An overview of jatropha (Jatropha curcas) pests, diseases and management in North-Western Nigeria

The growing and management of Jatropha curcas, either on private, public or community land is poorly documented and there is little field experience that is being shared especially in North western Nigeria where it is still grown wild. The few growers are unable to achieve the optimum economic benefit from the plants. However, the recent importance attached to Jatropha in the Nigerian Savanna agro-ecology have revealed that, the crop is subject to attack by a diversity of arthropod pests’ species and diseases, some of which may warrant control measures taken against them. Diseases caused by a number of plant pathogenic (disease-causing) organisms such as fungi, bacteria, virus etc often have a significant economic impact on yield and quality of Jatropha plant, hence the need for adopting control measures become imperative in order to be managed for successful production. Therefore, there is need to conduct a research on common diseases affecting the growth and development of J. curcas and possible management practices in north western Nigeria.

DSSAT-CSM Soil Module: Modeling Topsoil Water Holding Capacity in the two Dry Savanna Zones of Kano State, Nigeria.

The objective of this study was to test the efficiency of the Hydraulic Pedotrans- fer Functions (PTFs) employed in the Decision Support System for Agrotechnol- ogy Transfer – Crop Simulation Model (DSSAT-CSM) in modeling topsoil WHC in Northern Guinea Savanna (NGS) and Sudan Savanna (SS) of Kano State in Nigeria. Coefficient of determination (R2), Root Mean Squared Error (RMSE), and Index of Agreement (d-index) were the three statistical methods used to test the fitness between predicted, and laboratory observed WHC of dis- turbed, auger sampled topsoil. Findings of the study established that the PTFs fitted in the algorithm of DSSAT-CSM soil water sub module made a significant topsoil WHC estimation in NGS with statistics R² = 0.352, RMSE = 0.03, and d- Index = 0.71. However, the model did not estimate the WHC validly in Sudan Savanna, with insignificant statistics of R² = 0.031, RMSE of 0.10, and 0.44 as the index of agreement. The conclusion drawn was that DSSAT made fair and poor predictions of topsoil WHC in NGS and SS soils respectively, irrespective of texture and other intrinsic properties. Based on the findings above, we recom- mend the development of local PTFs alternatives to be used with DSSAT’s algo- rithm for Nigerian Savanna soil

Balanced nutrient requirements for maize in the Northern Nigerian Savanna: Parameterization and validation of QUEFTS model

Establishing balanced nutrient requirements for maize (Zea mays L.) in the Northern Nigerian Savanna is paramount to develop site-specific fertilizer recommendations to increase maize yield, profits of farmers and avoid negative environmental impacts of fertilizer use. The model QUEFTS (QUantitative Evaluation of Fertility of Tropical Soils) was used to estimate balanced nitrogen (N), phosphorus (P) and potassium (K) requirements for maize production in the Northern Nigerian Savanna. Data from on-farm nutrient omission trials conducted in 2015 and 2016 rainy seasons in two agro-ecological zones in the Northern Nigerian Savanna (i.e. Northern Guinea Savanna “NGS” and Sudan Savanna “SS”) were used to parameterize and validate the QUEFTS model. The relations between indigenous soil N, P, and K supply and soil properties were not well described with the QUEFTS default equations and consequently new and better fitting equations were derived. The average fertilizer recovery fractions of N, P and K in the NGS were generally comparable with the QUEFTS default values, but lower recovery fractions of these nutrients were observed in the SS. The parameters of maximum accumulation (a) and dilution (d) in kg grain per kg nutrient for the QUEFTS model obtained were respectively 35 and 79 for N, 200 and 527 for P and 25 and 117 for K in the NGS zone and 32 and 79 for N, 164 and 528 for P and 24 and 136 for K in the SS zone. The model predicted a linear relationship between grain yield and above-ground nutrient uptake until yield reached about 50 to 60% of the yield potential. When the yield target reached 60% of the potential yield (i.e. 6.0 tonnes per hectare), the model showed above-ground nutrient uptake of 19.4, 3.3 and 23.0 kg N, P, and K, respectively, per one tonne of maize grain in the NGS, and 17.3, 5.3 and 26.2 kg N, P and K, respectively, per one tonne of maize grain in the SS. These results suggest an average NPK ratio in the plant dry matter of about 5.9:1:7.0 for maize in the NGS and 3.3:1:4.9 for maize in the SS. There was a close agreement between observed and parameterized QUEFTS predicted yields across the two agro-ecological zones (R2 = 0.70 for the NGS and 0.86 for the SS). We concluded that the QUEFTS model can be used for balanced nutrient requirement estimations and development of site-specific fertilizer recommendations for maize intensification in the Northern Nigerian Savanna.

Symbiotic Effectiveness of Rhizobia Strains Isolated from Nigerian Savanna

Laboratory and screenhouse experiment were conducted to assess the symbiotic effectiveness (SE) of rhizobia isolated from southern Guinea savanna, northern Guinea savanna and Sudan savanna of Nigeria and response of promiscuous soybean varieties, TGx1448-2E, TGx1835-10E and TGx1955-10E to inoculation with ten indigenous rhizobia isolates. The soybean varieties were grown on sterilized sand at the screenhouse of the Department of Soil Science and Land Management, Federal University of Technology Minna and watered using Sandsman’s nutrient solution. The treatments were un-inoculated control, mineral nitrogen (urea) and ten rhizobia isolates arranged on a Completely Randomized Design (CRD) and replicated three times. The rhizobia isolates were Sg4, Sg6-3, Gw5, Gw3-2, Bg3, Bg1-4, Sk2-3, Am2, Am6-3 and Kr5-5 isolated from Sabon-gida, Gwada, Birnin-gwari, Shika, Amawa and Karaye sites of Nigerian savanna. The results obtained were subjected to Analysis of Variance using statistical analysis system (SAS 2008) computer software. The treatments mean was separated using Least Significant Different (LSD) at 5% probability. Nodulation and biomass yield of the varieties were assessed at six weeks after planting. Nodules were only produced in inoculated plants, SE was calculated. The result obtained showed that nodule dry weight, SE and shoot dry weight were significantly affected by the interaction between inoculation and promiscuous soybean varieties. Generally, inoculated plants gave higher shoot biomass gain than the un-inoculated control but lower than those treated with urea. The difference between those inoculated and those treated with urea was associated to environmental specificities and higher temperature during the period of the experiment. The SE was highest in northern Guinea savanna isolate reaching 67% and lowest in southern Guinea savanna isolate Sg6-3 recorded 53%. The result showed an SE of less than 100% in all the isolates which implies that the indigenous rhizobia isolates were not superior to the mineral nitrogen.