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Rice blast is a serious fungal disease of rice (Oryza sativa L.) that is threatening global food security. It has been extensively studied due to the importance of rice production and consumption, and because of its vast distribution and destructiveness across the world. Rice blast, caused by Pyricularia oryzae Cavara 1892 (A), can infect aboveground tissues of rice plants at any growth stage and cause total crop failure. The pathogen produces lesions on leaves (leaf blast), leaf collars (collar blast), culms, culm nodes, panicle neck nodes (neck rot), and panicles (panicle blast), which vary in color and shape depending on varietal resistance, environmental conditions, and age. Understanding how rice blast is affected by environmental conditions at the cellular and genetic level will provide critical insight into incidence of the disease in future climates for effective decision-making and management. Integrative strategies are required for successful control of rice blast, including chemical use, biocontrol, selection of advanced breeding lines and cultivars with resistance genes, investigating genetic diversity and virulence of the pathogen, forecasting and mapping distribution of the disease and pathogen races, and examining the role of wild rice and weeds in rice blast epidemics. These tactics should be integrated with agronomic practices including the removal of crop residues to decrease pathogen survival, crop and land rotations, avoiding broadcast planting and double cropping, water management, and removal of yield-limiting factors for rice production. Such an approach, where chemical use is based on crop injury and estimated yield and economic losses, is fundamental for the sustainable control of rice blast to improve rice production for global food security.

Nitrogen (N) fertilizers are needed to enhance maize (Zea mays L.) production. Maize plays a major role in the livestock industry, biofuels, and human nutrition. Globally, less than one-half of applied N is recovered by maize. Although the application of N fertilizer can improve maize yield, excess N application due to low knowledge of the mechanisms of nitrogen use efficiency (NUE) poses serious threats to environmental sustainability. Increased environmental consciousness and an ever-increasing human population necessitate improved N utilization strategies in maize production. Enhanced understanding of the relationship between maize growth and productivity and the dynamics of maize N recovery are of major significance. A better understanding of the metabolic and genetic control of N acquisition and remobilization during vegetative and reproductive phases are important to improve maize productivity and to avoid excessive use of N fertilizers. Synchronizing the N supply with maize N demand throughout the growing season is key to improving NUE and reducing N loss to the environment. This review examines the mechanisms of N use in maize to provide a basis for driving innovations to improve NUE and reduce risks of negative environmental impacts.

Nitrogen fertilizers play a key role in crop production to meet global food demand. Inappropriate application of nitrogen fertilizer coupled with poor irrigation and other crop management practices threaten agriculture and environmental sustainability. Over application of nitrogen fertilizer increases nitrogen gas emission and nitrate leaching. A field experiment was conducted in China’s oasis irrigation area in 2018 and 2019 to determine which nitrogen rate, plant density, and irrigation level in sole maize ( Zea mays L.) cropping system reduce ammonia emission and nitrate leaching. Three nitrogen rates of urea (46-0-0 of N-P 2 O 5 -K 2 O), at (N 0 = 0 kg N ha −1 , N 1 = 270 kg N ha −1 , and N 2 = 360 kg N ha −1 ) were combined with three plant densities (D 1 = 75,000 plants/ha −1 , D 2 = 97,500 plants/ha −1 , and D 3 = 120,000 plants/ha −1 ) with two irrigation levels (W 1 = 5,250 m 3 /hm 2 and W 2 = 4,740 m 3 /hm 2 ) using a randomized complete block design. The results showed that, both the main and interaction effects of nitrogen rate, plant density, and irrigation level reduced nitrate leaching ( p < 0.05). In addition, irrigation level × nitrogen rate significantly ( p < 0.05) reduced ammonia emission. Nitrate leaching and ammonia emission decreased with higher irrigation level and higher plant density. However, high nitrogen rates increased both nitrate leaching and ammonia emission. The study found lowest leaching (0.35 mg kg −1 ) occurring at the interaction of 270 kg N ha −1 × 120,000 plants/ha −1 × 4,740 m 3 /hm 2 , and higher plant density of 120,000 plants/ha −1 combined with 0 kg N ha −1 and irrigation level of 5,250 m 3 /hm 2 recorded the lowest ammonia emission (0.001 kg N) −1 . Overall, ammonia emission increased as days after planting increased while nitrate leaching decreased in deeper soil depths. These findings show that, though the contributory roles of days after planting, soil depth, amount of nitrogen fertilizer applied and year of cultivation cannot be undermined, it is possible to reduce nitrate leaching and ammonia emission through optimized nitrogen rate, plant density and regulated irrigation for agricultural and environmental sustainability.

Nitrogen is a key factor in maize (Zea mays L.) grain and biomass production. Inappropriate application with sub-optimum plant density and irrigation can lead to low productivity and inefficient use. A two-year field experiment was conducted to determine which nitrogen rate, plant density, and irrigation level optimize grain, biomass yield, and water use efficiency. Three nitrogen rates of urea (46–0–0 of N–P2O5–K2O) (N0 = 0 kg N ha−1, N1 = 270 kg N ha−1, and N2 = 360 kg N ha−1), with three maize densities (D1 = 75,000 plants ha−1, D2 = 97,500 plants ha−1, and D3 = 120,000 plants ha−1), and two irrigation levels (W1 = 5250 m3/hm2 and W2 = 4740 m3/hm2) were investigated. The results show that both grain and biomass yields were affected by the main factors. The interaction between nitrogen rate and irrigation level significantly (p < 0.001) affected grain yield but not biomass. It was observed that the grain yield increased correspondingly with nitrogen rate and plant density, while it decreased as the irrigation level increased. Water use efficiency was significantly (p < 0.001) affected by the main factors and their interactions. Nevertheless, water use efficiency was highest at (5250 m3/hm2) × 270 kg N ha−1; × 360 kg N ha−1 × 120,000 plants ha−1 and increased from 62% to 68%. In addition, the highest biomass yield was recorded at 5250 m3/hm2 × 270 kg N ha−1; × 360 kg N ha−1 × 120,000 plants ha−1 while the interaction of either irrigation level with 0 and 270 kg ha−1 or 97,500 and 120,000 plants ha−1 yielded the lowest water use efficiency. Thus, optimized nitrogen rates, plant density, and alternate irrigation levels can support optimum grain and biomass yields. It can also improve nitrogen and water use efficiency in maize production.

The development of productively viable cropping systems with lower environmental footprints to maintain sustainable agriculture in arid areas is urgently needed. Increasing crop diversity usually improves system productivity; however, the effects of crop diversification on the carbon footprint and the sustainability of a cropping system remain unclear. A 3-year field experiment (2018–2020) was conducted in northwestern China to determine the carbon footprint and productivity of five cropping systems, including spring wheat-common vetch/maize double relay cropping (three crops a year), wheat-maize intercropping (two crops a year) wheat-common vetch multiple cropping (two crops a year), monoculture maize (one crop a year), and monoculture wheat (one crop a year). The grain yield for wheat-common vetch/maize double relay cropping (the former) was higher by 8.7% in 2020 as compared to wheat-maize intercropping (the latter). For the same two cropping systems, the energy yield of the former was higher by 9.5–25.1% over 3 years. The carbon footprints of the former system were respectively 5.3%, 14.3%, 16.4%, and 7.4% lower than that of the latter in terms of unit area, kg grain yield, unit energy yield, and unit of economic output. Four carbon footprints of the former system were lower by 12.2%, 27.9%, 37.6%, and 29.6% compared with monoculture maize. The highest sustainability index was observed for a three crops per year system (0.94), due to higher productivity and a lower carbon footprint. This is the first demonstration that increased diversity via double relay cropping on the same plot annually maintained productivity without increasing the carbon footprint in arid irrigation areas. The results partly confirm the positive effect of diversified cropping systems by integrating multiple cropping green manure into an intercropping system. Adopting a diversified strategy exemplified by spring wheat-common vetch/maize double relay cropping contributes to improvements in sustainable crop production in arid, irrigated areas.

To some extent, the photosynthetic traits of developing leaves of maize are regulated systemically by water and nitrogen. However, it remains unclear whether photosynthesis is systematically regulated via water and nitrogen when maize crops are grown under close (high density) planting conditions. To address this, a field experiment that had a split-split plot arrangement of treatments was designed. Two irrigation levels on local traditional irrigation level (high, I2, 4,050 m 3 ha −1 ) and reduced by 20% (low, I1, 3,240 m 3 ha −1 ) formed the main plots; two levels of nitrogen fertilizer at a local traditional nitrogen level (high, N2, 360 kg ha −1 ) and reduced by 25% (low, N1, 270 kg ha −1 ) formed the split plots; three planting densities of low (D1, 7.5 plants m −2 ), medium (D2, 9.75 plants m −2 ), and high (D3, 12 plants m −2 ) formed the split-split plots. The grain yield, gas exchange, and chlorophyll a fluorescence of the closely planted maize crops were assessed. The results showed that water–nitrogen coupling regulated their net photosynthetic rate (Pn), stomatal conductance (Gs), transpiration rate (Tr), quantum yield of non-regulated non-photochemical energy loss [Y(NO)], actual photochemical efficiency of PSII [Y(II)], and quantum yield of regulated non-photochemical energy loss [Y(NPQ)]. When maize plants were grown at low irrigation with traditional nitrogen and at a medium density (i.e., I1N2D2), they had Pn, Gs, and Tr higher than those of grown under traditional treatment conditions (i.e., I2N2D1). Moreover, the increased photosynthesis in the leaves of maize in the I1N2D2 treatment was mainly caused by decreased Y(NO), and increased Y(II) and Y(NPQ). The coupling of 20%-reduced irrigation with the traditional nitrogen application boosted the grain yield of medium density-planted maize, whose Pn, Gs, Tr, Y(II), and Y(NPQ) were enhanced, and its Y(NO) was reduced. Redundancy analysis revealed that both Y(II) and SPAD were the most important physiological factors affecting maize yield performance, followed by Y(NPQ) and NPQ. Using the 20% reduction in irrigation and traditional nitrogen application at a medium density of planting (I1N2D2) could thus be considered as feasible management practices, which could provide technical guidance for further exploring high yields of closely planted maize plants in arid irrigation regions.

Cowpea is deemed as a food security crop due to its ability to produce significant yields under conditions where other staples fail. Its resilience in harsh environments; such as drought, heat and marginal soils; along with its nitrogen-fixing capabilities and suitability as livestock feed make cowpea a preferred choice in many farming systems across sub-Saharan Africa (SSA). Despite its importance, Cowpea yields in farmers’ fields remain suboptimal, primarily due to biotic and abiotic factors and the use of either unimproved varieties or improved varieties that are not well-suited to local conditions. Multi environment testing of genotypes is essential for recommending varieties suited for either specific or for wide cultivation. This study aimed, to identify and recommend cowpea breeding lines for wide or specific cultivation in the Sudan Savanna and Deciduous Forest zones of Ghana. The research utilized twenty early-maturing advance cowpea breeding lines and three check varieties (released varieties). The experiment was conducted in two locations: Bunso in the Deciduous Forest zone and Manga in the Sudan Savanna zone over 2020/2021 and 2021/2022 cropping seasons. Combined analysis of variance revealed a significant genotype-environment interaction (GEI) which accounted for 35.12% of the variation in yield. The environments were classified into three mega environments, with Bunso_2021 identified as the near-ideal environment where the genotypes exhibited their maximum genetic potentials. In terms of adaption, genotype UG_04 demonstrated broad adaption, showing high yield and stability across all test environments. Genotypes UG_01 and UG_02 performed particularly well in Bunso_2021 and Bunso_2022, while UG_04 and UG_14 excelled in Manga_2021. These findings provide valuable insights for selecting cowpea varieties that can enhance productivity and stability in diverse agro-ecological zones.

Cowpea is deemed as a food security crop due to its ability to produce significant yields under conditions where other staples fail. Its resilience in harsh environments; such as drought, heat and marginal soils; along with its nitrogen-fixing capabilities and suitability as livestock feed make cowpea a preferred choice in many farming systems across sub-Saharan Africa (SSA). Despite its importance, Cowpea yields in farmers' fields remain suboptimal, primarily due to biotic and abiotic factors and the use of either unimproved varieties or improved varieties that are not well-suited to local conditions. Multi environment testing of genotypes is essential for recommending varieties suited for either specific or for wide cultivation. This study aimed, to identify and recommend cowpea breeding lines for wide or specific cultivation in the Sudan Savanna and Deciduous Forest zones of Ghana. The research utilized twenty early-maturing advance cowpea breeding lines and three check varieties (released varieties). The experiment was conducted in two locations: Bunso in the Deciduous Forest zone and Manga in the Sudan Savanna zone over 2020/2021 and 2021/2022 cropping seasons. Combined analysis of variance revealed a significant genotype-environment interaction (GEI) which accounted for 35.12% of the variation in yield. The environments were classified into three mega environments, with Bunso_2021 identified as the near-ideal environment where the genotypes exhibited their maximum genetic potentials. In terms of adaption, genotype UG_04 demonstrated broad adaption, showing high yield and stability across all test environments. Genotypes UG_01 and UG_02 performed particularly well in Bunso_2021 and Bunso_2022, while UG_04 and UG_14 excelled in Manga_2021. These findings provide valuable insights for selecting cowpea varieties that can enhance productivity and stability in diverse agro-ecological zones.

Cowpea is deemed as a food security crop due to its ability to produce significant yields under conditions where other staples fail. Its resilience in harsh environments; such as drought, heat and marginal soils; along with its nitrogen-fixing capabilities and suitability as livestock feed make cowpea a preferred choice in many farming systems across sub-Saharan Africa (SSA). Despite its importance, Cowpea yields in farmers' fields remain suboptimal, primarily due to biotic and abiotic factors and the use of either unimproved varieties or improved varieties that are not well-suited to local conditions. Multi environment testing of genotypes is essential for recommending varieties suited for either specific or for wide cultivation. This study aimed, to identify and recommend cowpea breeding lines for wide or specific cultivation in the Sudan Savanna and Deciduous Forest zones of Ghana. The research utilized twenty early-maturing advance cowpea breeding lines and three check varieties (released varieties). The experiment was conducted in two locations: Bunso in the Deciduous Forest zone and Manga in the Sudan Savanna zone over 2020/2021 and 2021/2022 cropping seasons. Combined analysis of variance revealed a significant genotype-environment interaction (GEI) which accounted for 35.12% of the variation in yield. The environments were classified into three mega environments, with Bunso_2021 identified as the near-ideal environment where the genotypes exhibited their maximum genetic potentials. In terms of adaption, genotype UG_04 demonstrated broad adaption, showing high yield and stability across all test environments. Genotypes UG_01 and UG_02 performed particularly well in Bunso_2021 and Bunso_2022, while UG_04 and UG_14 excelled in Manga_2021. These findings provide valuable insights for selecting cowpea varieties that can enhance productivity and stability in diverse agro-ecological zones.