Assessment of millet-groundnut intercropping systems efficiency in Jigawa and Kano states.

Open access Journal; Published online: 30 June 2016In this study, an intercropping experiment consisting of millet and groundnut was established at Dutse (Jigawa) and Minjibir (Kano) to compare the efficiencies of intercropping systems. Two intercropping systems (2:2 and 2:4; millet to groundnut ratio) were studied in terms of aggressivity, competitive ratio, actual yield loss and intercropping advantage. The treatments were studied under split-split plot design that was replicated four times. The results shows that aggressivity was determined by crop arrangement not by component crop and that the rate of increase in millet aggressivity was proportional to rate at which groundnut aggressivity was reduced. Intercropping advantage was higher and positive under 2:4 system at both trial locations; this implies that the system have a better economic feasibility. Under the same system at Dutse, competitive ratio was higher (1.18); indicating that the crops have a fairly comparative ability for resources competition, in contrast, the reverse was the case at Dutse 2:2 with higher competitive ration difference value of 1.05 compared to 0.69 at 2:4

Performance of groundnut genotypes under millet based intercropping systems in Sudan Savanna of Nigeria

Open access JournalSpatial arrangement of crops is critical in determining the growth and yield of lower crops in intercropping. The productivity of two spatial arrangements of pearl millet-groundnut intercrops was studied in the Sudan savanna of Nigeria during 2014 rainy season at Wasai (5ˈN, 08o62ˈE) in Minjibir of Kano state, and Rahama (11o40ˈN, 09o20ˈE) in Dutse of Jigawa state. The treatments were two millet varieties (Dankaranjo and SuperSosat), two intercropping systems (2:2 and 2:4; reflecting millet to groundnut row) and four groundnut genotypes (SAMNUT 21, SAMNUT 22, SAMNUT 23 and SAMNUT 24). The experiment was laid out in split-split plot design with four replications. Among the groundnut genotypes, pod yield was greater at 2:4 system at Minjibir, while SAMNUT 23 and SAMNUT 24 were significantly (P<0.05) better than SAMNUT 21 and SAMNUT 22, SAMNUT 21 was best in terms of pod yield (480 Kg ha-1) at Dutse followed by SAMNUT 22 and SAMNUT 23 and least was SAMNUT 24 (293 Kg ha-1). Higher haulm yields were produced by SAMNUT 21 and SAMNUT 22 at both locations followed by SAMNUT 23 and SAMNUT 24 which had similar haulm yields at Minjibir

Implication of blanket NPK application on nutrient balance of maize based on soil and tissue diagnosis approaches in the savannas of northern Nigeria

Open Access JournalImproper nutrient management reduces the yield and affects the nutrient status of crops. This study aimed to diagnose the nutrients limitation in maize. A three-year multi-location (348 sites) nutrient experiments were conducted in randomized block design to analyse nutrients limitation for maize production under conventional fertilizer recommendation system in Nigeria using DRIS, and to identify soil factors that influence DRIS indices using random forest model. DRIS indices for nutrients were calculated from the results of ear leaf samples collected from the experimental plots. The DRIS indices were summed, and used to cluster plots using k-means cluster algorithm. The results show large differences in average yield between the clusters. The clusters also differed based on frequency with which nutrients are most limiting. B was the most limiting in cluster one and three, Mn in cluster two and K in cluster four. Random forest results show that soil pH, B and Mg had the largest influence on DRIS indices in cluster one. DRIS indices were most influenced by soil N and B in cluster two. To a lesser extent, the soil Fe, K, Mg and S contents also influenced DRIS indices in cluster two. Soil K, B and Zn were the most significant factors influencing the DRIS indices in cluster four. Bulk Density, Fe, Na, ECEC, and organic carbon had a moderate influence on the indices in this cluster. Nutrient limitation in plants can be diagnose using the DRIS. Soil properties have a definite influence on maize nutrient status

Maize yield as affected by the interaction of fertilizer nitrogen and phosphorus in the Guinea savanna of Nigeria

Open Access Article; Published online: 14 Nov 2022The soils of the Nigeria savannas are particularly low in nitrogen (N) and phosphorus (P) and negatively affects maize productivity. The main objective of the study was to evaluate the interactive effect of N and P fertilizers on maize growth, grain yield, nitrogen uptake and N use efficiency. Field experiments were conducted during the 2015 and 2016 cropping seasons at Iburu in southern Guinea and Zaria in northern Guinea savanna zones of Nigeria. The treatments consisted of three levels of nitrogen (0, 60, and 120 kg N ha−1) and three levels of phosphorus (0, 13, and 26 kg P ha−1). The experimental design consisted of three replications in a split-plot design, with N as the main plot and P as the subplot. Our results show that the response of maize to N depends on the application of P. Higher yields were obtained with the combined application of 120 kg N ha−1 and 26 kg P ha−1 in both locations. With no P applied, plant N uptake (PNU) was greater at N rate of 120 kg ha−1 at Iburu while in Zaria, it increases with increase in N from 0 to 60 kg ha−1. When P was applied at 13 kg ha−1, the PNU increased by 52 and 66% at Iburu while in Zaria the increases were 51 and 57% each with N application of 60 and 120 kg ha−1, respectively, compared with zero N rate. The values for N recovery efficiency (NRE) and agronomic efficiency (AE) were lower for N rate of 120 than for 60 kg ha−1 irrespective of P application rate at both locations. The N utilization efficiency (NUTE) however was higher at 120 N kg ha−1 under 26 kg P ha−1across locations. It can be concluded from these results that in low fertile soils environments such as the Nigeria savannas, N fertilizer should be applied along with P fertilizer for optimum growth, grain yield and nitrogen use efficiency of maize

Breeding cowpea for adaptation to intercropping for sustainable intensification in the Guinea Savannas of Nigeria

Open Access Article; Published online: 24 May 2023Cowpea is a multifaceted crop; however, considerable challenges affect the production of this crop despite its comparatively better adaptation to harsh environments. Most smallholder farmers in West Africa cultivate this crop in intercropping systems where its low plant population does not allow the full expression of the cultivars’ yield potential. This is because most varieties currently grown in intercrop have been developed in and for monocropping, although some breeding programs recently have focused on intercrop systems. This study, therefore, aimed to evaluate the performance of some newly developed cowpea breeding lines for adaptation to intercropping systems. Firstly, an on-station field experiment was conducted in 2018. The selected promising lines and a standard check were evaluated in three locations in an intercropping system and on-farm trials. Significant differences were observed among the cowpea genotypes for all the traits measured. Two improved lines, UAM14-122-17-7 and UAM14-123-18-3, had superior grain and fodder yields under sole and intercropping systems and in different agroecological systems, revealing their adaptability. Based on our findings, UAM14-122-17-7 and UAM14-123-18-3 are recommended for a cereal-cowpea mixture because they are adapted to intercropping and produce high-grain yield under intercrop and sole-cropping systems

Simulating potential yield of rainfed soybean in northeast Nigeria

Open Access Article; Published online: 07 Nov 2022We used the CROPGRO-Soybean model to simulate the production potential of rainfed soybean in northeast Nigeria. Data from ten soybean experiments conducted under optimal conditions in 2016–2018 at Kano and Dambatta in the Sudan savanna (SS) agroecological zone were used to determine the cultivar coefficients and calibrate the model for the varieties TGX 1448–2E and TGX1951–3 F. The model was evaluated with data from four phosphorous response trials conducted at Zaria and Doguwa in the northern Guinea savanna (GS) of Nigeria between 2016 and 2018. Results show that the CROPGRO-Soybean model was able to accurately simulate soybean growth and grain yield with low RMSE and high d-index values. Consequently, the model was used to investigate the rainfed yield potential of the two varieties in 24 sites in northeast Nigeria under different sowing windows using 30-year (1985–2014) weather data. The result shows that soybean can be grown in northeast Nigeria, but yield performance is dependent on location, variety and sowing window. The simulated yield was higher in the SS than in the GS agro-ecozone despite the longer growing period in the later. Low yield was simulated for TGX 1448–2E for most of the sites. The yield of TGX1951–3 F was above a threshold of 1500 kg ha−1 in 5 out of 12 sites in the GS and 7 out of 12 sites in the SS, suggesting that this variety is the most suitable for cultivation in northeast Nigeria. Sowing TGX 1951–3 F can be delayed to July 16 at Gwaskara, Nasarawo Demsa and Tawa in the GS and at Briyel, Lakundum, Jara Dali, Kurbo Gayi, and Mathau in the SS with a low-risk of crop failure. The desired yield will be achieved at Chikala and Puba Vidau with a significantly low risk of crop failure for all sowing windows. The results from this study suggest that the CSM-CROPGRO-Soybean model can be a valuable tool in determining the right variety and sowing window for soybean production in targeted agroecological zones in northeast Nigeria

Understanding nutrient imbalances in maize (Zea mays L.) using the diagnosis and recommendation integrated system

Open Access Journal; Published online: 06 Aug 2021Low 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

Predicting intercrop competition, facilitation, and productivity from simple functional traits

Open Access ArticleContext Recent meta-analyses demonstrate that intercropping can increase the land use efficiency of crop production by 20–30 % on average, indicating a strong potential contribution to sustainable intensification. However, there is substantial variability around this average: individual studies range from half to double the land productivity of monocrops. Legume-cereal intercrops and intercrops with high temporal niche separation tend to be more productive than the average, but these two combination types are not always suitable. There is a need to explore other possibilities to achieve productive intercrops. Research question We explored whether two simple functional traits involved in radiation use, plant vegetative height and specific leaf area (SLA), could be used to predict intercrop productivity. Height and SLA together are associated with key plant life-history and resource economy strategies determining competitiveness and tolerance of competition, especially with regard to light, and could therefore be expected to underpin overyielding in intercrops. Methods In the first year of our study, we grew crops as monocrops at one site in Kenya and measured their height and SLA. In the second year, we grew crops in monocrop, intercrop, and single plant treatments at two sites in Kenya and one site in Nigeria. Together, these treatments allowed us to identify whether each intercrop combination overyielded or underyielded, and whether any overyielding was driven by facilitation and/or differences in inter- vs intraspecific competition. We then related the strength of these interactions to the two traits. Results We found that intercrop grain yields varied in relation to the height and SLA of each species in the intercrop, but together these traits explained less than a third of variation in intercrop land equivalence ratios (LER). More variation could be explained by allowing for the effect of site, suggesting that the two traits interact with site conditions to determine yield. Biomass LERs responded differently to grain LERs, suggesting that plasticity in resource allocation in response to intercropping conditions may further influence yields. Conclusions Our study found some evidence that combining species with traits indicating contrasting responses to competition (an avoidant species with a tolerant species) could increase resource use complementarity and thus intercrop overyielding. However, it was clear that other factors (such as additional traits, or the trait by site interaction) are needed to refine our understanding of intercrop productivity. Implications A trait-based framework has potential to predict intercrop productivity, but simple measures of height and SLA alone are insufficient

Compositional nutrient diagnosis (CND) and associated yield predictions in maize: a case study in the northern Guinea savanna of Nigeria

Open Access Article; Published online: 17 Aug 2022Developing optimal strategies for nutrient management of soils and crops at a larger scale requires an understanding of nutrient limitations and imbalances. The availability of extensive data (n = 1,781) from 2-yr nutrient omission trials in the most suitable agroecological zone for maize (Zea mays L.) in Nigeria (i.e., the northern Guinea savanna) provides an opportunity to assess nutrient limitations and imbalances using the concept of multi-ratio compositional nutrient diagnosis (CND). We also compared and contrasted the use of linear regression models and bootstrap forest machine learning to predict maize yield based on nutrient concentration in ear leaves. The results showed that 35% of the experimental plots had low yields due to nutrient imbalances (hereafter referred to as low yield imbalanced [LYI]). These experimental plots were dominated by control plots (without any nutrients applied), plots without N fertilization, and plots without P fertilization. Using the control plot as the ultimate indicator of nutrient imbalance, the significantly limiting nutrients in order of decreasing frequency of deficiency were N, P, S, Ca > Cu, and B. Both linear regression and bootstrap forest machine learning models fairly predicted maize grain yield based on nutrient concentration in ear leaves only in the LYI group and when examining all data with an independent validation dataset. These results suggest that nutrient management strategies, especially through the site-specific management approach, should consider S, Ca, Cu, and B in addition to the existing nutrients N, P, and K to improve nutrient balance and maize yield in the study area

Delineation of soil fertility management zones for site-specific nutrient management in the maize belt region of Nigeria

Open Access Journal; Published online: 29 Oct 2020Site-specific nutrient management can reduce soil degradation and crop production risks related to undesirable timing, amount, and type of fertilizer application. This study was conducted to understand the spatial variability of soil properties and delineate spatially homogenous nutrient management zones (MZs) in the maize belt region of Nigeria. Soil samples (n = 3387) were collected across the area using multistage and random sampling techniques, and samples were analyzed for pH, soil organic carbon (SOC), macronutrients (N, P, K, S, Ca and Mg), micronutrients (S, B, Zn, Mn and Fe) content, and effective cation exchange capacity (ECEC). Spatial distribution and variability of these parameters were assessed using geostatistics and ordinary kriging, while principal component analysis (PCA) and multivariate K-means cluster analysis were used to delineate nutrient management zones. Results show that spatial variation of macronutrients (total N, available P, and K) was largely influenced by intrinsic factors, while that of S, Ca, ECEC, and most micronutrients was influenced by both intrinsic and extrinsic factors with moderate to high spatial variability. Four distinct management zones, namely, MZ1, MZ2, MZ3, and MZ4, were identified and delineated in the area. MZ1 and MZ4 have the highest contents of most soil fertility indicators. MZ4 has a higher content of available P, Zn, and pH than MZ1. MZ2 and MZ3, which constitute the larger part of the area, have smaller contents of the soil fertility indicators. The delineated MZs offer a more feasible option for developing and implementing site-specific nutrient management in the maize belt region of Nigeria