Genome-wide association study reveals SNP markers controlling drought tolerance and related agronomic traits in chickpea across multiple environments.

Chickpea, renowned for its exceptional nutritional value, stands as a crucial crop, serving as a dietary staple in various parts of the world. However, its productivity faces a significant challenge in the form of drought stress. This challenge highlights the urgent need to find genetic markers linked to drought tolerance for effective breeding programs. The primary objective of this study is to identify genetic markers associated with drought tolerance to facilitate effective breeding programs. To address this, we cultivated 185 chickpea accessions in two distinct locations in Lebanon over a two-year period, subjecting them to both irrigated and rain-fed environments. We assessed 11 drought-linked traits, including morphology, growth, yield, and tolerance score. SNP genotyping revealed 1344 variable SNP markers distributed across the chickpea genome. Genetic diversity across populations originating from diverse geographic locations was unveiled by the PCA, clustering, and structure analysis indicating that these genotypes have descend from five or four distinct ancestors. A genome-wide association study (GWAS) revealed several marker trait associations (MTAs) associated with the traits evaluated. Within the rainfed conditions, 11 significant markers were identified, each associated with distinct chickpea traits. Another set of 11 markers exhibited associations in both rainfed and irrigated environments, reflecting shared genetic determinants across these conditions for the same trait. The analysis of linkage disequilibrium (LD) highlighted two genomic regions with notably strong LD, suggesting significant interconnections among several investigated traits. This was further investigated by the correlation between major markers associated with these traits. Gene annotation of the identified markers has unveiled insights into 28 potential genes that play a role in influencing various chickpea drought-linked traits. These traits encompass crucial aspects such as blooming organ development, plant growth, seed weight, starch metabolism, drought regulation, and height index. Among the identified genes are CPN60-2, hsp70, GDSL(GELP), AHL16, NAT3, FAB1B, bZIP, and GL21. These genes collectively contribute to the multifaceted response of chickpea plants to drought stress. Our identified genetic factors exert their influence in both irrigated and rainfed environments, emphasizing their importance in shaping chickpea characteristics.

Ca and Mg stimulate protein synthesis in maize kernel through the action of endogenous hormones and defense enzymes.

Soil calcium (Ca) and magnesium (Mg) mineral states in rain-fed arid regions of Northwest China are inefficient, and their levels of substitution and water-soluble states are far below the lowest threshold required for maize growth, resulting in frequent physiological diseases, restricting synthesis of kernel protein (CRP). Our study set up different levels of foliar spraying of Ca and Mg fertilizers before maize pollination to examine the response characteristics of physiological and biochemical indicators in kernel, and the driving process of CRP synthesis. The main findings were: (1) Ca and Mg significantly increased the levels of CRP and endogenous hormones, and the activities of defense enzymes and CRP synthesis enzymes, which decreased significantly and stabilized at the maturity stage of maize. (2) The synthesis and accumulation of CRP were synergistically regulated by endogenous hormones, defense enzymes, and CRP synthase enzymes, with the degree of regulation varying with the level of Ca and Mg supplementation. Indole-3-acetic acid (IAA), gibberellin (GA), zeatin riboside (ZR), catalase (CAT), malondialdehyde (MDA), and glutamate dehydrogenase (GDH) were the primary physiological driving indicators of CRP synthesis, with CRP having a significant synergistic relationship with CAT and a remarkable trade-off with other driving indicators. (3) The dominant driving pathway of CRP synthesis was "Ca, Mg-IAA or GA or ZR-CAT-GDH-CRP". Ca and Mg positively affected IAA and GA levels, and IAA and GA positively regulated CAT activity. However, CAT negatively regulated GDH levels, causing GDH to negatively influence the synthesis and accumulation of CRP and its components. The findings provide theoretical support for further study of inter-root endogenous hormones and soil microbe-driven processes in the regulation of maize quality by Ca and Mg.

Small-Scale Farmers' Vulnerability to Biophysical and Socio-Economic Risks in Semi-Arid Lowlands of Mwanga District, Kilimanjaro Region, Tanzania.

Agricultural production systems in semi-arid areas are vulnerable to a myriad of risks. Using a systems approach of risk framework and a mixed-methods research design, this paper sought to explore selected biophysical and socio-economic risks that contributed to vulnerability of agricultural production systems in the semi-arid lowlands of Mwanga District, Kilimanjaro Region, Tanzania. Despite the lack of statistically significant relationships between amounts of rainfall and crop production in the district, 30 focus group participants perceived that spatial and temporal changes of rainfall distribution as coupled with increased crop pest/disease outbreaks and soil loss contributed to vulnerability of agricultural production systems in terms of frequent crop failure and famine particularly amongst farmers who practised rain-fed farming in the semi-arid lowlands. Furthermore, participants perceived that crop production and yields were negatively influenced by poor marketing and institutional structures and that crop production and yields were negatively influenced by farmers' poor access to appropriate technologies including seeds, fertilizers, agrochemicals, agricultural machinery and infrastructure including modern irrigation schemes and all-weather roads. By way of conclusion, reduced vulnerability of agricultural production systems calls for integrated enhancement of farmers' capacity in addressing the biophysical, agro-industrial and institutional risks.

Evaluation of technical efficiency of some rain-fed cereal and legume crops production in Syria: does crisis matter?

Background: Syria is a developing country whose economy is still dominated by the agricultural sector. The agricultural sector is considered as the main source of food in Syria and a major source of employment and income generation. Food and agricultural policies in Syria focus heavily on achieving food security and improving its four pillars (availability, accessibility, stability and utilization). As a result, until 2011, a good progress has been attained in food availability. The food security situation deteriorated in Syria after 2011 crisis, with the number of people facing acute food insecurity rising from 7.9 million in 2020 to a staggering 12.4 million in 2021. This is the result of many shocks that the agricultural sector has been exposed to, such as the relative decrease in cultivated areas, high costs of production, reduced input availability including labour, prevailing violence, related damage to farm equipment, and abandoned land. In view of the changes that the agricultural sector has been exposed to in Syria as a result of the crisis, the study concerns measuring the technical efficiency of production of some rain-fed cereal and legume crops in Syria and comparing it in the pre and post-crisis period, which has started in 2011. A non-parametric (DEA) method is applied for measuring technical efficiency during the time period 2003-2010 (pre-crisis) and the period 2011-2018 (post-crisis) with censored regression (the tobit model) to investigate the determinants of technical efficiency. A t test is used to test the null hypothesis (H0) that there was no difference in technical efficiency of the production of studied crops before and after the crisis in Syria and the alternative hypothesis (Ha) that there was a significant difference in technical efficiency. Results: The findings show low level of technical efficiency in the post-crisis period. The results verified differences in the technical efficiency of pre- and post-crisis period. The use of censored regression with dummy for crisis has shown negative and significant effect on technical efficiency of each of the durum wheat and lentil crops, while it had no significant effect on the other studied crops. Conclusions: This study can provide important information to the government to pursue a new policy for recovery and improving the agricultural production and productivity. There is an urgent need to adopt new policies that focus on providing production requirements in the form of low-interest loans, sustainable use of resources, providing support for the marketing process, and focusing on the export markets of some study crops (chickpeas and lentils). Government should improve agricultural extension services for farmers and encouraging them to adopt new technologies.

Field edge rainwater harvesting and inorganic fertilizers for improved sorghum (Sorghum bicolor L.) yields in semi-arid farming regions of Marange, Zimbabwe.

Sorghum (Sorghum bicolor L.) is mainly cultivated in marginal areas of Zimbabwe, where soil fertility is poor and rainfall is low, erratic, and poorly distributed, leading to low yields. The study aimed to determine the effect of tied contour (TC) and in-contour infiltration pits (IP) rainwater harvesting (RWH) methods and varying nitrogen fertilizer application rates on the yield of two sorghum varieties, Macia and Sc Sila. A split-split plot experiment was laid out, with the main plot factor being the RWH method, the subplot factor being sorghum variety, the sub-sub plot factor being nitrogen application, and the sub-sub-sub plot factor being the plant distance from the RWH method. The experiment was done at Mt Zonwe's small-scale farming community in the Mutare region from 2016/17 to 2018/19. The results revealed that TC and IP increased the gravimetric water content (gwc) of the soil. The gwc decreased gradually as the distance from the rainwater RWH method increased (0-5 m > 5-10 m > 10-15 m), with the 2016/17 season having the maximum gwc. In all seasons, TC and IP yielded much more sorghum grain than standard contour (SC). Sorghum grain production was significantly greater at all nitrogen application rates and consistently higher at all plant distances from the RWH method in the 2016/17 season with more rainfall. In comparison to TC and IP, the SC had significantly lower grain yield at all nitrogen application rates. At all plant distances from the RWH method, TC and IP had significantly higher grain production than SC in each variety of sorghum.

Benthic macroinvertebrates assemblages of glacial-fed (Bheri) and rain-fed (Babai) rivers in western Nepal in the wake of proposedinter-basin water transfer.

BACKGROUND: Benthic macroinvertebrates, encompassing large taxonomic groups of invertebrate organisms, are important components of aquatic ecosystems and play crucial roles in aquatic food webs. These organisms are also extensively used in water quality assessments as bioindicators for a range of stressors. Inter-basin water transfer (IBWT) is the transfer of water from a donor basin to a recipient basin and such transfers have both beneficial as well as adverse environmental and socio-economic impacts. This study attempts to generate baseline information on macroinvertebrates assemblages in glacial-fed (Bheri) and rain-fed (Babai) rivers of west Nepal, where Nepal's first ever inter-basin transfer is in progress and the data can be used to assess the impact of inter-basin water transfer on water quality and aquatic biodiversity after completion. NEW INFORMATION: The dataset includes the records on the taxonomic diversity of macroinvertebrate in the Bheri and the Babai River systems. A total of 56 families of macroinvertebrates belonging to eight classes and four phyla were observed. A significant variation between the glacial-fed and rain-fed and seasons were observed reflecting different ecological zones and abiotic variables in the rivers and their catchments. Hydropsychidae and Baetidae were reported to be the most abundant taxa in the Bheri River system, whereas Gyrinidae, Physidae, Chironomidae and Hydropsychidae were most abundant taxa in the Babai River system.

Statistical modeling for analyzing grain yield of durum wheat under rainfed conditions in Azad Jammu Kashmir, Pakistan / Modelagem estatística para analisar o rendimento de grãos de trigo durum sob condições de chuva em Azad Jammu Kashmir, Paquistão

One of the most important traits that plant breeders aim to improve is grain yield which is a highly quantitative trait controlled by various agro-morphological traits. Twelve morphological traits such as Germination Percentage, Days to Spike Emergence, Plant Height, Spike Length, Awn Length, Tillers/Plant, Leaf Angle, Seeds/Spike, Plant Thickness, 1000-Grain Weight, Harvest Index and Days to Maturity have been considered as independent factors. Correlation ,regression, and principal component analysis (PCA) are used to identify the different durum wheat traits, which significantly contribute to the yield. The necessary assumptions required for applying regression modeling have been tested and all the assumptions are satisfied by the observed data. The outliers are detected in the observations of fixed traits and Grain Yield. Some observations are detected as outliers but the outlying observations did not show any influence on the regression fit. For selecting a parsimonious regression model for durum wheat, best subset regression, and stepwise regression techniques have been applied. The best subset regression analysis revealed that Germination Percentage, Tillers/Plant, and Seeds/Spike have a marked increasing effect whereas Plant thickness has a negative effect on durum wheat yield. While stepwise regression analysis identified that the traits, Germination Percentage, Tillers/Plant, and Seeds/Spike significantly contribute to increasing the durum wheat yield. The simple correlation coefficient specified the significant positive correlation of Grain Yield with Germination Percentage, Number of Tillers/Plant, Seeds/Spike, and Harvest Index. These results of correlation analysis directed the importance of morphological characters and their significant positive impact on Grain Yield. [...].

Uma das características mais importantes que os produtores de plantas visam melhorar é o rendimento de grãos, que é uma particularidade altamente quantitativa e controlada por várias características agromorfológicas. Foram considerados 12 traços morfológicos como fatores independentes, como Porcentagem de Germinação, Dias para Emergência da Espiga, Altura da Planta, Comprimento da Espiga, Comprimento da Aresta, Perfilhos /Planta, Ângulo da Folha, Sementes /Espiga, Espessura da Planta, Peso de 1000 Grãos, Índice de Colheita e Dias até a Maturidade. A correlação, regressão e análise de componentes principais (em inglês Principal Component Analysis (PCA)) são usadas para identificar as diferentes características do trigo duro, que contribuem significativamente para o rendimento. As suposições necessárias exigidas para a aplicação da modelagem de regressão foram testadas e todas as suposições são adequadas de acordo com os dados observados. Os outliers são detectados nas observações de características fixas e rendimento de grãos. Algumas observações são detectadas como outliers, mas as observações outliers não mostraram qualquer influência no ajuste da regressão. Para selecionar um modelo de regressão parcimonioso para o trigo duro, foram aplicadas tanto a melhor regressão de subconjunto quanto as técnicas de regressão stepwise. A melhor análise de regressão de subconjunto revelou que a porcentagem de germinação, perfilhos /planta e sementes /espiga tem um efeito de aumento acentuado, enquanto a espessura da planta tem um efeito negativo sobre o rendimento do trigo duro. Enquanto a análise de regressão passo a passo identificou que as características, porcentagem de germinação, perfilhos/planta e sementes /espiga contribuem significativamente para aumentar a produtividade do trigo duro. O coeficiente de correlação simples especificou a correlação positiva significativa do [...].

Statistical modeling for analyzing grain yield of durum wheat under rainfed conditions in Azad Jammu Kashmir, Pakistan

Abstract One of the most important traits that plant breeders aim to improve is grain yield which is a highly quantitative trait controlled by various agro-morphological traits. Twelve morphological traits such as Germination Percentage, Days to Spike Emergence, Plant Height, Spike Length, Awn Length, Tillers/Plant, Leaf Angle, Seeds/Spike, Plant Thickness, 1000-Grain Weight, Harvest Index and Days to Maturity have been considered as independent factors. Correlation, regression, and principal component analysis (PCA) are used to identify the different durum wheat traits, which significantly contribute to the yield. The necessary assumptions required for applying regression modeling have been tested and all the assumptions are satisfied by the observed data. The outliers are detected in the observations of fixed traits and Grain Yield. Some observations are detected as outliers but the outlying observations did not show any influence on the regression fit. For selecting a parsimonious regression model for durum wheat, best subset regression, and stepwise regression techniques have been applied. The best subset regression analysis revealed that Germination Percentage, Tillers/Plant, and Seeds/Spike have a marked increasing effect whereas Plant thickness has a negative effect on durum wheat yield. While stepwise regression analysis identified that the traits, Germination Percentage, Tillers/Plant, and Seeds/Spike significantly contribute to increasing the durum wheat yield. The simple correlation coefficient specified the significant positive correlation of Grain Yield with Germination Percentage, Number of Tillers/Plant, Seeds/Spike, and Harvest Index. These results of correlation analysis directed the importance of morphological characters and their significant positive impact on Grain Yield. The results of PCA showed that most variation (70%) among data set can be explained by the first five components. It also identified that Seeds/Spike; 1000-Grain Weight and Harvest Index have a higher influence in contributing to the durum wheat yield. Based on the results it is recommended that these important parameters might be considered and focused in future durum wheat breeding programs to develop high yield varieties.

Resumo Uma das características mais importantes que os produtores de plantas visam melhorar é o rendimento de grãos, que é uma particularidade altamente quantitativa e controlada por várias características agromorfológicas. Foram considerados 12 traços morfológicos como fatores independentes, como Porcentagem de Germinação, Dias para Emergência da Espiga, Altura da Planta, Comprimento da Espiga, Comprimento da Aresta, Perfilhos /Planta, Ângulo da Folha, Sementes /Espiga, Espessura da Planta, Peso de 1000 Grãos, Índice de Colheita e Dias até a Maturidade,. A correlação, regressão e análise de componentes principais (em inglês Principal Component Analysis (PCA)) são usadas para identificar as diferentes características do trigo duro, que contribuem significativamente para o rendimento. As suposições necessárias exigidas para a aplicação da modelagem de regressão foram testadas e todas as suposições são adequadas de acordo com os dados observados. Os outliers são detectados nas observações de características fixas e rendimento de grãos. Algumas observações são detectadas como outliers, mas as observações outliers não mostraram qualquer influência no ajuste da regressão. Para selecionar um modelo de regressão parcimonioso para o trigo duro, foram aplicadas tanto a melhor regressão de subconjunto quanto as técnicas de regressão stepwise. A melhor análise de regressão de subconjunto revelou que a porcentagem de germinação, perfilhos /planta e sementes /espiga tem um efeito de aumento acentuado, enquanto a espessura da planta tem um efeito negativo sobre o rendimento do trigo duro. Enquanto a análise de regressão passo a passo identificou que as características, porcentagem de germinação, perfilhos/planta e sementes /espiga contribuem significativamente para aumentar a produtividade do trigo duro. O coeficiente de correlação simples especificou a correlação positiva significativa do rendimento de grãos com a porcentagem de germinação, número de perfilhos/planta, sementes / espiga e índice de colheita. Esses resultados da análise de correlação direcionaram a importância dos caracteres morfológicos e seu impacto positivo e significativo no rendimento de grãos. Os resultados da PCA mostraram que a maior parte da variação (70%) entre o conjunto de dados pôde ser explicada pelos cinco primeiros componentes. Também identificou que Sementes / Espiga, Peso de 1000 Grãos e Índice de Colheita têm uma maior influência na contribuição para o rendimento do trigo duro. Com base nos resultados, recomenda-se que esses importantes parâmetros possam ser considerados e focados em futuros programas de melhoramento de trigo duro para desenvolver variedades de alto rendimento.

Statistical modeling for analyzing grain yield of durum wheat under rainfed conditions in Azad Jammu Kashmir, Pakistan / Modelagem estatística para analisar o rendimento de grãos de trigo durum sob condições de chuva em Azad Jammu Kashmir, Paquistão

One of the most important traits that plant breeders aim to improve is grain yield which is a highly quantitative trait controlled by various agro-morphological traits. Twelve morphological traits such as Germination Percentage, Days to Spike Emergence, Plant Height, Spike Length, Awn Length, Tillers/Plant, Leaf Angle, Seeds/Spike, Plant Thickness, 1000-Grain Weight, Harvest Index and Days to Maturity have been considered as independent factors. Correlation, regression, and principal component analysis (PCA) are used to identify the different durum wheat traits, which significantly contribute to the yield. The necessary assumptions required for applying regression modeling have been tested and all the assumptions are satisfied by the observed data. The outliers are detected in the observations of fixed traits and Grain Yield. Some observations are detected as outliers but the outlying observations did not show any influence on the regression fit. For selecting a parsimonious regression model for durum wheat, best subset regression, and stepwise regression techniques have been applied. The best subset regression analysis revealed that Germination Percentage, Tillers/Plant, and Seeds/Spike have a marked increasing effect whereas Plant thickness has a negative effect on durum wheat yield. While stepwise regression analysis identified that the traits, Germination Percentage, Tillers/Plant, and Seeds/Spike significantly contribute to increasing the durum wheat yield. The simple correlation coefficient specified the significant positive correlation of Grain Yield with Germination Percentage, Number of Tillers/Plant, Seeds/Spike, and Harvest Index. These results of correlation analysis directed the importance of morphological characters and their significant positive impact on Grain Yield. The results of PCA showed that most variation (70%) among data set can be explained by the first five components. It also identified that Seeds/Spike; 1000-Grain Weight and Harvest Index have a higher influence in contributing to the durum wheat yield. Based on the results it is recommended that these important parameters might be considered and focused in future durum wheat breeding programs to develop high yield varieties.

Uma das características mais importantes que os produtores de plantas visam melhorar é o rendimento de grãos, que é uma particularidade altamente quantitativa e controlada por várias características agromorfológicas. Foram considerados 12 traços morfológicos como fatores independentes, como Porcentagem de Germinação, Dias para Emergência da Espiga, Altura da Planta, Comprimento da Espiga, Comprimento da Aresta, Perfilhos /Planta, Ângulo da Folha, Sementes /Espiga, Espessura da Planta, Peso de 1000 Grãos, Índice de Colheita e Dias até a Maturidade,. A correlação, regressão e análise de componentes principais (em inglês Principal Component Analysis (PCA)) são usadas para identificar as diferentes características do trigo duro, que contribuem significativamente para o rendimento. As suposições necessárias exigidas para a aplicação da modelagem de regressão foram testadas e todas as suposições são adequadas de acordo com os dados observados. Os outliers são detectados nas observações de características fixas e rendimento de grãos. Algumas observações são detectadas como outliers, mas as observações outliers não mostraram qualquer influência no ajuste da regressão. Para selecionar um modelo de regressão parcimonioso para o trigo duro, foram aplicadas tanto a melhor regressão de subconjunto quanto as técnicas de regressão stepwise. A melhor análise de regressão de subconjunto revelou que a porcentagem de germinação, perfilhos /planta e sementes /espiga tem um efeito de aumento acentuado, enquanto a espessura da planta tem um efeito negativo sobre o rendimento do trigo duro. Enquanto a análise de regressão passo a passo identificou que as características, porcentagem de germinação, perfilhos/planta e sementes /espiga contribuem significativamente para aumentar a produtividade do trigo duro. O coeficiente de correlação simples especificou a correlação positiva significativa do rendimento de grãos com a porcentagem de germinação, número de perfilhos/planta, sementes / espiga e índice de colheita. Esses resultados da análise de correlação direcionaram a importância dos caracteres morfológicos e seu impacto positivo e significativo no rendimento de grãos. Os resultados da PCA mostraram que a maior parte da variação (70%) entre o conjunto de dados pôde ser explicada pelos cinco primeiros componentes. Também identificou que Sementes / Espiga, Peso de 1000 Grãos e Índice de Colheita têm uma maior influência na contribuição para o rendimento do trigo duro. Com base nos resultados, recomenda-se que esses importantes parâmetros possam ser considerados e focados em futuros programas de melhoramento de trigo duro para desenvolver variedades de alto rendimento.

Nitrous oxide, methane emissions and grain yield in rainfed wheat grown under nitrogen enriched biochar and straw in a semiarid environment.

BACKGROUND: Soil application of biochar and straw alone or their combinations with nitrogen (N) fertilizer are becoming increasingly common, but little is known about their agronomic and environmental performance in semiarid environments. This study was conducted to investigate the effect(s) of these amendments on soil properties, nitrous oxide (N2O) and methane (CH4) emissions and grain and biomass yield of spring wheat (Triticum aestivum L.), and to produce background dataset that may be used to inform nutrient management guidelines for semiarid environments. METHODS: The experiment involved the application of biochar, straw or urea (46% nitrogen [N]) alone or their combinations. The treatments were: CN0-control (zero-amendment), CN50 -50 kg ha-1 N, CN100-100 kg ha-1 N, BN0 -15 t ha-1 biochar, BN50-15 t ha-1 biochar + 50 kg ha-1 N, BN100-15 t ha-1 biochar + 100 kg ha-1 N, SN0 -4.5 t ha-1 straw, SN50 -4.5 t ha-1 straw + 50 kg ha-1 N and SN100-4.5 t ha-1 straw + 100 kg ha-1 N. Fluxes of N2O, CH4 and grain yield were monitored over three consecutive cropping seasons between 2014 and 2016 using the static chamber-gas chromatography method. RESULTS: On average, BN100reported the highest grain yield (2054 kg ha-1), which was between 25.04% and 38.34% higher than all other treatments. In addition, biomass yield was much higher under biochar treated plots relative to the other treatments. These findings are supported by the increased in soil organic C by 17.14% and 21.65% in biochar amended soils (at 0-10 cm) compared to straw treated soils and soils without carbon respectively. The BN100treatment also improved bulk density and hydraulic properties (P < 0.05), which supported the above results. The greatest N2O emissions and CH4 sink were recorded under the highest rate of N fertilization (100 kg N ha-1). Cumulative N2O emissions were 39.02% and 48.23% lower in BN100 compared with CN0 and CN100, respectively. There was also a ≈ 37.53% reduction in CH4 uptake under BN100compared with CN0-control and CN50. The mean cumulative N2O emission from biochar treated soils had a significant decrease of 10.93% and 38.61% compared to straw treated soils and soils without carbon treatment, respectively. However, differences between mean cumulative N2O emission between straw treated soils and soils without carbon were not significant. These results indicate the dependency of crop yield, N2O and CH4 emissions on soil quality and imply that crop productivity could be increased without compromising on environmental quality when biochar is applied in combination with N-fertilizer. The practice of applying biochar with N fertilizer at 100 kg ha-1 N resulted in increases in crop productivity and reduced N2O and CH4soil emissions under dryland cropping systems.

Quantifying the interaction of water and radiation use efficiency under plastic film mulch in winter wheat.

Local natural resources, (e.g., precipitation, solar radiation) are important for developing environmentally and scientifically sound management practices in dryland agroecosystem. Maximizing water use efficiency (WUE) in dryland farming systems remains a challenge. The objectives of this study were to assessing the robustness of radiation use efficiency (RUE) during different periods and investigate the interaction between RUE and WUE from water loss pattern and canopy development during wheat growth under different agricultural practices (non-mulched control, CK; transparent film mulching, TF; and black film mulching, BF) from 2013 to 2016 on the Loess Plateau, Northwest China. Results showed that RUE was mainly improved during post-anthesis under PM treatments. PM treatments contributed to elevated canopy photosynthesis and a delayed RUE peak during the reproductive period. Due to the increased spike number and ratio of plant transpiration to soil evaporation, TF and BF treatments had relatively stable photosynthetic activity relative to the CK treatment even those during dry periods. Initially, no relationship was found between WUE and RUE under the CK treatment. On the other hand, RUE and WUE were positively related in TF and BF treatments following a power function. RUE values increased with WUE rapidly to stabilize at a plateau value of 5.5 g MJ-1 under TF and BF treatments, and thus, the wheat WUE had a higher improvement potential than RUE as it did not have an apparent plateau value. PM treatments enhanced the wheat production by taking full advantage of local solar radiation and precipitation (improving RUE and WUE). This higher use efficiency of resources produced more photoassimilates for wheat than that under the CK management, increased source size (LAI) and sink size (spike number) during wheat growth seasons, and thus increased the final grain yield.

Effect of Row Spacing and Seeding Rate on Russian Thistle (Salsola tragus) in Spring Barley and Spring Wheat.

Russian thistle (Salsola tragus L.) is a persistent post-harvest issue in the Pacific Northwest (PNW). Farmers need more integrated management strategies to control it. Russian thistle emergence, mortality, plant biomass, seed production, and crop yield were evaluated in spring wheat and spring barley planted in 18- or 36-cm row spacing and seeded at 73 or 140 kg ha-1 in Pendleton and Moro, Oregon, during 2018 and 2019. Russian thistle emergence was lower and mortality was higher in spring barley than in spring wheat. However, little to no effect of row spacing or seeding rate was observed on Russian thistle emergence or mortality. Russian thistle seed production and plant biomass followed crop productivity; higher crop yield produced higher Russian thistle biomass and seed production and lower crop yield produced lower weed biomass and seed production. Crop yield with Russian thistle pressure was improved in 2018 with 18-cm rows or by seeding at 140 kg ha-1 while no effect was observed in 2019. Increasing seeding rates or planting spring crops in narrow rows may be effective at increasing yield in low rainfall years of the PNW, such as in 2018. No effect may be observed in years with higher rainfall than normal, such as in 2019.

Drought, Climate Change, and Dryland Wheat Yield Response: An Econometric Approach.

Agriculture has been identified as one of the most vulnerable sectors affected by climate change. In the present study, we investigate the impact of climatic change on dryland wheat yield in the northwest of Iran for the future time horizon of 2041-2070. The Just and Pope production function is applied to assess the impact of climate change on dryland wheat yield and yield risk for the period of 1991-2016. The Statistical Downscaling Model (SDSM) is used to generate climate parameters from General Circulation Model (GCM) outputs. The results show that minimum temperature is negatively related to average yield in the linear model while the relationship is positive in the non-linear model. An increase in precipitation increases the mean yield in either model. The maximum temperature has a positive effect on the mean yield in the linear model, while this impact is negative in the non-linear model. Drought has an adverse impact on yield levels in both models. The results also indicate that maximum temperature, precipitation, and drought are positively related to yield variability, but minimum temperature is negatively associated with yield variability. The findings also reveal that yield variability is expected to increase in response to future climate scenarios. Given these impacts of temperature on rain-fed wheat crop and its increasing vulnerability to climatic change, policy-makers should support research into and development of wheat varieties that are resistant to temperature variations.

Late planting has great potential to mitigate the effects of future climate change on Australian rain-fed cotton.

The rain-fed cotton industry in Australia is vulnerable to climate change due to its high dependence on seasonal climate and summer rainfall. The rain-fed cotton in eastern Australia is increasingly being incorporated into cereal crop rotations due to government regulation of water resources, restricting opportunities for irrigated cotton. The accurate quantification of future climate impacts on exposed cropping systems such as rain-fed cotton is required to identify effective agronomic practices and inform strategic industry planning for the expansion of Australian cotton industry. Our study utilized 32 General Circulation Model (GCMs) for four cotton-growing regions representing the geographic range of cotton production in eastern Australia. We assessed the climate impacts on rain-fed cotton yield for two future periods (2040s and 2080s) under the RCP4.5 (low) and RCP8.5 (high) emissions scenarios employing the processed-based APSIM-Cotton model. Our results showed that current cotton yields varied with planting date, and the magnitude of yield change was consistent with regional climate variations at four locations representing the current geographic distribution of rain-fed cotton production. Means from multi-GCM ensemble showed growth period temperature increased more under RCP8.5 in the longer-term (2080s). Growth period rainfall changes had significantly positive effects on yield at all planting dates over each site. The projected increases in rainfall were more evident at later planting dates for dry sites than early planting dates at wet sites. In addition, we found planting date had the greatest influence on cotton yield at wet sites, while GCMs accounted for a large portion of variation in cotton yield at dry sites. We conclude that later planting has a great potential to increase rain-fed cotton yields. This provides important insights for regional-specific adaptation strategies for the rain-fed cotton industry in eastern Australia.

Isolation, characterization, and effect of phosphate-zinc-solubilizing bacterial strains on chickpea (Cicer arietinum L.) growth.

OBJECTIVE: Phosphate (P) and zinc (Zn) are essential plant nutrients required for nodulation, nitrogen-fixation, plant growth and yield. Mostly applied P and Zn nutrients in the soil are converted into unavailable form. A small number of soil microbes have the ability to transform unsolvable forms of P and Zn to an available form. P-Zn-solubilizing rhizobacteria are potential alternates for P and Zn supplement. In the present study, the effect of two P-Zn-solubilizing bacterial strains (Bacillus sp. strain AZ17 and Pseudomonas sp. strain AZ5) was evaluated on the growth of chickpea plant. METHODOLOGY: Both strains were purified from the rhizospheric soil of chickpea plant grown-up in sandy soil and rain-fed area (Thal desert). In vitro, both strains solubilize P and Zn as well both strain produce IAA and organic acids. In the field experiments, conducted in the rain-fed area, the positive influence of inoculation with both bacterial isolates AZ5 and AZ17 on chickpea growth was observed. RESULTS: The application of inoculum (strains AZ5 and AZ17) resulted in up to 17.47% and 17.34% increase in grain yield of both types of chickpea grown in fertilized and non-fertilized soil, respectively over non-inoculated control. Strain AZ5 was the most effective inoculum, increasing up to 17.47%, 16.04%, 26.32%, 22.53%, 26.12% and 22.59% in grain yield, straw weight, nodules number, dry weight of nodules, Zn uptake and P uptake respectively, over control. CONCLUSION: These results indicated that Pseudomonas sp. strain AZ5 and Bacillus sp. strain AZ17 can serve as effective microbial inocula for chickpea, particularly in the rain-fed area.

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Studying soil water dynamics is critical to agricultural production and ecological environment construction. Based on a 4-year field experiment, we measured soil moisture in both winter wheat and spring corn fields in rain-fed Changwu Tableland of the Loess Plateau from 2012 to 2015, explored soil desiccation and analyzed the effects of soil moisture on crop growth, the effect of precipitation on soil reservoir, and the effect of crop on soil water dynamics. The results showed that the dominant factor for the formation of dried soil layer was yearly precipitation pattern in winter wheat field and was uneven distribution of precipitation among months in each year in spring corn field. Permanent dried soil layer did not occur in both winter wheat and spring corn under the plan-ting system of one crop a year in rain-fed Changwu Tableland. Due to the characteristics of soil water circulation in the Loess Tableland, planting winter wheat was more suitable for this region compared to spring corn. Soil water availability in the Loess Tableland area could ensure the stability of crop yield. Under the influence of precipitation, soil reservoir in winter wheat was consecutively recharged from harvest period to fallow period to seedling period, while from slow consumption period to large consumption period, soil reservoir was consecutively consumed. Soil reservoir in the depth of 0-300 and 300-600 cm was inconsistent. If the maximum root depth was used as sampling depth when measuring soil moisture, evapotranspiration would be overestimated in the fallow period and the seedling period, but would be underestimated in the large consumption period and slow consumption period. This was mainly due to the negative feedbacks of deep soil reservoir. In winter wheat field, transition layer existed and ranged from 140-360 cm. Crop growth at different stages had an effect on soil reservoir. Soil reservoir showed inter-annual regulation effect on the water supply to winter wheat and intra-annual regulation effect on spring corn.

Evaluation of ACC-deaminase-producing rhizobacteria to alleviate water-stress impacts in wheat (Triticum aestivum L.) plants.

Application of plant-growth-promoting rhizobacteria (PGPR) is an environmentally sustainable option to reduce the effects of abiotic and biotic stresses on plant growth and productivity. Bacteria isolated from rain-fed agriculture field soils in the Central Himalaya Kumaun region, India, were evaluated for the production of 1-aminocyclopropane-1-carboxylic acid (ACC) deaminase. Those producing ACC deaminase in high amounts were evaluated for their potential to improve wheat (Triticum aestivum L.) plant growth under irrigated and water-stress conditions in two glasshouse experiments. Some of the isolates also showed other plant-growth-promoting (PGP) traits, e.g., N2 fixation, siderophore production, and phosphate solubilization; however, strains with higher ACC deaminase activity showed the greatest effects. These were Variovorax paradoxus RAA3; Pseudomonas spp. DPC12, DPB13, DPB15, DPB16; Achromobacter spp. PSA7, PSB8; and Ochrobactrum anthropi DPC9. In both simulated irrigated and water-stress conditions, a single inoculation of RAA3 and a consortium of DPC9 + DPB13 + DPB15 + DPB16 significantly improved wheat plant growth and foliar nutrient concentrations and caused significant positive changes in antioxidant properties compared with noninoculated plants especially under water stress. These findings imply that PGPB having ACC deaminase activity together with other PGP traits could potentially be effective inoculants to improve the growth of wheat plants in water-stressed rain-fed environments.

Modeling the impact of crop rotation with legume on nitrous oxide emissions from rain-fed agricultural systems in Australia under alternative future climate scenarios.

Limited information exists on potential impacts of climate change on nitrous oxide (N2O) emissions by including N2-fixing legumes in crop rotations from rain-fed cropping systems. Data from two 3-yr crop rotations in northern NSW, Australia, viz. chickpea-wheat-barley (CpWB) and canola-wheat-barley (CaWB), were used to gain an insight on the role of legumes in mitigation of N2O emissions. High-frequency N2O fluxes measured with an automated system of static chambers were utilized to test the applicability of Denitrification and Decomposition model. The DNDC model was run using the on-site observed weather, soil and farming management conditions as well as the representative concentration pathways adopted by the Intergovernmental Panel on Climate Change in its Fifth Assessment Report. The DNDC model captured the cumulative N2O emissions with variations falling within the deviation ranges of observations (0.88±0.31kgNha-1rotation-1 for CpWB, 1.44±0.02kgNha-1rotation-1 for CaWB). The DNDC model can be used to predict between modeled and measured N2O flux values for CpWB (n=390, RSR=0.45) and CaWB (n=390, RSR=0.51). Long-term (80-yr) simulations were conducted with RCP 4.5 representing a global greenhouse gas stabilization scenario, as well RCP 8.5 representing a very high greenhouse gas emission scenario based on RCP scenarios. Compared with the baseline scenarios for CpWB and CaWB, the long-term simulation results under RCP scenarios showed that, (1) N2O emissions would increase by 35-44% for CpWB and 72-76% for CaWB under two climate scenarios; (2) grain yields would increase by 9% and 18% under RCP 4.5, and 2% and 14% under RCP 8.5 for CpWB and CaWB, respectively; and (3) yield-scaled N2O-N emission would increase by 24-42% for CpWB and 46-54% for CaWB under climate scenarios, respectively. Our results suggest that 25% of the yield-scaled N2O-N emission would be saved by switching to a legume rotation under climate change conditions.

Balanced N and C input recommendations for rain-fed maize production in northern China based on N balances and grain yields.

BACKGROUND: This study aimed to assess longer-term (1993-2009) effects of combined applications of fertiliser, maize stover, and cattle manure on maize yields, partial nitrogen (N) and carbon (C) balances, and water and N-use efficiencies, to guide N and C input recommendations for rain-fed maize production in northern China. RESULTS: The field trial, with three factors at five levels and 12 treatments, was conducted at Shouyang Dryland-Farming Experimental Station, Shanxi, China. Data analysis revealed higher N balances but lower C balances significantly occurred in a dry year than in a wet year. Positive N balances related to higher N inputs resulted in higher soil available N, even downward to deep layers with increasing N inputs, while positive C balances due to higher C inputs could be benefit to increase soil organic C. Based on partial N balances and grain yields, N and C inputs at ranges of 100 kg N ha-1 and 1.9-2.9 Mg C ha-1 could be recommended for target yields of 6.7-7.2 Mg ha-1 in rain-fed maize production. CONCLUSION: The study suggests that N balances close to neutral be given priority to improving N-use efficiency, and more positive C balances also be important for sustaining target yields and soil fertility levels. © 2017 Society of Chemical Industry.

Potential impacts of climate change on carbon dynamics in a rain-fed agro-ecosystem on the Loess Plateau of China.

Although many studies have been conducted on crop yield in rain-fed agriculture, the possible impacts of climate change on the carbon (C) dynamics of rain-fed rotation systems, particularly their direction and magnitude at the long-term scale, are still poorly understood. In this study, the sensitivity of C dynamics of a typical rotation system to elevated CO2 and changed temperature and precipitation were first tested using the CENTURY model, based on data collected from a 30-year field experiment of a corn-wheat-wheat-millet (CWWM) rotation system in the tableland of the Loess Plateau. The possible responses of crop biomass C and soil organic C (SOC) accumulation were then evaluated under scenarios representing the Representative Concentration Pathways (RCPs) 4.5 and 8.5. The results indicated that elevated CO2 and increased precipitation exerted positive effect on biomass C in CWWM rotation system, while increasing the temperature by 1°C, 2°C and 4°C had negative effects on biomass C due to opposite responses of corn and winter wheat to warming. SOC accumulation was enhanced by increased CO2 concentration and precipitation but impaired by increased temperature. Under future RCP scenarios with dynamic CO2, the biomass C of corn exhibited decrease during the period of 2046-2075 under RCP4.5 and the period of 2016-2075 under RCP8.5 due to reduced precipitation and a warmer climate. In contrast, winter wheat would benefit from increased CO2 and temperature and was projected to have larger biomass C under both RCP scenarios. Although the climate condition had large differences between RCP4.5 and RCP8.5, the projected SOC had similar trends under two scenarios due to CO2 fertilizer effect and precipitation fluctuation. These results implied that crop biomass C and SOC accumulation in a warmer environment are strongly related to precipitation, and increase in field water storage should be emphasized in coping with future climate.