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1
Peterson, Todd Andrews, Charles A. Shapiro, and A. Dale Flowerday. "Rainfall and previous crop effects on crop yields." American Journal of Alternative Agriculture 5, no. 1 (March 1990): 33–37. http://dx.doi.org/10.1017/s0889189300003209.
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AbstractAfield study was conducted between 1972 and 1982 to compare the effects of previous crop on row crop yields under rainfed conditions in eastern Nebraska. The objectives were to determine the effects of fallow and three previous crops: corn (Lea. maysLJ, soybeans /Glycine max (L.) Mem], and grain sorghum /Sorghum bicolor (L.) Moench], on the growth and grain yield of the same crops. The study was conducted on a Sharpsburg silty clay loam (fine, montmorillonitic, mesicf Typic Argiudoll). Corn grain yield was most variable (C. V. 23.4percent) compared to soybean (C. V. 13.6percent) or grain sorghum (C. V. 9.5 percent) yields. Corn was also the most sensitive crop to previous crop effects. The range of treatment yields for each crop was 47 percent, 22 percent, and 11 percent of the overall means for corn, soybean, and sorghum, respectively. Previous crop affected yields for all crops, but the effects were not consistent across years. All crops produced highest yield following fallow. Yields of corn, soybean, and grain sorghum following fallow were 74, 25, and 10 percent higher than their respective monoculture yields. In years of average precipitation, a corn-soybean sequence produced the greatest yield. In years having above- or below-normal precipitation, a grain sorghum-soybean sequence produced the highest yield.
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Angus, J. F., J. A. Kirkegaard, J. R. Hunt, M. H. Ryan, L. Ohlander, and M. B. Peoples. "Break crops and rotations for wheat." Crop and Pasture Science 66, no. 6 (2015): 523. http://dx.doi.org/10.1071/cp14252.
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Wheat crops usually yield more when grown after another species than when grown after wheat. Quantifying the yield increase and explaining the factors that affect the increase will assist farmers to decide on crop sequences. This review quantifies the yield increase, based on >900 comparisons of wheat growing after a break crop with wheat after wheat. The mean increase in wheat yield varied with species of break crop, ranging from 0.5 t ha–1 after oats to 1.2 t ha–1 after grain legumes. Based on overlapping experiments, the observed ranking of break-crop species in terms of mean yield response of the following wheat crop was: oats < canola ≈ mustard ≈ flax < field peas ≈ faba beans ≈ chickpeas ≈ lentils ≈ lupins. The mean additional wheat yield after oats or oilseed break crops was independent of the yield level of the following wheat crop. The wheat yield response to legume break crops was not clearly independent of yield level and was relatively greater at high yields. The yield of wheat after two successive break crops was 0.1–0.3 t ha–1 greater than after a single break crop. The additional yield of a second wheat crop after a single break crop ranged from 20% of the effect on a first wheat crop after canola, to 60% after legumes. The mean yield effect on a third wheat crop was negligible, except in persistently dry conditions. The variability of the break-crop effect on the yield of a second wheat crop was larger than of a first wheat crop, particularly following canola. We discuss the responses in relation to mechanisms by which break crops affect soil and following crops. By quantifying the magnitude and persistence of break-crop effects, we aim to provide a basis for the decision to grow continuous cereal crops, strategic rotations or tactically selected break crops. In many wheat-growing areas, the large potential yield increases due to break crops are not fully exploited. Research into quantifying the net benefits of break crops, determining the situations where the benefits are greatest, and improving the benefits of break crops promises to improve the efficiency of wheat-based cropping systems.
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Evans, J., G. Scott, D. Lemerle, A. Kaiser, B. Orchard, G. M. Murray, and E. L. Armstrong. "Impact of legume 'break' crops on the yield and grain quality of wheat and relationship with soil mineral N and crop N content." Australian Journal of Agricultural Research 54, no. 8 (2003): 777. http://dx.doi.org/10.1071/ar02224.
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The effect of annual 'break' crops on the yield and protein content of wheat was investigated over 3 seasons on a Red Kandasol on the south-western slopes of New South Wales. The 'break' crops included lupin and pea grown for grain, pea and vetch managed for silage, clovers managed for silage or hay, and vetch and clovers managed for green manuring. Wheat was sown for 2 years following the legume year, or canola and wheat followed the legumes. Averaged over 3 experiments the yields of first crop wheat following pea or vetch silage crops were comparable with those after grain pea. Yields following clover forage conservation crops or green manures exceeded those after grain pea by at least 0.41 t/ha; average yield increase after clover green manure was 0.93 t/ha. In one experiment, yields of second crop wheat were greater, by up to 0.37 t/ha, after forage conservation or green manure legume 'breaks' than after grain legumes. In 2 experiments, second crop wheat yields were greater after a first crop of canola than a first crop of wheat. Compared with continuous wheat yield, aggregate mean wheat yield increases were 3.5–4 t/ha following grain legumes, pea, and vetch silage crops, but 5.3–6.3 t/ha following clover forage conservation and green manure crops. However, the relative effects of legume treatments on wheat yield were significantly seasonally dependent. Yield and grain protein variation in wheat after legumes was significantly correlated with variation in mineral N at wheat establishment. However, in one experiment, yield was correlated only with variation in mineral N below the 20-cm soil depth, whereas protein was correlated only with variation in mineral N above the 20 cm soil depth. Yield increases in first crop wheat did not occur at the expense of grain protein.
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Li, Zhonghe, Chesheng Zhan, Shi Hu, Like Ning, Lanfang Wu, and Hai Guo. "Evaluation of global gridded crop models (GGCMs) for the simulation of major grain crop yields in China." Hydrology Research 53, no. 3 (March 1, 2022): 353–69. http://dx.doi.org/10.2166/nh.2022.087.
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Abstract Multimodel ensembles are powerful tools for evaluating agricultural production. Multimodel simulation results provided by the Global Gridded Crop Model Intercomparison (GGCMI) facilitate the evaluation of the grain production situation in China. With census crop yield data, the performance of nine global gridded crop models (GGCMs) in China was evaluated, and the yield gaps of four crops (maize, rice, soybean, and wheat) were estimated. The results showed that GGCMs better simulated maize yields than those of other crops in the northeast, north, northwest, east, and center. GEPIC (CLM-CROP) performed best in simulating maize (wheat) yield in the north, east, and northwest (southwest and south), due to reasonable parameter (cultivar and phenology parameters) settings. Because the rice phenology parameters were calibrated against phenological observation networks and a simple nitrogen limitation index was introduced, ORCHIDEE-CROP performed well in rice yield simulation and soybean yield simulation (center and southwest). Among four crops, wheat has the largest yield gap (7.3–14.1%), in which the poor soil of northwest (14.1%) exposes wheat to relatively high nutritional stress. Thus, in northwest China, optimizing nitrogen management in wheat production can effectively mitigate the negative impact of climate change on crop production.
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Li, Wei, Philippe Ciais, Elke Stehfest, Detlef van Vuuren, Alexander Popp, Almut Arneth, Fulvio Di Fulvio, et al. "Mapping the yields of lignocellulosic bioenergy crops from observations at the global scale." Earth System Science Data 12, no. 2 (April 2, 2020): 789–804. http://dx.doi.org/10.5194/essd-12-789-2020.
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Abstract. Most scenarios from integrated assessment models (IAMs) that project greenhouse gas emissions include the use of bioenergy as a means to reduce CO2 emissions or even to achieve negative emissions (together with CCS – carbon capture and storage). The potential amount of CO2 that can be removed from the atmosphere depends, among others, on the yields of bioenergy crops, the land available to grow these crops and the efficiency with which CO2 produced by combustion is captured. While bioenergy crop yields can be simulated by models, estimates of the spatial distribution of bioenergy yields under current technology based on a large number of observations are currently lacking. In this study, a random-forest (RF) algorithm is used to upscale a bioenergy yield dataset of 3963 observations covering Miscanthus, switchgrass, eucalypt, poplar and willow using climatic and soil conditions as explanatory variables. The results are global yield maps of five important lignocellulosic bioenergy crops under current technology, climate and atmospheric CO2 conditions at a 0.5∘×0.5∘ spatial resolution. We also provide a combined “best bioenergy crop” yield map by selecting one of the five crop types with the highest yield in each of the grid cells, eucalypt and Miscanthus in most cases. The global median yield of the best crop is 16.3 t DM ha−1 yr−1 (DM – dry matter). High yields mainly occur in the Amazon region and southeastern Asia. We further compare our empirically derived maps with yield maps used in three IAMs and find that the median yields in our maps are > 50 % higher than those in the IAM maps. Our estimates of gridded bioenergy crop yields can be used to provide bioenergy yields for IAMs, to evaluate land surface models or to identify the most suitable lands for future bioenergy crop plantations. The 0.5∘×0.5∘ global maps for yields of different bioenergy crops and the best crop and for the best crop composition generated from this study can be download from https://doi.org/10.5281/zenodo.3274254 (Li, 2019).
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Zscheischler, Jakob, Rene Orth, and Sonia I. Seneviratne. "Bivariate return periods of temperature and precipitation explain a large fraction of European crop yields." Biogeosciences 14, no. 13 (July 11, 2017): 3309–20. http://dx.doi.org/10.5194/bg-14-3309-2017.
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Abstract. Crops are vital for human society. Crop yields vary with climate and it is important to understand how climate and crop yields are linked to ensure future food security. Temperature and precipitation are among the key driving factors of crop yield variability. Previous studies have investigated mostly linear relationships between temperature and precipitation and crop yield variability. Other research has highlighted the adverse impacts of climate extremes, such as drought and heat waves, on crop yields. Impacts are, however, often non-linearly related to multivariate climate conditions. Here we derive bivariate return periods of climate conditions as indicators for climate variability along different temperature–precipitation gradients. We show that in Europe, linear models based on bivariate return periods of specific climate conditions explain on average significantly more crop yield variability (42 %) than models relying directly on temperature and precipitation as predictors (36 %). Our results demonstrate that most often crop yields increase along a gradient from hot and dry to cold and wet conditions, with lower yields associated with hot and dry periods. The majority of crops are most sensitive to climate conditions in summer and to maximum temperatures. The use of bivariate return periods allows the integration of non-linear impacts into climate–crop yield analysis. This offers new avenues to study the link between climate and crop yield variability and suggests that they are possibly more strongly related than what is inferred from conventional linear models.
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Eisenhut, Marion, and Andreas P. M. Weber. "Improving crop yield." Science 363, no. 6422 (January 3, 2019): 32–33. http://dx.doi.org/10.1126/science.aav8979.
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Brown, Alastair. "Crop-yield drivers." Nature Climate Change 4, no. 12 (November 26, 2014): 1050. http://dx.doi.org/10.1038/nclimate2458.
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Tsolmon, Nyamdavaa, and Friedel K. Jürgen. "Tuber yield parameters in organic potato production with green manures as preceding crop, catch crop and with farmyard manure." Mongolian Journal of Agricultural Sciences 17, no. 1 (January 3, 2017): 21–26. http://dx.doi.org/10.5564/mjas.v17i1.722.
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The effect of different preceding crops, catch crops and manure application on the agronomic performance of potato was studied in two consequential years in an organic farming system. Within the study the effect of three different preceding crops: viz. lucerne, field pea and spring barley; incorporated catch crops as green manure: non-legume or mixture; and farmyard manure (30 tones ha-1) are tested on subsequent potato yield and tuber size distribution. The catch crop treatments were studied in comparison to control bare fallow. The subsequent crop response to preceding crops was negligible since there was no indication of a greater tuber yields (fresh tuber, marketable and dry matter) after legume pre-crops compared to barley. Catch crops and manure effects both slightly increased tuber dry matter yield from 4.9 tones ha-1 to 5.2 tones ha-1 in 2010 only, on the contrary dry matter yield was not affected by catch crop and manure in 2011. The significant interaction effect was found between year and catch crop for fresh and dry matter tuber yield and non-standard small sized tubers. Catch crops had a positive effect on potato yield only in 2010 when mineral nitrogen availability was low. The catch crops significantly (P < 0.01) increased the percentage of large sized tubers (> 65 mm in diameter); however catch crops even negatively affected potato medium sized tuber yield and quality. Significant (P < 0.01) interaction effect was found between year and catch crop for small sized tubers, also.
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Husain, Dr Mohammad, and Dr Rafi Ahmad Khan. "Date Palm Crop Yield Estimation – A Framework." International Journal of Innovative Research in Computer Science & Technology 7, no. 6 (November 2019): 143–46. http://dx.doi.org/10.21276/ijircst.2019.7.6.1.
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Parker, Joyce E., David W. Crowder, Sanford D. Eigenbrode, and William E. Snyder. "Trap crop diversity enhances crop yield." Agriculture, Ecosystems & Environment 232 (September 2016): 254–62. http://dx.doi.org/10.1016/j.agee.2016.08.011.
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TeKrony, Dennis M., and Dennis B. Egli. "DOES SEED VIGOR INFLUENCE CROP YIELD?" HortScience 26, no. 6 (June 1991): 797A—797. http://dx.doi.org/10.21273/hortsci.26.6.797a.
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Both seed viability and vigor directly affect the performance of seeds planted to regenerate the crop. Although seed quality can influence many aspects of performance (e.g., total emergence, rate of emergence), this presentation will primarily examine the relationship of seed vigor to one aspect of performance - crop yield. Reductions in yield can be indirectly related to low seed vigor if the low vigor seed results in plant populations that are below a critical level. Thus, we investigated the direct effects of seed vigor on yield in the absence of population differences for annual crops that are harvested at three stages; during vegetative growth, early reproductive growth or at full reproductive maturity. Seed vigor affects vegetative growth and is frequently related to yield in crops that are harvested during vegetative growth or during early reproductive growth. However, there is usually no relationship between vigor and yield in crops harvested at full reproductive maturity because seed yields at full reproductive maturity are usually not closely associated with vegetative growth. The use of high vigor planting seed can be justified for all crops; however, to insure adequate plant populations over the wide range of field conditions which occur during emergence.
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Soriano, Imelda, and Georges Reversat. "Management of Meloidogyne graminicola and yield of upland rice in South-Luzon, Philippines." Nematology 5, no. 6 (2003): 879–84. http://dx.doi.org/10.1163/156854103773040781.
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AbstractMeloidogyne graminicola, the rice root-knot nematode, has become a constraint on Asian rice production due to rice cropping intensification and increasing scarcity of water. This work relates to the assessment of crop rotation, fallow and nematicide treatments in naturally infested fields to manage M. graminicola populations and prevent yield losses. One or two consecutive crops of cowpea or seasons of fallow before a rice crop lowered nematode populations and improved rice yield by 30-80%. Methyl bromide was used to determine yield potential and almost eradicated the nematode, trebling rice yield. Carbofuran improved yield of the first rice crop but did not affect the second rice crop. Due to its short life cycle, M. graminicola populations were similar after only a single rice crop and after three consecutive crops. It is recommended that, to ensure higher rice yields, M. graminicola populations should be maintained at low density by non-host crop rotations or fallows, ideally for two seasons before planting rice.
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PEGOVA, N. A. "YIELD AND PHYTOSANITARY STATE OF THE LAST CROPS OF THE CROP ROTATION OF WHEAT AND BARLEY." Izvestiâ Timirâzevskoj selʹskohozâjstvennoj akademii, no. 1 (2022): 61–70. http://dx.doi.org/10.26897/0021-342x-2022-1-61-70.
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The article shows the analysis of the effect of long-term application (since 2006) of nonmoldboard and combined systems of main tillage in a crop rotation in comparison with annual moldboard tillage on productivity of spring wheat, yield and phytosanitary state of barley. The author studied tillage options in a cereal-grass rotation (71% cereals) with different types of fallow (clean, manured, clover and mustard) and with winter rye straw left in the field. Annual mouldboard tillage resulted in the highest yields of spring wheat and barley in the experiment – 2.90 and 2.31 t/ha. Annual nonmoldboard tillage resulted in a significant reduction in wheat yield to 2.61 t/ha and barley yield to 1.28 t/ha. The combined tillage system, alternating two mouldboard and four nonmoldboard treatments per rotation, ensured the wheat yield at the level of the mouldboard system – 2.82 t/ha, and a decrease in barley yields to 1.85 t/ha. In 2020, the limiting factor for barley yield formation in the variants with surface distribution of crop residues and straw was increased weed infestation and deterioration of the phytosanitary state of the crop. Straw had a depressive effect on the yield of the last crops in a crop rotation with pure fallow. Crop yields decreased by 0.43 and 0.26 t/ha. Wheat yield was 2.34 t/ha, barley yield was 1.41 t/ha. Green manure mustard and clover fallows leveled the depressive effect of straw. The yields of the 6th and 7th crops of the crop rotation were at the control level (2.69–2.78 t/ha of wheat and 1.70–1.81 t/ha of barley). Regardless of the tillage system and the use of by-products as organic fertilizer, the application of manure ensured the highest yields of the final crops of the rotation: 3.10 and 2.99 t/ha for spring wheat and 2.00 and 2.14 t/ha for barley.
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WRIGHT, E., M. K. V. CARR, and P. J. C. HAMER. "Crop production and water-use. IV. Yield functions for sugarbeet." Journal of Agricultural Science 129, no. 1 (August 1997): 33–42. http://dx.doi.org/10.1017/s0021859697004498.
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The water-use model (watyield) was used to estimate a number of variables which were then related to the actual yields recorded in long term sugarbeet experiments carried out at several sites in England over the last 30–40 years. Nine functions were developed which are based on yield/water-input, yield/crop evaporation and (the equivalent of) relative yield/relative crop evaporation relationships. In all cases, highly significant linear correlations were obtained but the levels of precision, and degree of site specificity, varied. For irrigation planning and water allocation, three approaches are recommended with increasing sophistication and, in general, precision. These are (1) relating yield increases to the estimated irrigation need; (2) relating actual yields to crop evaporation totals; and (3) determining actual yields for rainfed and irrigated crops from the calculated seasonal totals of the ‘effective’ solar radiation intercepted by the crop canopy. These values can be estimated with the model using standard weather and soil physical data appropriate to the locality and the crop.
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Garba, Ismail Ibrahim, and Alwyn Williams. "Integrating Diverse Cover Crops for Fallow Replacement in a Subtropical Dryland: Implications on Subsequent Cash Crop Yield, Grain Quality, and Gross Margins." Agronomy 13, no. 1 (January 16, 2023): 271. http://dx.doi.org/10.3390/agronomy13010271.
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Integrating cover cropping into crop–fallow rotation has been considered a key component of ecological intensification that could mitigate negative productivity and sustainability challenges associated with conventional fallow practices. However, the adoption of cover crops in water-limited environments has been limited by potential soil water and nitrogen (N) costs and resulting yield penalties. We examined the impacts of diverse cover crops on fallow soil water and mineral N dynamics and the legacy impacts on subsequent cash crop productivity and profitability. The cover crops used (forage oat—Avena sativa L. [grass], common vetch—Vicia sativa subsp. sativa L.)/fababean—Vicia faba L. [legume], forage rape—Brassica napus L. [brassica]) differed in functional traits related to growth, phenology, and soil water and N acquisition and use strategies. We found that grass-associated cover crops generally supported higher cash crop grain yield and profit than brassica- or legume-associated cover crops, mainly due to moderate biomass accumulation and water use and persistent groundcover. Cash crop grain yields increased by +19% and +23% following forage oat cover crop, with concomitant gains in gross margins of +96$ ha−1 and +318$ ha−1 for maize and winter wheat compared to conventional fallow. In contrast, maize grain yield following brassica-associated cover crops ranged from +8 to −21% and reduced gross margins by −229 to −686$ ha−1 relative to conventional fallow. Legume- and brassica-associated cover crops had the lowest mungbean and winter wheat grain yield and gross margins compared to conventional fallow and the added stubble. Cash crop yields were related to cover crop biomass production, biomass N accumulation, residue carbon to N ratio, and legacy impacts through effects on soil water availability at cash crop sowing. Given the additional grain yield and gross margin benefits following grass-associated cover crops, they may provide a potential alternative fallow soil water and N management option that could improve crop productivity and cropping system resilience in water-limited environments.
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Jelodar, N. B. "Yield, yield components and physico-chemical characters of the ratoon crop of Iranian rice cultivars." Acta Agronomica Hungarica 53, no. 3 (October 1, 2005): 329–37. http://dx.doi.org/10.1556/aagr.53.2005.3.10.
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The ratooning ability of five Iranian rice cultivars and the grain quality of the ratoon crop were evaluated in a randomized complete block design with four replications in consecutive years from 1999 to 2001 to select promising lines for economical ratoon culture. The main crop was harvested by cutting 30 cm above the soil surface for regrowth of the second (ratoon) crop. The ratoon grain yields (kg/ha) varied greatly among the cultivars, ranging from 144.9 (Haseni) to 1472.1 (Sang-e-Tarom). In general, the ratoon crops had fewer fertile spikelets, fewer spikelets per panicle, shorter panicle length and fewer primary and secondary branches per panicle than the main crop. The gelatinization temperature and gel consistency of rice grains from ratoon crops were lower than those of the main crops. The amylose content (%) of the grains from ratoon crops varied from 23.1 (Sang-e-Tarom) to 21.4 (Dailamani).
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Péter Pepó. "Role of some agrotechnical elements in the precision crop technology of cereals." Acta Agraria Debreceniensis, no. 49 (November 13, 2012): 241–44. http://dx.doi.org/10.34101/actaagrar/49/2534.
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The crop models and precision technology have an important role in the development of winter wheat and maize agrotechnics, which crops have determinative role in Hungarian crop production. The effects of agrotechnical elements (crop rotation, fertilization, irrigation, crop protection, plant density) were studied in our longterm experiments on chernozem soil. Our scientific results proved that the high yields, and good yield stability were obtained in the input-intensive crop models. Maize had lower ecological adaptive capacity than winter wheat. The optimatization of agrotechnical elements reduces the harmful climatic effects so we can increase the yield and yield stability of cereals agro-ecosystems. The yields of wheat varied between 2 and 7 t ha-1 in extensive and 8 and 10 t ha-1 in intensive crop models and the yields of maize ranged between 2 and 11 t ha-1 and 10 and 15 t ha-1, respectively.
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Oliveira, P., A. S. Nascente, J. Kluthcouski, and T. A. P. Castro. "Corn and soybean yields as affected by cover crops and herbicide timing under no-tillage system." Planta Daninha 31, no. 4 (December 2013): 939–46. http://dx.doi.org/10.1590/s0100-83582013000400020.
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To achieve better results in the no-tillage system (NTS), it is important to properly manage the cover crop prior to planting by using herbicides, usually glyphosate. The effect of glyphosate on plant coverage is slow, and plants take a few days to die completely. Thus, when applying the herbicide on the same day of planting soybean or corn, cover crops are still alive and standing, causing initial shading on seedlings of the crop and delaying its establishment. Therefore, this study aimed to evaluate the effect of distinct cover crops and their timing of desiccation prior to planting soybean or corn, on crop yield and yield components. Two experiments were installed, one for soybean and another for corn. Each experiment consisted in combining three cover crops (Brachiaria brizantha, common bean or millet) chemically desiccated at two timings before planting the crop (15 or 0 days before planting) under no-tillage system (NTS). Experiments were installed in a completely randomized block design with five replications. Brachiaria brizantha produced the highest amount of biomass; common bean and millet as cover crops allowed higher soybean grain yields; herbicide application under common bean, millet and Brachiaria brizantha 15 days before planting soybean allowed higher crop grain yields; desiccation timing of common bean did not affect corn grain yield; Brachiaria brizantha should be desiccated 15 days before planting corn to allow maximum grain yield; when millet was used as a cover crop, glyphosate application at planting of corn allowed the highest grain yield.
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Karuna, G., K. Pravallika, K. Anuradha, and V. Srilakshmi. "Convolutional and Spiking Neural Network Models for Crop Yield Forecasting." E3S Web of Conferences 309 (2021): 01162. http://dx.doi.org/10.1051/e3sconf/202130901162.
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Prediction of Crop yield focuses primarily on agriculture research which will have a significant effect on making decisions such as import-export, pricing and distribution of specific crops. Predicting accurately with well-timed forecasts is important, but it is a difficult task due to numerous complex factors. Mostly crops like wheat, rice, peas, pulses, sugar cane, tea, cotton, green houses, corn, and soybean can all be used to forecast crop yields. We considered corn dataset to predict the yield for 13 different states in United States. Crop development and progression are strongly affected by climatic changes and unpredictability. Predicting crop yield well before harvest time will support farmers for selling and storing their crops. Agriculture involves large datasets and knowledge processes. Factors such as Weather Components, Soil Components, Management practices, genotype and their interactions are used in predicting Corn Yield. Precise crop growth generally necessitates a complete overview of the functional correlations between yield and all these interactive variables, which necessitates the use of large datasets and complex algorithms to demonstrate. Various Machine Learning models, Deep Learning models, and Artificial Neural Network algorithms are used for predicting. Deep Neural Network Models such as Convolution Neural Networks (CNN), Spiking Neural Networks (SNN), and Recurrent Neural Networks (RNN) are used to assess corn yield. Integrating CNN, RNN and SNN models outperformed than individual model performance.
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Shirsath, Paresh B., Vinay Kumar Sehgal, and Pramod K. Aggarwal. "Downscaling Regional Crop Yields to Local Scale Using Remote Sensing." Agriculture 10, no. 3 (March 2, 2020): 58. http://dx.doi.org/10.3390/agriculture10030058.
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Local-scale crop yield datasets are not readily available in most of the developing world. Local-scale crop yield datasets are of great use for risk transfer and risk management in agriculture. In this article, we present a simple method for disaggregation of district-level production statistics over crop pixels by using a remote sensing approach. We also quantified the error in the disaggregated statistics to ascertain its usefulness for crop insurance purposes. The methodology development was attempted in Parbhani district of Maharashtra state with wheat and sorghum crops in the winter season. The methodology uses the ratio of Enhanced Vegetation Index (EVI) of pixel to total EVI of the crop pixels in that district corresponding to the growth phase of the crop. It resulted in the generation of crop yield maps at the 500 m resolution pixel (grid) level. The methodology was repeated to generate time-series maps of crop yield. In general, there was a good correspondence between disaggregated crop yield and sub-district level crop yields with a correlation coefficient of 0.9.
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Zablotowicz, Robert M., Krishna N. Reddy, L. Jason Krutz, R. Earl Gordon, Ryan E. Jackson, and Leslie D. Price. "Can Leguminous Cover Crops Partially Replace Nitrogen Fertilization in Mississippi Delta Cotton Production?" International Journal of Agronomy 2011 (2011): 1–9. http://dx.doi.org/10.1155/2011/135097.
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Petroleum prices impact cotton nitrogen (N) fertilization cost. A field study was conducted from 2005 to 2007 to assess the interactions of cover crop (none, Austrian winter pea (Pisum sativumspp.arvense) or hairy vetch (Vicia villosaRoth)) and N fertilization (0, 67 or 134 kg N/ha applied at planting) on N availability and cotton yield under reduced-tillage management. Nitrogen content in desiccated residues averaged 49, 220, and 183 kg N/ha, in no cover crop, Austrian winter pea, and hairy vetch, respectively. Seventy percent of N in the above ground cover crop was derived from biological N fixation. In 2005, cover crops decreased cotton yield, while fertilizer N had no effect. In 2006, cover crops did not affect yield, but yield was positively correlated with N rate. In 2007, in no N plots, cotton yields were 65% higher in cover crops than in no cover crop. However, yield from N fertilized cover crop plots were similar to N fertilized no cover plots. These results indicate that leguminous cover crops can provide over 150 kg N/ha, but this N may not be as effective as fertilizer N for lack of synchronization between cotton N requirements and N release from residues.
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Zhu, Yongbin, Yajuan Shi, Changxin Liu, Bing Lyu, and Zhenbo Wang. "Reinspecting the Climate-Crop Yields Relationship at a Finer Scale and the Climate Damage Evaluation: Evidence from China." Complexity 2020 (September 17, 2020): 1–8. http://dx.doi.org/10.1155/2020/9424327.
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This paper reinvestigated the climate-crop yield relationship with the statistical model at crops’ growing stage scale. Compared to previous studies, our model introduced monthly climate variables in the production function of crops, which enables separating the yield changes induced by climate change and those caused by inputs variation and technique progress, as well as examining different climate effects during each growing stage of crops. By applying the fixed effect regression model with province-level panel data of crop yields, agricultural inputs, and the monthly climate variables of temperature and precipitation from 1985 to 2015, we found that the effects of temperature generally are negative and those of precipitation generally are positive, but they vary among different growth stages for each crop. Specifically, GDDs (i.e., growing degree days) have negative effects on spring maize’s yield except for the sowing and ripening stages; the effects of precipitation are negative in September for summer maize. Precipitation in December and the next April is significantly harmful to the yield of winter wheat; while, for the spring wheat, GDDs have positive effects during April and May, and precipitation has negative effects during the ripening period. In addition, we computed climate-induced losses based on the climate-crop yield relationship, which demonstrated a strong tendency for increasing yield losses for all crops, with large interannual fluctuations. Comparatively, the long-term climate effects on yields of spring maize, summer maize, and spring wheat are more noticeable than those of winter wheat.
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Arumugam, Surendran, Ashok K.R., Suren N. Kulshreshtha., Isaac Vellangany, and Ramu Govindasamy. "Yield variability in rainfed crops as influenced by climate variables." International Journal of Climate Change Strategies and Management 7, no. 4 (November 16, 2015): 442–59. http://dx.doi.org/10.1108/ijccsm-08-2013-0096.
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Purpose – This paper aims to explore the impact of climate change on yields and yield variances in major rainfed crops and measure possible changes in yields under projected climate changes in different agro-climatic zones of Tamil Nadu, India. Although many empirical studies report the influence of climate change on crop yield, only few address the effect on yield variances. Even in such cases, the reported yield variances were obtained through simulation studies rather than from actual observations. In this context, the present study analyzes the impact of climate change on crops yield and yield variance using the observed yields. Design/methodology/approach – The Just-Pope yield function (1978) is used to analyze the impact of climate change on mean yield and variance. The estimated coefficient from Just-Pope yield function and the projected climatic data for the year 2030 are incorporated to capture the projected changes in crop yield and variances. Findings – By the year 2030, the yield of pulses is estimated to decline in all the zones (Northeast, Northwest, Western, Cauvery delta, South and Southern zones), with significant declines in the Northeast zone (6.07 per cent), Cauvery delta zone (3.55 per cent) and South zone (3.54 per cent). Sorghum yield may suffer more in Western zone (2.63 per cent), Southern zone (1.92 per cent) and Northeast zone (1.62 per cent). Moreover, the yield of spiked millet is more likely to decrease in the Southern zone (1.39 per cent), Northeast zone (1.21 per cent) and Cauvery delta zone (0.24 per cent), and the yield of cotton may also decline in the Northeast zone (12.99 per cent), Northwest zone (8.05 per cent) and Western zone (2.10 per cent) of Tamil Nadu, India. Originality/value – The study recommends introducing appropriate crop insurance policies to address possible financial losses to the farmers. Prioritizing area-specific stress-tolerant crop varieties without complementing yield would sustain crops cultivation further.
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Carrera, Lidia M., Aref A. Abdul-Baki, and John R. Teasdale. "Cover Crop Management and Weed Suppression in No-tillage Sweet Corn Production." HortScience 39, no. 6 (October 2004): 1262–66. http://dx.doi.org/10.21273/hortsci.39.6.1262.
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Cover crops combined with conservation tillage practices can minimize chemical inputs and improve soil quality, soil water-holding capacity, weed suppression and crop yields. No-tillage production of sweet corn (Zea mays var. `Silver Queen') was studied for 2 years at the USDA Beltsville Agricultural Research Center, Md., to determine cover crop management practices that maximize yield and suppress weeds. Cover crop treatments were hairy vetch (Vicia villosa Roth), rye (Secale cereale L.) and hairy vetch mixture, and bare soil (no cover crop). There were three cover crop killing methods: mowing, rolling or contact herbicide paraquat. All plots were treated with or without atrazine and metolachlor after planting. There was a 23% reduction in sweet corn plant population in the rye-hairy vetch mixture compared to bare soil. Averaged over both years, sweet corn yield in hairy vetch treatments was 43% greater than in bare soil, whereas yield in the rye-hairy vetch mixture was 30% greater than in bare soil. There were no significant main effects of kill method or significant interactions between kill method and cover crop on yield. Sweet corn yields were not different for hairy vetch or rye-hairy vetch treatments with or without atrazine and metolachlor. However, yield in bare soil without the herbicides atrazine and metolachor were reduced by 63% compared to bare soil with these herbicides. When no atrazine and metolachlor were applied, weed biomass was reduced in cover crops compared to the bare soil. Regression analysis showed greater yield loss per unit of weed biomass for bare soil than for the vetch or rye-hairy vetch mixture. This analysis suggests that cover crops increased sweet corn yield in the absence of atrazine and metolachlor not only by reducing weed biomass, but also by increasing the competitiveness of corn to weeds at any given biomass.
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Dwamena, Harriet Achiaa, Kassim Tawiah, and Amanda Serwaa Akuoko Kodua. "The Effect of Rainfall, Temperature, and Relative Humidity on the Yield of Cassava, Yam, and Maize in the Ashanti Region of Ghana." International Journal of Agronomy 2022 (January 24, 2022): 1–12. http://dx.doi.org/10.1155/2022/9077383.
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This study examined the consequences of changes in minimum temperature, maximum temperature, relative humidity, and rainfall on the yields of maize, cassava, and yam per hectare of land in the Ashanti Region of Ghana. Correlation analysis of each climatic condition on the yield of each crop per hectare of land revealed that each of the climatic conditions was significant in predicting the crop yields. Separate multiple linear regression models were obtained for crop yield per hectare of land under all the climatic conditions. The regression models showed that an increase in maximum temperature reduces the yield of all the crops, whereas an increase in minimum temperature reduces only the yield of maize. Increases in relative humidity reduce the yield of maize alone, while increases in rainfall reduce the yield of only cassava. The significant multiple linear regression model for each crop yield indicated that 63.8% of the variations in the yield of maize per hectare of land, 74.3% of the variations in the yield of cassava per hectare of land, and 64.2% of the variations in the yield of yam per hectare of land are accounted for by minimum temperature, maximum temperature, relative humidity, and rainfall. We encourage the Government of Ghana, the Ministry of Food and Agriculture, and all stakeholders in the agriculture sector to increase their campaign on the consequences of climate change on the yield of these crops. They should educate farmers on the effects of overreliance on rainfed and traditional agricultural methods, introduce them to modern methods of agriculture, and provide them with varieties of these crops with higher-yielding capacities in higher temperatures.
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Sudmeyer, R. A., M. A. Adams, J. Eastham, P. R. Scott, W. Hawkins, and I. C. Rowland. "Broadacre crop yield in the lee of windbreaks in the medium and low rainfall areas of south-western Australia." Australian Journal of Experimental Agriculture 42, no. 6 (2002): 739. http://dx.doi.org/10.1071/ea02011.
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In Western Australia, the paucity of documented information detailing crop yield in the lee of windbreaks is a constraint to the adoption of tree windbreaks in dryland farming systems. This paper presents grain yield data for crops growing in the lee of windbreaks in the medium to low rainfall areas of the south-west of Western Australia for 64 field years between 1994 and 1997. Two distinct areas were identified in the lee of windbreaks: a zone of reduced crop yield extending 3–5 times the windbreak height (H) from the trees (competition zone), and a zone of unchanged or improved yield extending 15–20 H (sheltered zone). Yield between 1 and 20 H was less than unsheltered yield in years with average rainfall, similar to unsheltered yield in years, or areas, with low rainfall and higher than unsheltered yield if the unsheltered crop was subjected to sandblasting. Changes in microclimate in shelter appeared to be of benefit in increasing crop yields in drier years or areas. Lupin yield was generally increased in the sheltered zone while cereal yield was generally unchanged. The rate of canopy development may be critical to crop response. In dry years, reduced wind speed in shelter reduced evaporation of soil moisture, increasing the amount of soil water available to establishing crops and reducing sandblasting damage. The principle benefit of windbreaks was their ability to reduce wind erosion and subsequent crop damage. As such, windbreaks are best regarded as a form of insurance.
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Deng, Xiaohui, Barry J. Barnett, Yingzhuo Yu, Gerrit Hoogenboom, and Axel Garcia y. Garcia. "Alternative Crop Insurance Indexes." Journal of Agricultural and Applied Economics 40, no. 1 (April 2008): 223–37. http://dx.doi.org/10.1017/s1074070800023567.
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Three index-based crop insurance contracts are evaluated for representative south Georgia corn farms. The insurance contracts considered are based on indexes of historical county yields, yields predicted from a cooling degree-day production model, and yields predicted from a crop-simulation model. For some of the representative farms, the predicted yield index contracts provide yield risk protection comparable to the contract based on historical county yields, especially at lower levels of risk aversion. The impact of constraints on index insurance choice variables is considered and important interactions among constrained, conditionally optimized, choice variables are analyzed.
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Deng, Xiaohui, Barry J. Barnett, Gerrit Hoogenboom, Yingzhuo Yu, and Axel Garcia y. Garcia. "Alternative Crop Insurance Indexes." Journal of Agricultural and Applied Economics 40, no. 01 (April 2008): 223–37. http://dx.doi.org/10.1017/s1074070800028078.
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Three index-based crop insurance contracts are evaluated for representative south Georgia corn farms. The insurance contracts considered are based on indexes of historical county yields, yields predicted from a cooling degree-day production model, and yields predicted from a crop-simulation model. For some of the representative farms, the predicted yield index contracts provide yield risk protection comparable to the contract based on historical county yields, especially at lower levels of risk aversion. The impact of constraints on index insurance choice variables is considered and important interactions among constrained, conditionally optimized, choice variables are analyzed.
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P.K.SINGH, K.K.SINGH, PRIYANKA SINGH, R. BALASUBRAMANIAN, A.K.BAXLA, B.KUMAR, AKHILESH GUPTA, L.S.RATHORE, and NAVEEN KALRA. "Forecasting of wheat yield in various agro-climatic regions of Bihar by using CERES-Wheat model." Journal of Agrometeorology 19, no. 4 (December 14, 2017): 346–49. http://dx.doi.org/10.54386/jam.v19i4.604.
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Forecasting yield of crops is important for planners in taking tactical decisions for ensuring food availability. Crop simulation models are useful tool to forecast the crop yield. The CERES-wheat model calibrated and validated with experimental data was used to predict the district wise yield in Bihar. Based on the areas under different dates of sowing and crop cultivars, a correction factor was applied on simulated yield to predict the district wise and regional wheat yield. The simulated yield were higher than the actual yield in all the three agro-climatic zones, while the forecasted yields were very close to actual. The percentage deviation of the forecasted yield from the actual was ±4.0 %. The results clearly indicated that the CERES-Wheat model can be used to regional production estimates of wheat in Bihar.
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Hina, Firdous, and Dr Mohd Tahseenul Hasan. "Agriculture Crop Yield Prediction Using Machine Learning." International Journal for Research in Applied Science and Engineering Technology 10, no. 4 (April 30, 2022): 910–15. http://dx.doi.org/10.22214/ijraset.2022.41381.
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Abstract: In our suggested system, we employed a vast dataset that included all of India's states, whereas in the old system, just a single state was considered. These suggestions may be extracted and used to educate the farmers. The farmer can have a better understanding of the crops to cultivate by using a pictorial depiction. Machine Learning Techniques develops a well-defined model with the data and helps us to attain predictions. Agricultural issues like crop prediction, rotation, water requirement, fertilizer requirement and protection can be solved. Due to the variable climatic factors of the environment, there is a necessity to have a efficient technique to facilitate the crop cultivation and to lend a hand to the farmers in their production and management. This may help upcoming agriculturalists to have a better agriculture. A system of recommendations can be provided to a farmer to help them in crop cultivation with the help of data mining. To implement such an approach, crops are recommended based on its climatic factors and quantity. Data Analytics paves a way to evolve useful extraction from agricultural database. Crop Dataset has been analyzed and recommendation of crops is done based on productivity and season Keywords: Machine learning, Agriculture techniques, crop predictions
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Ang, James B., Per G. Fredriksson, and Satyendra Kumar Gupta. "Crop Yield and Democracy." Land Economics 96, no. 2 (March 2020): 265–90. http://dx.doi.org/10.3368/le.96.2.265.
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Zörb, C., C. ‐M Geilfus, and K. ‐J Dietz. "Salinity and crop yield." Plant Biology 21, S1 (September 5, 2018): 31–38. http://dx.doi.org/10.1111/plb.12884.
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Heagle, A. S. "Ozone and Crop Yield*." Annual Review of Phytopathology 27, no. 1 (September 1989): 397–423. http://dx.doi.org/10.1146/annurev.py.27.090189.002145.
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Ramirez, Octavio A., Sukant Misra, and James Field. "Crop‐Yield Distributions Revisited." American Journal of Agricultural Economics 85, no. 1 (February 2003): 108–20. http://dx.doi.org/10.1111/1467-8276.00106.
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Eser, Adnan, Hajnalka Kató, Laura Kempf, and Márton Jolánkai. "Water footprint of yield protein content of twelve field crop species on a Hungarian crop site." Agrokémia és Talajtan 68, Supplement (December 2019): 53–60. http://dx.doi.org/10.1556/0088.2019.00041.
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Abstract Water availability is one of the major physiological factors influencing plant growth and development. An assessment study has been done at the Szent István University, Gödöllő to evaluate and identify the water footprint of protein yield of field crop species. Twelve field crop species (Sugar beet Beta vulgaris, spring and winter barley Hordeum vulgare, winter wheat Triticum aestivum, maize Zea mays, sunflower Helianthus annuus, peas Pisum sativum, potato Solanum tuberosum, alfalfa Medicago sativa, oilseed rape Brassica napus, rye Secale cereale and oats Avena sativa) were involved in the study. Evapotranspiration patterns of the crops studied have been identified by the regular agroclimatology methodology and physiologically reliable protein ranges within crop yields were evaluated. The results obtained suggest, that water footprint of cereals proved to be the lowest, however maize values were highly affected by the high variability of protein yield. Oilseed crops had considerably high protein yield with medium water efficiency. Alfalfa, potato and sugar beet water footprints were in accordance with their evapotranspiration patterns. Protein based water footprint assessment seems to be more applicable in crop species evaluations than that of yield based methodologies.
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Sharma, R. P., Vandana Kaushal, Gayatri Verma, and S. P. Sharma. "Effect of three decade long application of chemical fertilizer and amendments on crop yield under maize - wheat cropping system in an acid alfisol." Journal of Applied and Natural Science 6, no. 1 (June 1, 2014): 106–9. http://dx.doi.org/10.31018/jans.v6i1.383.
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The results on the effect of three decade long term application of chemical fertilizers and amendments on the yield of continuous maize-wheat crop rotation in an acid alfisol at Palampur revealed that continuous omission of essential nutrients in a maize-wheat sequence resulted in an appreciable decline in the grain yield of maize and wheat crops. A remarkable reduction in crop yield was noticed in plots where nitrogen was applied alone. Use of recommended level of N alone through urea had deleterious effect on crop productivity. The continuous exhaustionof native pools of K in 100% NP treated plots appreciably reduced percent grain yield. Application of farmyard manure (FYM) and lime along with NPK fertilizers increased the crop yield. The integrated use of optimal dose of NPK and FYM give better and more sustainable yields.
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Drewniak, B., J. Song, J. Prell, V. R. Kotamarthi, and R. Jacob. "Modeling agriculture in the Community Land Model." Geoscientific Model Development Discussions 5, no. 4 (December 11, 2012): 4137–85. http://dx.doi.org/10.5194/gmdd-5-4137-2012.
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Abstract. The potential impact of climate change on agriculture is uncertain. In addition, agriculture could influence above- and below-ground carbon storage. Development of models that represent agriculture is necessary to address these impacts. We have developed an approach to integrate agriculture representations for three crop types – maize, soybean, and spring wheat – into the coupled carbon-nitrogen version of the Community Land Model (CLM), to help address these questions. Here we present the new model, CLM-Crop, validated against observations from two AmeriFlux sites in the United States, planted with maize and soybean. Seasonal carbon fluxes compared well with field measurements. CLM-Crop yields were comparable with observations in some regions, although the generality of the crop model and its lack of technology and irrigation made direct comparison difficult. CLM-Crop was compared against the standard CLM3.5, which simulates crops as grass. The comparison showed improvement in gross primary productivity in regions where crops are the dominant vegetation cover. Crop yields and productivity were negatively correlated with temperature and positively correlated with precipitation. In case studies with the new crop model looking at impacts of residue management and planting date on crop yield, we found that increased residue returned to the litter pool increased crop yield, while reduced residue returns resulted in yield decreases. Using climate controls to signal planting date caused different responses in different crops. Maize and soybean had opposite reactions: when low temperature threshold resulted in early planting, maize responded with a loss of yield, but soybean yields increased. Our improvements in CLM demonstrate a new capability in the model – simulating agriculture in a realistic way, complete with fertilizer and residue management practices. Results are encouraging, with improved representation of human influences on the land surface and the potentially resulting climate impacts.
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Bittman, S., J. Waddington, and D. A. Pulkinen. "Effect of N and P fertilizer on establishment of alfalfa with a wheat companion crop." Canadian Journal of Plant Science 71, no. 1 (January 1, 1991): 105–13. http://dx.doi.org/10.4141/cjps91-012.
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This study examines the effect of fertilizer applied before seeding on the grain yield of a wheat (Triticum aestivum L.) companion crop and on the forage yield and crude protein content of the underseeded alfalfa (Medicago media Pers.) in subsequent years. The crops were seeded into stubble at five sites in northeast Saskatchewan on soils ranging in texture from silty loam to silty clay. Combinations of three N rates (0, 57 and 114 kg ha−1) and three P rates (0, 28.5, 57 kg ha−1) were applied before seeding to the companion crop plots. Alfalfa was also seeded alone (clear-seeded) at the three P rates. Application of N increased wheat yield but lowered yield of companion-seeded alfalfa to a range of 65–95% of clear-seeded alfalfa in the year after seeding, depending on wheat yield. Alfalfa yields in subsequent years were more variable where wheat yields were high than where wheat yields were low. The wheat crop yielded 1300–2600 kg ha−1 of grain but reduced alfalfa yield over three years by 400–2100 kg ha−1. Phophorus increased yield of wheat without decreasing accumulated yield of alfalfa over 3 yr. The results of this study support the practice in northeast Saskatchewan of supplying N to the requirement of wheat and P to the greater requirement of alfalfa if these crops are seeded together. Key words: Forage, underseeding, yield, protein, Medicago media Pers., Triticum aestivum L.
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Pullins, Emily E., and Robert L. Myers. "Agronomic and economic performance of wheat and canola-based double-crop systems." American Journal of Alternative Agriculture 13, no. 3 (September 1998): 124–31. http://dx.doi.org/10.1017/s0889189300007803.
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AbstractDouble-cropping provides a method of diversifying the rotation, maximizing production, and increasing the profit potential of a cropping system. We assessed agronomic and economic performance of five alternative crops in comparison to the no-till wheat-soybean double-cropping system prevalent in the southern Corn Belt. Canola has shown potential as a profitable winter crop, but its effects on the subsequent crop in a no-till double-crop system required further study. Amaranth, buckwheat, sunflower, and pearl millet were planted after the harvest of canola or wheat, or after fallow. Alternative double-crop grain yield, production costs, and net returns were compared with those of double-crop soybean.Wheat yielded more than canola. Sunflower grain yields did not differ significantly after winter-crop treatments at any site. Yields of amaranth, buckwheat, soybean, and pearl millet differed after winter crops at some sites. At three study yield levels, net returns were positive and greatest for double-crop wheat-amaranth, canola-amaranth, wheat-sunflower, and canola-sunflower systems. All double-crop systems except canolapearl millet had positive net returns at median study yield levels. Low or negative net returns resulted from the combination of low yield and low price for some double crops. Canola was shown to be an economically feasible alternative to wheat in a doublecropping system for central and southern Missouri. Buckwheat and sunflower were shown to be agronomically and economically competitive alternatives to soybean following either canola or winter wheat, with buckwheat most valuable in late-season planting conditions.
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Feng, Sifang, Zengchao Hao, Xuan Zhang, and Fanghua Hao. "Changes in climate-crop yield relationships affect risks of crop yield reduction." Agricultural and Forest Meteorology 304-305 (July 2021): 108401. http://dx.doi.org/10.1016/j.agrformet.2021.108401.
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Brown, Peter R., Nguyen Thi My Phung, and Donald S. Gaydon. "Rats in rice: linking crop and pest models to explore management strategies." Wildlife Research 38, no. 7 (2011): 560. http://dx.doi.org/10.1071/wr10194.
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Context Rodents cause yield losses of 10–15% in irrigated lowland rice crops in Vietnam, with farmers spending a lot of time and money trying to control them. Despite this, there is little understanding about the optimal timing of rodent control and the level of reduction required to maximise rice crop yields. This is compounded by the ability of rice crops to compensate for damage, and farmers applying control at the wrong time. Aims We explored the optimal timing and intensity of rodent control required to increase yields of irrigated lowland rice crops in the Mekong Delta, Vietnam. Methods We developed a system analysis framework using the rice model APSIM-Oryza validated against a hand-clipped field experiment, linked with a rodent population model and field data on rodent damage rates in rice crops. A range of intensities of reduced feeding rates and timing were explored in simulated scenarios. The responses were examined over three rice crop seasons in An Giang province, Mekong Delta, Vietnam. Key results The rice crop model was benchmarked, validated and shown to adequately compensate for rodent damage. Highest yield losses occurred in the third rice crop (16% yield loss). A one-off rodent control action at the booting stage of the rice crop with 50% control effectiveness achieved a 5% yield increase. The community trap barrier system (CTBS) with 30% control effectiveness achieved a 5% yield increase. Conclusions The modelling demonstrated the importance of rodent management timing and that control should be applied before the onset of the rodent breeding season, which normally starts at maximum tillering or booting stages. Implications We conclude that modelling can improve pest management decisions by optimising timing and level of effectiveness to achieve yield increases.
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Raddatz, R. L., C. F. Shaykewich, and P. R. Bullock. "Prairie crop yield estimates from modelled phenological development and water use." Canadian Journal of Plant Science 74, no. 3 (July 1, 1994): 429–36. http://dx.doi.org/10.4141/cjps94-080.
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The feasibility of estimating average yields of spring wheat, barley and canola for Manitoba, Saskatchewan and Alberta, individually and collectively, from crop-specific model output routinely published in the Winnipeg Climate Centre's Agrometeorological Outlooks was examined. Statistically significant correlations were found between crop district/census division yields for 1988–1992 and modelled end-of-season crop water-use, and between these yields and the end-of-season ratios of water-use to water-demand and modelled days-to-maturity. Up to 69% of the observed variance in spring wheat yields could be explained by modelled agrometeorological variables. The best R2 values for barley and canola were 67 and 64%, respectively. The regression equations so derived were applied to 1993 model output and the resultant average crop district yield estimates for wheat, barley and canola, aggregated up to the provincial and the Prairie-wide levels, were compared with Statistics Canada's preliminary (i.e., July) and post-harvest (i.e., November) crop survey estimates and with yield estimates from the Canadian Wheat Board's Western Canada weather model. From these comparisons it was concluded that the Agrometeorological Outlooks can provide timely provincial and Prairie-wide estimates of average yields for these important Prairie crops. Key words: Crop water-use, crop water-demand, modelling, yield, wheat, barley, canola
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Brückler, Martin, Thomas Resl, and Andreas Reindl. "Comparison of organic and conventional crop yields in Austria." Die Bodenkultur: Journal of Land Management, Food and Environment 68, no. 4 (March 9, 2018): 223–36. http://dx.doi.org/10.1515/boku-2017-0018.
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SummaryOrganic farming represents an integral part of agriculture in Austria. The share of organic holdings and the share of area being organically farmed are already high relative to other countries within the European Union. So far, analyses of the organic sector have mainly focused on the economic output and the utilised area; less is known about absolute crop yields per hectare and the gap between organic and conventional crop yields. Given their relevance for profitability calculations and production strategies, such data is of major interest for farmers, advisors, and decision-makers. To address this lack of knowledge, we combine the Austrian farm accountancy data and Integrated Administration and Control System data for Austria. This paper presents a statistical analysis of organic crop yield data for the national Austrian territory as well as for regional categories and covers the period from 2003–2016. The results show a significant difference in crop yields: i) between organic and conventional farming systems; ii) between regional categories in Austria. Organic cereals achieve 35% lower average crop yields than conventional systems, yields for organic root and tuber crops were 27–49% lower. Yield gaps of oilseed and protein crops vary widely between respective crop species.
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Davis, Adam S. "Cover-Crop Roller–Crimper Contributes to Weed Management in No-Till Soybean." Weed Science 58, no. 3 (September 2010): 300–309. http://dx.doi.org/10.1614/ws-d-09-00040.1.
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Termination of cover crops prior to no-till planting of soybean is typically accomplished with burndown herbicides. Recent advances in cover-crop roller–crimper design offer the possibility of reliable physical termination of cover crops without tillage. A field study within a no-till soybean production system was conducted in Urbana, IL, from 2004 through 2007 to quantify the effects of cover crop (cereal rye, hairy vetch, or bare soil control), termination method (chemical burndown or roller–crimper), and postemergence glyphosate application rate (0, 1.1, or 2.2 kg ae ha−1) on soybean yield components, weed–crop interference, and soil environmental variables. Biomass of weeds surviving management within a soybean crop following either a vetch or rye cover crop was reduced by 26 and 56%, respectively, in the rolled system compared to the burndown system. Soybean yield loss due to weed interference was unaffected by cover-crop termination method in soybean following a rye cover crop, but was higher in the rolled than burndown treatment in both hairy vetch and bare soil treatments. In soybean following a rye cover crop, regardless of termination method, yield loss to weed interference was unaffected by glyphosate rate, whereas in soybean following a vetch cover crop or bare soil, yield loss decreased with glyphosate rate. Variation in soybean yield among cover crops and cover-crop termination treatments was due largely to differences in soybean establishment, rather than differences in the soil environment. Use of a roller–crimper to terminate a cover crop preceding no-till soybean has the potential to achieve similar yields to those obtained in a chemically terminated cover crop while reducing residual weed biomass.
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Borger, Catherine P. D., Abul Hashem, and Shahab Pathan. "Manipulating Crop Row Orientation to Suppress Weeds and Increase Crop Yield." Weed Science 58, no. 2 (June 2010): 174–78. http://dx.doi.org/10.1614/ws-09-094.1.
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Crop rows oriented at a right angle to sunlight direction (i.e., east–west within the winter cropping system in Western Australia) may suppress weed growth through greater shading of weeds in the interrow spaces. This was investigated in the districts of Merredin and Beverley, Western Australian (latitudes of 31° and 32°S) from 2002 to 2005 (four trials). Winter grain crops (wheat, barley, canola, lupines, and field peas) were sown in an east–west or north–south orientation. Within wheat and barley crops oriented east–west, weed biomass (averaged throughout all trials) was reduced by 51 and 37%, and grain yield increased by 24 and 26% (compared with crops oriented north–south). This reduction in weed biomass and increase in crop yield likely resulted from the increased light (photosynthetically active radiation) interception by crops oriented east–west (i.e., light interception by the crop canopy as opposed to the weed canopy was 28 and 18% greater in wheat and barley crops oriented east–west, compared with north–south crops). There was no consistent effect of crop row orientation in the canola, field pea, and lupine crops. It appears that manipulation of crop row orientation in wheat and barley is a useful weed-control technique that has few negative effects on the farming system (i.e., does not cost anything to implement and is more environmentally friendly than chemical weed control).
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Weih, Martin, Alison J. Karley, Adrian C. Newton, Lars P. Kiær, Christoph Scherber, Diego Rubiales, Eveline Adam, et al. "Grain Yield Stability of Cereal-Legume Intercrops Is Greater Than Sole Crops in More Productive Conditions." Agriculture 11, no. 3 (March 17, 2021): 255. http://dx.doi.org/10.3390/agriculture11030255.
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The intercropping of two or more crop species on the same piece of land at a given time has been hypothesized to enhance crop yield stability. To address this hypothesis, we assessed the grain yield stability of various barley-pea and wheat-faba bean mixtures grown in seven experimental field trials (locations) across Europe during two years with contrasting weather (2017 and 2018). Three different yield stability measures were used, all based on the expected yield variability of the mixture components grown as sole crops, and the corresponding observed yield variability of the same components grown in 50:50 mixtures in a replacement design. Stability indices were calculated as ratios between the expected and observed variabilities, with values > 1 indicating greater stability of the intercrops. Mean grain yields tended to be higher in intercrops than sole crops. However, in contrast to our hypothesis, the observed (intercrop) yield stability was similar or lower than the expected (sole crop) stability in most locations except one. Furthermore, yield stability significantly increased with increasing mean yields when assessed across differentially productive locations. The results are relevant for the designing of intercropping systems as a means to increase yield stability and the resilience of cropping systems.
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Hounnou, Fèmi E., Houinsou Dedehouanou, Afio Zannou, Sofwaan Bakary, and Elisée F. Mahoussi. "Influence of Climate Change on Food Crop Yield in Benin Republic." Journal of Agricultural Science 11, no. 5 (April 15, 2019): 281. http://dx.doi.org/10.5539/jas.v11n5p281.
Full textAbstract:
World climate is projected to be more harmful and unforeseeable. A threefold combination of temperature, precipitation and potential evapotranspiration leads to climate change with a negative effect on staple food crop production. To understand the sensitivity of staple food crop yield to future change in climate, this paper uses the feasible generalized least square (FGLS) and heteroskedasticity and autocorrelation (HAC) consistent standard error techniques function to quantify the effects of climate variables on the mean and variance of crop yields. Data from FAOSTAT website and national institutions such as temperature, precipitation and crop areas cultivated for period 1961-2015 for Benin country are used. Climate variables are computed according to each crop growing season. The results showed that climate change could significantly influence the mean crop yields and could significantly affect the crop yield variability. The contribution of climate variables to crop yield varies across staple crop yields and they were predicted to decrease about 2025. In order to ensure food availability in the context of climate change, support to agricultural sector and especially to staple food crops production should be focused on seeds improvement by generating, developing and extending drought and flood-tolerant varieties. The results also implicate the promoting of irrigated agriculture.
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DAS, H. P., A. D. PUJARI, and A. CHOWDHURY. "Dependance of soybean yield on crop evapotranspiration, crop duration and rainfall." MAUSAM 49, no. 4 (December 16, 2021): 503–6. http://dx.doi.org/10.54302/mausam.v49i4.3663.
Full textAbstract:
In the present study, data for four stations viz., Banswara, Bhopal, Parbhani and Rahuri for the years from 1990 to 1993 have been utilized to understand various aspects of evapotranspiration of the soybean crop. An attempt has also been made to find out the impact of rainfall and crop duration at different phases on the seed yield.
The yield was found to be significantly correlated with the rainfall during vegetative phase. Crop growth duration exert positive effect on the soybean yield and that a longer flowering period is favourable for higher yields.
The results also indicate that the soybean crop consume maximum water during the vegetative stage.
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Sandler, Leah, Kelly A. Nelson, and Christopher Dudenhoeffer. "Winter Wheat Row Spacing and Alternative Crop Effects on Relay-Intercrop, Double-Crop, and Wheat Yields." International Journal of Agronomy 2015 (2015): 1–8. http://dx.doi.org/10.1155/2015/369243.
Full textAbstract:
In Missouri as well as much of the Midwest, the most popular double-cropping system was winter wheat (Triticum aestivumL.) followed by soybean (Glycine max(L.) Merr). These two crops can also be used in an intercrop system, but optimal row spacing was important to increase crop productivity. Research was conducted to evaluate (1) winter wheat inter- and double-crop production systems, using a variety of alternative crops, and (2) the impact of different wheat row spacings on intercrop establishment and yields within the various cropping systems. Field research was conducted during droughts in 2012 and 2013. Spacing of wheat rows impacted wheat yields by 150 kg ha−1, as well as yields of the alternative crops. Narrower row spacings (150 kg ha−1) and the double-crop system (575 kg ha−1) increased yield due to the lack of interference for resources with wheat in 2013. Land equivalent ratio (LER) values determining productivity of intercrop systems of 19 and 38 cm row showed an advantage for alternative crops in 2013, but not 2012. This signified that farmers in Northeast Missouri could potentially boost yield potential for a given field and produce additional forage or green manure yields in a year with less severe drought.