><td>02.53±00.67<sup>c</sup></td></tr></tbody><thead><tr><th colspan="6">Compost_Biochar 2 (47.36-52.63)% based on <i>Prosopis juliflora</i> Eichhornia crassipes on sandy clay soil T02 (95%-05%)</th></tr><tr><th>Control treatments T02<br>(Biochar/Soil) %</th><th>Yield in number of<br>seeds (or<br>fruits)/plant</th><th>Average size of<br>seeds/fruits<br>harvested (mm)</th><th>Production<br>(kg/m²<br>harvested /<br>week)</th><th>Consumption of<br>water supplied<br>(liters / plant /<br>day)</th><th>% leaching of<br>the substrate</th></tr></thead><tbody><tr><td><i>Zea mays</i></td><td>881.36±62.54</td><td>01.55±00.55</td><td>04.67±00.02</td><td>02.01±00.03</td><td>01.65±00.03<sup>c</sup></td></tr><tr><td><i>Solanum lycopersicum</i> L</td><td>15.76±03.88</td><td>00.07±00.06</td><td>02.89±00.56</td><td>02.01±00.07</td><td>02.98±00.97<sup>c</sup></td></tr></tbody><thead><tr><th colspan="6">Compost_Biochar 3 (50-50)% based on <i>Prosopis juliflora</i> Eichhornia crassipes on sandy clay soil T03 (95%-05%)</th></tr><tr><th>Control treatments T03<br>(Compost/Soil) %</th><th>Yield in number of<br>seeds (or<br>fruits)/plant</th><th>Average size of<br>seeds/fruits<br>harvested (mm)</th><th>Production<br>(kg/m²<br>harvested /<br>week)</th><th>Consumption of<br>water supplied<br>(liters / plant /<br>day)</th><th>% leaching of<br>the substrate</th></tr></thead><tbody><tr><td><i>Zea mays</i></td><td>912.87±60.26</td><td>01.67±01.58</td><td>04.98±00.23</td><td>02.02±00.09</td><td>01.21±00.08</td></tr><tr><td><i>Solanum lycopersicum</i> L</td><td>14.41±02.39</td><td>00.06±00.08</td><td>02.47±00.38</td><td>02.11±00.03<sup>a</sup></td><td>02.54±00.67<sup>c</sup></td></tr></tbody></table>

The seeds of *Zea mays* have maximum average sizes of 01.67±01.58 mm with Compost_Biochar 3 (50-50)% while the seeds of *Solanum lycopersicum* L have maximum average sizes of 00.07±00.06 mm with Compost_Biochar 2 (47.36-52.63)%.

The maximum water consumption of 02.02±00.09 liters/Zea mays/day on Compost_Biochar 3 (50-50)% substrate, made it possible to obtain a maximum production of 04.98±00.23 kg/m² of seeds harvested/week and maximum leaching (of substrate based on Compost_Biochar 2 (47.36-52.63)% of 01.65±00.03% while the maximum water consumption of 02.11±00.03 liters/Solanum lycopersicum L/day on substrate of Compost_Biochar 3 (50-50)%, made it possible to obtain a maximum production of 02.89±00.56 kg/m² of Solanum lycopersicum L seeds harvested/week and maximum leaching (of substrate based on Compost_Biochar 2 (47.36-52.63)% of 02.98±00.97%).

## CONCLUSIONS

Application of Compost_Biochar based on *Prosopis juliflora* Eichhornia crassipes on Sandy clay soil T03 (95%-05%) in the field experiment showed significant effects
on seed germination and growth parameters of *Solanum lycopersicum* L and of *Zea mays* compared to control sites on sandy clay soil, on Compost substrate and on Biochar substrate. The results showed a significant increase in seed germination percentage as we applied more of 15 t/ha of Compost_Biochar 2 (47.36-52.63) % based on *Prosopis juliflora_Eichhornia crassipes* to agricultural land abandoned due to its degradation due to aridity and silting. The study also showed an increase in crop biomass or yield performance using Biochar (100%) based on *Prosopis juliflora_Eichhornia crassipes* alone and/or in combination with Compost based on *Prosopis juliflora_Eichhornia crassipes* on sandy soil. clayey T03 (95%-05%). The application of this Compost_Biochar based on *Prosopis juliflora_Eichhornia crassipes* on sandy clay soil T03 (95%-05%) also increases the growth of shoots and roots of crops, then improves crop yield by improving the physicochemical properties and biological soils, which is probably the reason why Compost_Biochar based on *Prosopis juliflora_Eichhornia crassipes* on sandy clay soil T03 (95%-05%) could contribute to plant productivity. In view of the percentage of leaching obtained due to runoff water, we conclude that, even in conditions of high precipitation (floods or irregular rainfall), leached soils of highlands for example could be sustainably improved by an amendment to Compost_Biochar based on *Prosopis juliflora_Eichhornia crassipes*. The application of Compost_Biochar based on *Prosopis juliflora_Eichhornia crassipes* alone could improve the dry matter yield (crop biomass) equivalent to that resulting from the application of Biochar based on *Prosopis juliflora_Eichhornia crassipes*.

Based on the results of the study, it can be recommended that the application of Compost_Biochar based on *Prosopis juliflora_Eichhornia crassipes* on a sandy clay soil T03 (95%-05%) with a view to restoring degraded agricultural soil and improve seed germination potential, crop growth performance and dry matter yield without chemical fertilizer. In addition, experiments have shown that it is now possible to manage the biodegradation of Sahelian arid zones by using invasive plants in agro-farming environments such as Compost, Biochar or Compost_Biochar for agricultural production in the highlands. This discovery makes it possible to valorize plant resources which were until now neglected and considered harmful.

This also implies that an optimal quantity of Compost_Biochar based on *Prosopis juliflora_Eichhornia crassipes* on a sandy clay soil T03 (95%-05%) must be used within the framework of regional and national projects for the sustainable restoration of degraded agricultural soils and improve their potential. In particular, when other chemical amendments become expensive and cause ecological damage, it could be substituted in parallel with Compost_Biochar based on *Prosopis juliflora_Eichhornia crassipes* on a sandy clay soil T03 (95%-05%)
in order to restore the long-term soil fertility and improve soil biodiversity. However, other experiences with the application of Compost_Biochar based on improved *Prosopis juliflora* *Eichhornia crassipes* could lead to organic soil amendments, capable of destroying agricultural pests and certain plant diseases. Certain physical and chemical analyzes of the soil should be carried out before it can be extended on a large scale.

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## EXERCISES AND CORRECTIONS ON THE EFFECT OF THE BIOCHAR-COMPOST MIXTURE BASED ON DEAD BIOMASS OF PROSOPIS JULIFLORA AND EICHHORNIA CRASSIPES ON THE PRODUCTIVITY AND BIODIVERSITY OF ARID SANDY SOILS IN THE SAHEL ZONE

Here is a series of exercises accompanied by their corrections on the theme of the effect of the biochar-compost mixture based on dead biomass of Prosopis juliflora and Eichhornia crassipes on the productivity and biodiversity of arid sandy soils in the Sahelian zone.

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### Exercise 1: Understanding Basic Materials

**Objective:** Identify the characteristics of dead biomasses of Prosopis juliflora and Eichhornia crassipes used for the production of biochar and compost.

**Instructions:**

1. Describe the main characteristics of *Prosopis juliflora* and *Eichhornia crassipes* as biomasses for biochar and compost production.
2. Explain why these two species are considered attractive raw materials for the amendment of arid sandy soils.

**Correction:**

**1. Main Features:**

- *Prosopis juliflora*: Drought-resistant, carbon-rich, invasive tree used for biochar production due to its high lignin content.

- *Eichhornia crassipes*: Invasive aquatic plant with rapid growth, rich in nutrients, used for compost production due to its ability to provide organic matter and nutrients to soils.

**2. Interest in soil amendment:**

- *Prosopis juliflora*: Its carbon-rich biomass is ideal for creating biochar capable of improving water retention and the structure of sandy soils.

- *Eichhornia crassipes*: Its compost enriches the soil with essential nutrients, which is crucial for improving the fertility of soils poor in organic matter in the Sahel zone.

**Exercise 2: Effects of Mixed Biochar-Compost on Soil Productivity**

**Objective:** Analyze the impact of the biochar-compost mixture on the productivity of arid sandy soils.

**Instructions:**

1. Explain how biochar and compost influence soil structure and nutrient availability, respectively.

2. Compare the effects on soil productivity of an application of biochar alone, compost alone, and the biochar-compost mixture.

**Correction:**

**1. Influence on the structure and availability of nutrients:**

- **Biochar:** Improves soil structure by increasing water retention, aeration, and cation exchange capacity, which promotes microbial activity.

- **Compost:** Enriches the soil with nutrients such as nitrogen, phosphorus and potassium, which stimulates plant growth.

**2. Comparison of effects on productivity:**