In semiarid dryland farming regions, No‐till and intensified crop rotations may improve water use. Our objective was to determine water use efficiency (WUE) and precipitation use efficiency (PUE) for ...spring wheat (Triticum aestivum L.; SW) grown in crop sequences representing different levels of intensification, under minimum (Min‐till) or No‐till. Root zone (0–122 cm) water at planting (SWP) was 2.76 cm higher for two‐ and three‐phase sequences under Min‐till than continuous spring wheat (CSW), and sequences with fallow averaged 2.65 cm higher than those without. Conversely, SWP was unaffected by sequence under No‐till, with less effect of fallow. Root zone water at harvest was unaffected by the number of crop phases or fallow under Min‐till. However, values for CSW exceeded the two‐ or three‐phase sequences by 1.57 and 2.53 cm under No‐till, and sequences without fallow averaged 1.52 cm more than those with fallow. The highest WUE (8.4 kg grain ha−1 mm−1 water) was observed when SW was grown in three‐phase sequences compared with 7.7 kg grain ha−1 mm−1 water, for CSW and SW‐fallow. Spring wheat under Min‐till had higher WUE in sequences with fallow, but no effects of fallow occurred with No‐till. The lowest PUE (near 3 kg grain ha−1 mm−1 precipitation) and no effects of tillage were found in sequences with fallow. However, SW in continuously cropped sequences had PUE between 5.5 and 6.4 kg grain ha−1 mm−1 precipitation and was higher under No‐till. Both WUE and PUE are affected by intensification but may also be influenced by patterns of weather.
Core Ideas
Profile water varied as an interaction between crop sequence and tillage.
With fallow, soil water changed little the winter prior to planting.
Crop water use and yields were lower under continuous cropping than with fallow.
Water use efficiency was highest for three‐phase sequences but varied with yield.
Continuous cropping resulted in more efficient use of precipitation over the study.
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FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
Tillage and cropping sequence may influence C and N sequestration, microbial activities, and N mineralization in dryland soil aggregates. We evaluated the 21‐yr effect of tillage and cropping ...sequence combinations on C and N fractions in aggregates of a Dooley sandy loam (fine‐loamy, mixed, superactive, frigid Typic Argiustolls) at the 0‐ to 20‐cm depth in eastern Montana. Tillage and cropping sequences were no‐tilled continuous spring wheat (NTCW) (Triticum aestivum L.), spring‐tilled continuous spring wheat (STCW), fall‐ and spring‐tilled continuous spring wheat (FSTCW), fall‐ and spring‐tilled spring wheat‐barley (Hordeum vulgare L.) (1984–1999) followed by spring wheat‐pea (Pisum sativum L.)(2000–2004)(FSTW‐B/P), and spring‐tilled spring wheat‐fallow (STW‐F). Carbon and N fractions were soil organic C (SOC), total N (STN), particulate organic C and N (POC and PON), microbial biomass C and N (MBC and MBN), potential C and N mineralization (PCM and PNM), NH4–N, and NO3–N. Aggregate proportion was greater in NTCW than in FSTCW in the 4.75‐ to 2.00‐mm aggregate‐size class at 0 to 5 cm but was greater in STW‐F than in STCW in the 2.00‐ to 0.25‐mm size class at 5 to 20 cm. After 21 yr, STW‐F reduced SOC, STN, POC, and PON concentrations in aggregates by 34 to 42% at 0‐ to 5‐cm and by 20 to 32% at 5‐ to 20‐cm compared with NTCW and STCW. The PCM and MBC were greater in NTCW and STCW than in STW‐F in the <2.00‐mm size class at 0 to 5 cm but MBN varied with treatments, aggregate‐size classes, and soil depths. Compared with other treatments, NH4–N concentration was lower in STW‐F in the 4.75‐ to 0.25‐mm size class but PNM and NO3–N were greater in FSTW‐B/P in the <2.00‐mm size class. Long‐term reduced tillage with continuous spring wheat increased soil aggregation, C and N sequestration, and microbial biomass and activities in all aggregates but increased tillage intensity with spring wheat‐barley/pea rotation increased N mineralization and availability in small aggregates compared with the conventional STW‐F.
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FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
The individual nitrogen (N) contribution from above-ground plant residue (AGRP) and total below-ground residuals (BGRT) to a subsequent wheat crop remains poorly explored. The need to understand this ...dynamic is crucial for optimizing crop yield and soil nutrient management.
This study aimed to discern the individual N contributions from AGRP and BGRT to a succeeding wheat crop and understand the implications of various grain legume residues on these contributions.
A four-year field study consisting of two 2-year grain legume–cereal cropping sequences was conducted in Saskatoon, SK, Canada. The grain legumes were chickpea, faba bean, lentil, and field pea, with spring wheat grown as the reference crop in 2014 and 2016. Each plot was split into quadrants with one quadrant receiving 15N-urea and the other three receiving non-labeled (natural abundance, NA) urea in spring of the pulse phase. After pulse harvest, 15N-AGRP was swapped with NA-AGRP when returned to the field, resulting in sub-plots with 15N-AGRP/NA-BGRT and NA-AGRP/15N-BGRT combinations. In 2015 and 2017 all plots were planted with spring wheat and were fertilized based on soil mineral N measurements and target yields. One NA quadrant received 15N-urea during the cereal phase to track the fate of fertilizer N versus legume N.
Grain legume residue species did not affect the seed yield of the subsequent wheat crop. However, wheat grown on lentil and pea residue required less N fertilizer than other residues. Over the five tested residues, BGRT (roots, rhizodeposits, residual fertilizer, and soil) was the largest N source, accounting for 70–91% of wheat N uptake, which surpassed the combination of the contribution from AGRP (1–11% of wheat N uptake) and fertilizer (5–21% of the wheat N uptake). Among BGR components, soil was the main N contributor to subsequent wheat. The N recovery rates for the wheat crop were below 9% for AGRP, 18% for BGRT, and 26% for fertilizer N.
Below-ground residue, particularly the soil, plays a pivotal role in regulating N supply to the succeeding wheat crop, overshadowing contributions from AGR and fertilizer.
This research underscores the significance of BGR, especially the soil, in N management for subsequent crops. Recognizing these dynamics can help tailor crop residue management strategies and optimize soil nutrient supply for subsequent crops.
•Quantified N contribution from above- and below-ground residues for five crops.•Lentil and pea residues enhance wheat N uptake due to rapid below-ground residue decomposition.•BGR, including roots and soil, is the primary N source (70–91%).•Above-ground residue provides limited N supply (1–11%).•Emphasizes BGR's pivotal role in sustainable N supply to crops.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Many of the irrigated spring wheat regions in the world are also regions with high poverty. The impacts of temperature increase on wheat yield in regions of high poverty are uncertain. A grain ...yield–temperature response function combined with a quantification of model uncertainty was constructed using a multimodel ensemble from two key irrigated spring wheat areas (India and Sudan) and applied to all irrigated spring wheat regions in the world. Southern Indian and southern Pakistani wheat‐growing regions with large yield reductions from increasing temperatures coincided with high poverty headcounts, indicating these areas as future food security ‘hot spots’. The multimodel simulations produced a linear absolute decline of yields with increasing temperature, with uncertainty varying with reference temperature at a location. As a consequence of the linear absolute yield decline, the relative yield reductions are larger in low‐yielding environments (e.g., high reference temperature areas in southern India, southern Pakistan and all Sudan wheat‐growing regions) and farmers in these regions will be hit hardest by increasing temperatures. However, as absolute yield declines are about the same in low‐ and high‐yielding regions, the contributed deficit to national production caused by increasing temperatures is higher in high‐yielding environments (e.g., northern India) because these environments contribute more to national wheat production. Although Sudan could potentially grow more wheat if irrigation is available, grain yields would be low due to high reference temperatures, with future increases in temperature further limiting production.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
Abstract
Out of 277 varieties, according to the complex of economically valuable characteristics, 72 were distinguished in 2017-2020, 2022, of which 20 varieties were intensive. Their average yield ...in the dry years of 2017 and 2020 is 305-354 g/m
2
(st. 260-283 g/m
2
), while the best of the collection were: Grenada, AC Pollet, Jin Mai 71, Greina, Toronit (380-442-502 g/m
2
). High potential yields are characterized by: Alabuga, Grenada, Kommissar, India 288, Remus (550-592-633 g/m
2
). In dry years, the environment index Ii is negative (-77; -48), in other years it is positive (10; 7) and quite pronounced in 2022 (106). Plasticity (lower ranks and their sums) is expressed in Grenada, Kommissar, Alabuga, Greina, AC Pollet. Positive effects on the reaction of the medium - Er, are well manifested in: India 288, Margarita, SSL 46-50, Grenada, Omskaya 41, Kedem, Tyumenskaya 25, Tyumenskaya 29; negative - in 3-4 media in Line (k-65021), UI Alta Blanca, Omskaya 36, Toronit, India 288, Jin Mai 71, reduce their value. The following varieties are distinguished with the complex of yield indices (5 pcs.): Grenada, AC Pollet, Omskaya 41, Greina, Toronit, Uralosibirskaya 2. The selected varieties are recommended for breeding for productivity.
The health-promoting effects of whole-grain wheat likely derive from phenolic compounds and other antioxidants that also make wheat a potential source of functional food ingredients. The objective of ...this study was to determine the effects of genotype and growing environment on the phenolic contents and antioxidant activities of alcohol-soluble extracts from commercial wheat cultivars. Total phenolic contents (TPCs), antioxidant activities (AOAs), and concentrations of six phenolic acids were measured in six red- and white-grained hard spring wheat genotypes grown at four diverse locations in Western Canada during the 2003 crop year. There were significant differences among genotypes and environments for TPC, AOA, and concentrations of all the phenolic acids measured. The predominant indicators of antioxidant potential, i.e., TPC, AOA, and ferulic acid (FA) concentration were highly intercorrelated (r > 0.72). For these indices, the Canada Western (CW) Red Spring wheat cultivars Neepawa and AC Elsa had the highest levels, whereas an analogous CW hard white spring wheat cultivar, AC Snowbird, had the lowest levels. Grain color did not appear to be a factor in the expression of antioxidant-related parameters. For both TPC and AOA, as well as for vanillic acid, syringic acid, and ferulic acid, environmental effects were considerably larger than genotype effects. Neither growing temperature nor rainfall from anthesis to maturity appeared to be related to the environmental variation that was observed. Genotype × environment interaction was small for all parameters compared with genotype and location effects and was significant only for TPC. Genotype variation for antioxidant properties indicates that it would be possible to select for these quantitative traits in a breeding program. However, the significant environmental variation observed would delay and/or complicate this process. Keywords: Wheat; genotype by growing location; antioxidant activity; total phenolic content; DPPH
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IJS, KILJ, NUK, PNG, UL, UM, UPUK
This study explores the potential of vegetation indices (VIs) for crop leaf area index (LAI) estimation, with a focus on comparing red-edge reflectance based (RE-based) and the visible reflectance ...based (VIS-based) VIs. Seven VIs were derived from multi-temporal RapidEye images to correlate with LAI of two crop species having contrasting leaf structures and canopy architectures: spring wheat (a monocot) and canola (a dicot) in northern Ontario, Canada. The relationship between LAI and the selected VIs (LAI-VI) was characterized using a semi-empirical model. The Markov Chain Monte Carlo (MCMC) sampling method was used to estimate the model parameters, including the extinction coefficient (KVI) and VI value for dense green canopy (VI∞). Results showed that crop-specific regression models were much closer to a generic regression model using the RE-based VIs than using the VIS-based VIs. Furthermore, the joint posterior probability distribution of the KVI and VI∞ of the RE-based VIs tended to converge for the two crops. This suggests that the RE-based VIs are not as sensitive to canopy structure, e.g., the average leaf angle (ALA), as the VIS-based VIs. This is also demonstrated by the sensitivity analyses using both PROSAIL simulations and field measurements. Hence, the RE-based VIs can be used to develop a more generic LAI estimation algorithm for different crops. Further studies are required to assess the impact of soil reflectance and other factors, such as illumination-target-viewing geometries and atmospheric conditions, on LAI retrieval.
•RapidEye vegetation indices were assessed for LAI estimation for two field crops.•Interference for LAI estimation using vegetation indices was assessed.•Red-edge indices reduce impacts due to leaf angle distribution.•A generic model for LAI estimation could be generated using red-edge based indices.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Drought is the most devastating abiotic stress which has significantly threatened global wheat production. The recent study was designed to evaluate the performance of eight exotic wheat lines ...through the Drought Spring Bread Wheat Yield Trial (DSBWYT), along with a local drought-tolerant check cultivar, Khirman, under water-stressed conditions based on agronomic and yield-related traits. The experiment was conducted during cropping season 2019–2020 in a randomized complete block design with three replications at the Nuclear Institute of Agriculture (NIA), Tando Jam, Pakistan. The analysis of variance revealed that there was a significant difference among the genotypes for all studied traits. The genotype DSBWYT-8 possessed better agronomic traits and growth features like early growth vigor and early ground cover. On the other hand, the genotype DSBWYT-4 performed better in yield and yield-related traits like main spike yield, grains per spike, and 1000-grains weight. Both genotype revealed excellent plot grain yield and harvest index and were not significantly different from each other. The cluster analysis grouped all the genotypes into three clades. The drought-tolerant local check cultivar Khirman clustered with genotypes DSBWYT-2, DSBWYT-4, and DSBWYT-8 thus, this clade can be regarded as drought tolerant. The second cluster comprised of two genotypes, i.e., DSBWYT-1 and DSBWYT-5, which performed relatively low as compared to genotypes present in the drought-tolerant cluster, whereas the genotypes DSBWYT-3, DSBWYT-6, and DSBWYT-7 clustered together to represent low yielding genotypes under drought condition as compared with the check cultivar Khirman. Based on these results, the genotypes DSBWYT-2, DSBWYT-4, and DSBWYT-8 can be recommended as the drought-tolerant genotypes.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
The intercropping system has shown great advantages in adverse environments due to balanced use of diverse resources and promotion of sustainable productivity. However, identifying an optimal ...intercropping practice is still urgently needed in resources-limited areas, i.e., some perennial legume crop and annual cereal crop intercropping in arid areas.
This study tested a hypothesis that spring wheat/alfalfa strip intercropping under irrigation could improve land and irrigation water uses compared to sole spring wheat or alfalfa, and, therefore, would ensure reliable agronomic and economic benefits in the arid areas.
A three years field experiment was conducted to investigate the yield performance, resource use and economic benefit of irrigated spring wheat/alfalfa strip intercropping in the inland arid area of northwestern China. The intercropping systems with different intercropping ratios were established, including four rows of alfalfa intercropped with twelve rows of spring wheat (W12A4) and with eight rows of spring wheat (W8A4), both of which were compared with sole spring wheat (SW) and sole alfalfa (SA). All these cropping systems were provided with irrigation at four levels: 450 (I450), 360 (I360), 270 (I270), and 180 mm (I180).
The grain yield of spring wheat first increased and then decreased with the decrease in irrigation amount, with maximum yield achieved at I360. However, dry matter yield of alfalfa decreased with decreasing irrigation amount. Land equivalent ratio (LER) of the intercropping system was 0.72–1.05, suggesting this intercropping may not effectively save farmland. The W12A4 had higher grain yield, total dry matter accumulation, LER, and irrigation water use efficiency than W8A4. Except for the establishing year, the intercropping system produced 3.37–39.82% higher net income than SW in the other two years. There were no difference in net income and output/input ratio between W12A4 and W8A4.
Spring wheat/alfalfa strip intercropping can be used as a productive and sustainable strategy in the arid areas, which can improve irrigation water use, produce higher grain and forage yield, and increase net income. The W12A4 with 360 mm irrigation could be extensively used in the inland arid area of northwestern China.
It is recommended that this spring wheat/alfalfa intercropping should be adopted in this and similar arid areas in the world to promote sustainable development of agriculture and animal husbandry in the context of increasing population, resource constraint and climate change.
•More intercropping practices are still urgently needed in resources-limited areas.•Spring wheat/alfalfa intercropping had higher irrigation water use efficiency than sole spring wheat.•The intercropping system produced more net income than sole spring wheat.•This intercropping system had less advantage for farmers in saving farmland.•Strip intercropping of 12-row spring wheat and 4-row alfalfa with 360-mm irrigation was recommended in arid areas.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Climate extremes, such as droughts or heat waves, can lead to harvest failures and threaten the livelihoods of agricultural producers and the food security of communities worldwide. Improving our ...understanding of their impacts on crop yields is crucial to enhance the resilience of the global food system. This study analyses, to our knowledge for the first time, the impacts of climate extremes on yield anomalies of maize, soybeans, rice and spring wheat at the global scale using sub-national yield data and applying a machine-learning algorithm. We find that growing season climate factors-including mean climate as well as climate extremes-explain 20%-49% of the variance of yield anomalies (the range describes the differences between crop types), with 18%-43% of the explained variance attributable to climate extremes, depending on crop type. Temperature-related extremes show a stronger association with yield anomalies than precipitation-related factors, while irrigation partly mitigates negative effects of high temperature extremes. We developed a composite indicator to identify hotspot regions that are critical for global production and particularly susceptible to the effects of climate extremes. These regions include North America for maize, spring wheat and soy production, Asia in the case of maize and rice production as well as Europe for spring wheat production. Our study highlights the importance of considering climate extremes for agricultural predictions and adaptation planning and provides an overview of critical regions that are most susceptible to variations in growing season climate and climate extremes.
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