Understanding nutrient imbalances in maize (Zea mays L.) using the diagnosis and recommendation integrated system (DRIS) approach in the Maize belt of Nigeria.

Low nutrient use efficiency in maize as a result of imbalanced nutrition has been reported to drastically reduce yield. We implemented a nutrient omission experiment to assess the effect of nutrient application on maize yield and nutritional balance. Maize ear leaves were analyzed for nutrients, to identify nutrient balance status using the Diagnostic and Recommendation Integrated System (DRIS) approach. Results indicated that omission of N or P resulted in highly imbalanced DRIS indices respectively, and significantly lower grain yield. A strong inverse relationship between K ear leaf content with DRIS index suggests that K application negatively increases K imbalance in many situations. Imbalances of Mg, Ca and Cu were more associated with higher yielding treatments. A Which-Won-Where result show that nutrient imbalances in the diagnosis were systematically frequent when N was omitted. All the diagnosed nutrients were imbalanced even under the highest yielding NPKZn treatment; indicating further opportunity for yield increase with more balanced nutrition. Balanced nutrition of maize in the maize belt of Nigeria should target application of varying rates of N, P, K, Mg, S and Zn, depending on the soil conditions. But, because of complexities of nutrient interactions during uptake, it is hardly possible to realize a balanced nutrition. However, differentiating the application of antagonistic nutrients into foliar or soil-based methods is recommended for a more balanced maize nutrition.

Assessment of the Genetic Structure and Diversity of Soybean (Glycine max L.) Germplasm Using Diversity Array Technology and Single Nucleotide Polymorphism Markers.

Knowledge of the genetic structure and diversity of germplasm collections is crucial for sustainable genetic improvement through hybridization programs and rapid adaptation to changing breeding objectives. The objective of this study was to determine the genetic diversity and population structure of 281 International Institute of Tropical Agriculture (IITA) soybean accessions using diversity array technology (DArT) and single nucleotide polymorphism (SNP) markers for the efficient utilization of these accessions. From the results, the SNP and DArT markers were well distributed across the 20 soybean chromosomes. The cluster and principal component analyses revealed the genetic diversity among the 281 accessions by grouping them into two stratifications, a grouping that was also evident from the population structure analysis, which divided the 281 accessions into two distinct groups. The analysis of molecular variance revealed that 97% and 98% of the genetic variances using SNP and DArT markers, respectively, were within the population. Genetic diversity indices such as Shannon's diversity index, diversity and unbiased diversity revealed the diversity among the different populations of the soybean accessions. The SNP and DArT markers used provided similar information on the structure, diversity and polymorphism of the accessions, which indicates the applicability of the DArT marker in genetic diversity studies. Our study provides information about the genetic structure and diversity of the IITA soybean accessions that will allow for the efficient utilization of these accessions in soybean improvement programs, especially in Africa.

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 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; 32 and 79 for N, 164 and 528 for P and 24 and 136 for K in the SS zone; and 35 and 79 for N, 199 and 528 for P and 24 and 124 for K when the data of the two zones were combined. There was a close agreement between observed and parameterized QUEFTS predicted yields in each of the agro-ecological zone (R2 = 0.69 for the NGS and 0.75 for the SS). Although with a slight reduction in the prediction power, a good fit between the observed and model predicted grain yield was also detected when the data for the two agro-ecological zones were combined (R2 = 0.67). Therefore, across the two agro-ecological zones, 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 t ha-1), the model showed above-ground balanced nutrient uptake of 20.7, 3.4 and 27.1 kg N, P, and K, respectively, per one tonne of maize grain. These results suggest an average NPK ratio in the plant dry matter of about 6.1:1:7.9. We concluded that the QUEFTS model can be widely used for balanced nutrient requirement estimations and development of site-specific fertilizer recommendations for maize intensification in the Northern Nigerian Savanna.