Nitrogen level impact on the production of double row fodder of maize

Maize is the most important crop in Mexico, being central to the diets of consumers, particularly smallholders, and an undetermined amount is allocated as straw, green fodder, and, to a lesser extent, as silage for animal feed. Nitrogen fertilizer is considered one of the most important factors affecting growth, grain yield, and maize biomass production. In this context, the main objective of this study was to evaluate the effects of different levels of nitrogen fertilizer on maize production. A randomized complete block experimental design consisted of three treatments of nitrogen (180, 160, and 80 kg/ha) with three replications and morphological (plant height, stem thickness, and rate of growth), yield, and yield components (cob weight, length, thickness, number of rows per cob, and plant biomass) variables were used. The results suggest that the increase in nitrogen levels increases all the parameters of maize production. However, at 160 kg/ha, the greatest production of fodder was recorded with 5.99 tons/ha, superior to the one reported at 180 kg/ha, which was 5.47 tons/ha. We conclude that the maize fodder production can be optimized with the use of 160 kg/ha in the conditions of the altiplano of San Luis Potosí (Mexico).

Evaluation of multiple satellite precipitation products for rainfed maize production systems over Vietnam

High-resolution reliable rainfall datasets are vital for agricultural, hydrological, and weather-related applications. The accuracy of satellite estimates has a significant effect on simulation models in particular crop simulation models, which are highly sensitive to rainfall amounts, distribution, and intensity. In this study, we evaluated five widely used operational satellite rainfall estimates: CHIRP, CHIRPS, CPC, CMORPH, and GSMaP. These products are evaluated by comparing with the latest improved Vietnam-gridded rainfall data to determine their suitability for use in impact assessment models. CHIRP/S products are significantly better than CMORPH, CPC, and GsMAP with higher skill, low bias, showing a high correlation coefficient with observed data, and low mean absolute error and root mean square error. The rainfall detection ability of these products shows that CHIRP outperforms the other products with a high probability of detection (POD) scores. The performance of the different rainfall datasets in simulating maize yields across Vietnam shows that VnGP and CHIRP/S were capable of producing good estimates of average maize yields with RMSE ranging from 536 kg/ha (VnGP), 715 kg/ha (CHIRPS), 737 kg/ha (CHIRP), 759 kg/ha (GsMAP), 878 kg/ha (CMORPH) to 949 kg/ha (CPC). We illustrated that there is a potential for use of satellite rainfall estimates to overcome the issues of data scarcity in regions with sparse rain gauges.

Evaluating Climate Change Impact of Rainfed Maize Production Yield in Southern Ethiopia

A developing country like Ethiopia suffers a lot from the effects of climate change due to its limited economic capability to build irrigation projects to combat climate change's impact on crop production. This study evaluates climate change's impact on rainfed maize production in the Southern part of Ethiopia. AquaCrop, developed by FAO that simulates the crop yield response to water deficit conditions, is employed to assess potential rainfed maize production in the study area with and without climate change. The Stochastic weather generators model LARS-WG of the latest version is used to simulate local-scale level climate variables based on low-resolution GCM outputs. The expected monthly percentage change of rainfall during these two-time horizons (2040 and 2060) ranges from -23.18 to 20.23% and -14.8 to 36.66 respectively. Moreover, the monthly mean of the minimum and maximum temperature are estimated to increase in the range of 1.296 0C to 2.192 0C and 0.98 0C to 1.84 0C for the first time horizon (2031-2050) and from 1.860C to 3.40C and 1.560C to 3.180C in the second time horizon (2051-2070), respectively. Maize yields are expected to increase with the range of 4.13–7% and 6.36–9.32% for the respective time horizon in the study area provided that all other parameters were kept the same. In conclusion, the study results suggest that rainfed maize yield responds positively to climate change if all field management, soil fertility, and crop variety improve were kept the same to baseline; but since there is intermodal rainfall variability among the seasons planting date should be scheduled well to combat water stress on crops. The authors believe that this study is very likely important for regional development agents (DA) and policymakers to cope up with the climate change phenomenon and take some mitigation and adaptation strategies.

Conservation agriculture in the southern highlands of Tanzania: learnings from two decades of research for development.

Since its introduction into the Southern Highlands of Tanzania by researchers 25 years ago, Conservation Agriculture (CA) has been well received, researched and the concept proven to be increasing productivity and incomes, enhancing resilience of livelihoods and contributing to reducing greenhouse gas emissions. CA research, as defined by the three interlined principles, was introduced into the Southern Highlands by the Tanzania Agricultural Research Institute (TARI) Uyole, formerly Agricultural Research Institute (ARI) Uyole around 1995. Research results showed a labour saving of up to 70% in CA compared to conventional tillage, yield increases of 26%-100% and 360% for maize and sunflower, respectively, partly attributed to higher moisture content (18%-24%) in CA systems. CA was also found to be much more effective in mitigating dry spells and increasing productivity in maize production in areas where average annual rainfall is less than 770 mm. Economic analysis of maize production showed that profits in CA were three times more than in conventional tillage production at US$526.9 ha-1 and US$ 176.6 ha-1, respectively. Profits were twice as much for beans under CA at US$917.4 ha-1 compared to US$376.3 ha-1 for conventional practice. Studies confirm that 5% of farmers in the Southern Highlands have adopted CA. Increased uptake requires addressing challenges including resistance to change in mindset, inaccessibility of appropriate mechanization and cover crop seeds, traditions of free-range communal grazing of livestock (which makes it difficult for farmers to retain crop residue in their farms) and shortage of investment capital. A holistic value chain approach is recommended in CA interventions, bringing together various stakeholders including scientists, trainers, extension workers, administrators, policy makers, agro-inputs and machinery dealers, machinery service providers, agro-processors and financial institutions. The innovations adaptation set-up brings service providers closer to farmers for co-innovation. Long-term CA programmes are recommended, with farmers being taken through the complete learning cycle in testing CA technologies under their own farm environments. This should be complemented by entrepreneurial CA machinery hire services provision to increase the availability of farm power to smallholders unlikely to have the capital or skills to buy and manage their own machinery. The proof of application of the CA concept in the Southern Highlands has set the stage for further scaling the adoption of CA through support from national policies and programmes.

Effect of Application of Compost With Inorganic Fertilizer on Population of Phosphate-Solubilizing Bacteria and Maize Yield in Dry Land

The aim of this study was to explore the effect of a combination of manure and inorganic fertilizer (NPK and Urea) on the population of phosphate-solubilizing bacteria and the yield of maize. The study was carried out from June to October 2018 in the Kemantren Village, Alas Kulak Hamlet, Jabung District, Malang Regency. This study used a randomized block design consisting of 8 treatment levels and repeated three times. The results of the analysis of variance showed that the application of a combination of compost, fertilizer (NPK and Urea) gave significantly different results to the population of phosphate solubilizing bacteria C-organic, P-total, P-available, dry shelled weight and stover weight. The treatment of 2 t ha-1 compost + 100 kg ha-1 NPK + 50 kg gave the highest yield for the population of phosphate solubilizing bacteria with a value of 61×104 CFU.g-1. Maize production yields obtained treatment of 2 t ha-1 of compost + 400kg.ha-1NPK + 200 kg.ha-1 Urea reached a value of 8.65 t ha-1.

Analysis of Potential Distribution of Spodoptera Frugiperda In Northwest

Spodoptera frugiperda (J. E. Smith) (Lepidoptera: Noctuidae), a newly invaded pest that breaks out fast and severely, causes a serious threat to the national security of food production. In this study, the MaxEnt model was used to predict the potentially suitable distribution area of S. frugiperda in Northwest China. The potential distribution of S. frugiperda was predicted using meteorological factors from the correlation analysis. According to the result, a satisfactory AUC value in the MaxEnt model indicates that the prediction model has good accuracy, which is sufficient for predicting the fitness zone of S. frugiperda in Northwest China. The prediction results show that the potential distribution risk of S. frugiperda is high in western Gansu, eastern Qinghai, Shaanxi, most regions of Ningxia, and part regions of Tibetan, and it also exists in Hami, Yili, Bozhou, Urumqi, Hotan, and Aksu in Xinjiang, and more than 60% of Northwest China are suitable distribution areas for S. frugiperda. As China's major wheat and maize production area, Northwest China is a crucial prevention area for S. frugiperda. Clarifying the potential geographical distribution of S. frugiperda in Northwest China is essential for early warning as well as prevention and control.