Stages Of Crop Development Research Articles

Impact of different rootstocks and limited water on yield and fruit quality of melon grown in a field naturally infested with Fusarium wilt

1- Grafting and rootstock-scion combinations affect fruit yield. 2- The yield increased with increasing the mean fruit weight, yield per plant and number of fruits per plant. 2- Grafting plants had a significant positive effect on fruit quality. 3- The mineral concentrations of melon-grafted plants are higher than those of non-grafted plants throughout the growth period. 4- The low soil moisture and not to graft for Fusarium wilt disease promotes the growth of the pathogen and the emergence of wilt symptoms. The experiment was performed to determine the effects of different rootstocks on yield and some fruit quality characteristics of grafted melon growth under the soil-borne pathogen ( Fusarium oxysporum f.sp.melonis ) and water stress conditions in 2019-2020, at Cumra in Konya Plain, Turkey. In the study, four different Cucurbita maxima x Cucurbita moschata hybrids rootstocks were used: 1-Non-grafted, 2-Ferro, 3-Maximus, and TZ 148. Edalı F 1 variety ( Cucumis melo var. Edalı F 1 ) was selected as a scion. Cotyledon splice grafting was used as the grafting method. The experiment was conducted in a split-plot design with three replications. The main plots constituted of three irrigation levels while the subplots were designed to have different rootstocks. Irrigation was supplied during the appropriate crop development stages (early vegetative, late vegetative, flowered-fruit setting and ripening) with enough water to fill the soil depth of 0–90 cm to field capacity (I100), to 50% of field capacity (I50) with decreased water supply levels and water-free (I0) conditions. As a result, it was found that yield and some fruit quality parameters were significantly affected by the treatments. The rootstocks were similarly effective on soil-borne pathogen management and resulted in yields higher than non-grafted plants in the both years. The highest yield (4.939–3.604 t da−1) was obtained under no water stress I100 / TZ148 rootstock combination (p<0.01). Other macro-micro nutrient and fruit sugar contents were significantly affected by treatments. The seasonal water consumptive use (ET) at I100 treatment was recorded as 205 and 231 mm, respectively, for the both years.

Times of Trinexapac-ethyl application associated to plant densities in agronomic performance of second-season corn

Plant growth regulators, which can alter the plant size and anatomy, allow the use of cultivars of interest that do not have a modern leaf architecture, making higher plant densities possible. The objective of this study was to evaluate the agronomic performance of second season corn, grown at different plant densities and under Trinexapac-ethyl applications at different stages of crop development. The field study was carried out in two growing seasons (2013 and 2014), at the Fazenda Escola of the State University of Londrina. Fifteen treatments were evaluated in a randomized block, 5 x 3 factorial design, at five plant densities (40,000, 60,000, 80,000, 100,000 and 120,000 plants per hectare), of Trinexapac-ethyl applied in three stages: control (no application), V6 and V9, with four replications. The morphological plant characteristics, the yield components and grain yield were evaluated. Increases in plant density raise the plant height, reduce the number of grains per ear, ear length and 100-kernel weight, and have no influence on grain yield. The application of Trinexapac-ethyl in stage V9 reduces plant and ear insertion height and 100-kernel weight.

Plant beneficial rhizobacteria community structure changes through developmental stages of peanut and maize

Our objective in this study was to analyze the structure of the rhizobacterial community during different growth stages of peanut and maize plants. Microcosm assays were performed using pots containing unsterile soil from the peanut growing area of Argentina in which peanut and maize plants were grown during 120 and 100 days, respectively. Four to five samples of rhizospheric soil were obtained at the beginning of the assay, at an early growth stage of each plant and at the end of the assay. Two replicate DNA extractions from rhizospheric soil samples were realized per treatment on both microcosm assays to analyze rhizobacterial community structure by high-throughput sequencing of 16S rRNA gene.We observed changes in rhizobacteria community structure with crop developmental stages. Community structure changes occurred at several bacteria taxonomic levels, and major changes were observed in later stages. In particular, plant growth promoting bacteria genera were promoted in later stages. Our results indicate plant rhizospheric selection for growth enhancing rhizobacteria during stages of high nutrient demand. In conclusion, the structure of the rhizobacterial communities of peanut and maize are influenced by plant phenological stages, and beneficial bacteria are favoured in late phenological stages.

Winter cover crops shape early‐season predator communities and trophic interactions

AbstractDespite the dynamic nature of annual cropping systems, few studies have investigated how the structure of predator communities and their interactions with prey corresponds with crop seasonality. Adding winter habitat, such as cover crops, improves soil health and likely contributes seasonal habitat availability for arthropod communities. Stable habitat may lead to functionally diverse predatory communities and their associated ecosystem services, such as biological control. Here, we estimated predatory community functional changes based on foraging traits determined by molecular gut–content analysis (MGCA) in response to winter cover crops (rye and crimson clover) in a cotton agroecosystem. Predators were collected from replicated 1‐ha experimental field plots during each major stage of crop development in 2017 and 2018, and MGCA was used to estimate predator roles and responses to cover crop treatments. Cotton planted into a rye cover crop residue promoted unique predator communities in the early and mid‐season as compared to no‐cover fields. Correspondingly, we observed dissimilar prey consumption among cover crop treatments. Winter cover crops led to an increase in consumption of alternative prey and incidental pests by natural enemies on seedling cotton and encouraged high predator diversity that aligns temporally with potential early‐season pest outbreaks. Therefore, cover crops commonly employed for soil health and erosion benefits also contribute to pest management by providing habitat and alternative prey resources that boost early‐season predatory arthropod communities.

Decomposition of oat straw and release of macronutrients in different managements

The present work was aimed in order to evaluate the decomposition process of remaining straw from oat cultivars submitted to different handling during the cultivation of corn for silage intercropped with Urochloa brizantha cv. MG13 Braúna. We considered nine oat cultivars named as follows: "IAPAR 61 IBIPORÃ" oat hay (61F), "IAPAR 61 IBIPORÃ" pasture (61P), "IAPAR 61 IBIPORÃ" cover crop (61SM), "Embrapa 139 (Fog)" oat hay (139F),"Embrapa 139 (Fog)" pasture (139P)," Embrapa 139 (Fog)" cover crop (139SM), "Emerald IPR 126" oat hay (EF), "Emerald IPR 126" grazed (EP) and "Emerald IPR 126" cover crop (ESM) from which we evaluated the decomposition of the remaining straw using the method of litter bags. The evaluations were carried out at 0, 15, 30, 60, 90 and 108 days after sowing corn for silage intercropped with Brizantha brachiaria cv. MG13 Braúna (Urochloa brizantha). Every oat cultivar had three repetitions arranged in a split-plot design. We took into account the quantity of straw, organic matter, carbon, nitrogen, carbon / nitrogen ratio, phosphorus and potassium. The results we got clarify that oat decomposition rate varied with the meteorological factors and initial mass, so that the greater the initial mass is, the longer the straw permanency and mulch effectiveness on the soil. The time the residual oat straw took to be decomposed depended on meteorological factors both during the cover crop developmental stage and the decomposition period itself. The higher the initial mass, the greater the time and effectiveness of mulching.

Crop Simulation Models: A Tool for Future Agricultural Research and Climate Change

A crop simulation model is a computerized program which is used to describe the process of growth and developmental stages of crop in relation to weather data, crop conditions and soil conditions to solve the real-world problems. Crop simulation models plays an important role in decision making process as these models can save time and resources. The prediction accuracy of simulation models is one of the most vital components in decision making process. Our review shows the prediction accuracy and efficiency of the simulation models like DSSAT and APSIM. We have compared the prediction accuracy of these models on various growth and development stages of crops along with yield prediction. Both the models have performed well while predicting various growth and developmental stages of crops. The present scenario of traditional research is site-specific, Resource consuming and time consuming. Hence the information obtained through traditional research by qualitative analysis has many limitations, Because of changing climate and weather parameters there is a need for computerized based statistical tool which can provide decision support system for more than 10-15 years. By this we strongly believe that Crop simulation models can be a vital tool in future agricultural research and climate change mitigation strategies.

Differences in seasons and rice varieties provide opportunities for improving nitrogen use efficiency and management in irrigated rice in Kenya

Apart from nitrogen (N) rates, N use efficiency (NUE) (yield N/total input N) is affected by seasons, crop developmental stages, and varieties. Knowledge of how these factors affect NUE in rice production in Kenya is limited. Therefore, field experiments were conducted with ‘low rates’ of N (simulating farmers’ practices) of 0, 26, 52 and 78 kg N ha−1 with five varieties (MWUR1, MWUR4, IRAT109, NERICA4 and NERICA10) and higher rates of N (125, 175, and 225 kg N ha−1) simulating researchers’ doses with two lowland varieties (Basmati 370 and BW 196) and IR 72. Another experiment on NUE responses to sites, N rates and dose (split or full dose) was undertaken with the IR97 variety. With the ‘low rate’, yields increased with incremental N rates up to 52 Kg N ha−1 and declined (during cold periods, for some varieties). In this scenario, the N agronomic efficiencies (AEN) declined with increasing N but depended on sites and seasons. However, most AEN values were above 100, implying nutrient mining. In most cases (except at the Mwea site), the N utilization efficiency (NUtE) ranged from 16 to 22kg kg−1 and were not significantly affected by sources and methods of N application. In all cases, an increase in N elicited declining trends in NUtE. Moreover, N uptake efficiency ranged between 22 and 90kg kg−1 without significant variation among varieties. For the ‘high N rates’, high biomass yield resulted in higher grain yields in BW 196 and IR 72 but yield declined beyond 75 kg ha−1 N rates due to poor grain filling, particularly when a cold period coincided with booting and grain filling. We conclude that N rates, doses and rice varieties are key determinants of AEN and NUtE in contrasting rice growing seasons in Kenya. Cropping seasons and rice varieties are therefore potential key determinants of sustainable rice productivity and improved NUE in rice-based systems in the studied regions of Kenya.

Interference of post-emergent herbicides with wheat (Triticum aestivum L.) productivity parameters/ Interferência de herbicidas pós-emergentes sobre parâmetros produtivos do trigo (Triticum aestivum L.)

Wheat is the most important income-generating crop in southern Brazil during the cold season. It also contributes to the crop rotation system and increases the yield of successive crops. During its growth cycle, herbicides are used to control weeds, which are the main factor limiting wheat productivity. Further, high costs of weed control directly affect crop economic returns. The objective of this study was to evaluate the effect of the application of two herbicides, namely, 2,4-D and iodosulfuron-methyl, on the productivity of two wheat cultivars during the nine different stages of crop development. The most suitable crop stage for herbicide application, as described in the corresponding label on the package, is at the beginning of tillering. 2,4-D had a significant impact on productivity parameters, reducing the number of tillers, the number of ears, and the number of tillers without grains, while increasing the number of tillers without ears and ears without grains, indicating greater phytotoxicity and, ultimately, reducing crop productivity. Conversely, iodosulfuron-methyl showed greater selectivity to the wheat cultivars tested and caused a much lesser impact on the productivity parameters measured.

Bioecology of fall armyworm Spodoptera frugiperda (J. E. Smith), its management and potential patterns of seasonal spread in Africa.

Fall armyworm, Spodoptera frugiperda (J. E. Smith) has rapidly spread in sub-Saharan Africa (SSA) and has emerged as a major pest of maize and sorghum in the continent. For effective monitoring and a better understanding of the bioecology and management of this pest, a Community-based Fall Armyworm Monitoring, Forecasting, Early Warning and Management (CBFAMFEW) initiative was implemented in six eastern African countries (Ethiopia, Kenya, Tanzania, Uganda, Rwanda and Burundi). Over 650 Community Focal Persons (CFPs) who received training through the project were involved in data collection on adult moths, crop phenology, cropping systems, FAW management practices and other variables. Data collection was performed using Fall Armyworm Monitoring and Early Warning System (FAMEWS), a mobile application developed by the Food and Agricultural Organization (FAO) of the United Nations. Data collected from the CBFAMFEW initiative in East Africa and other FAW monitoring efforts in Africa were merged and analysed to determine the factors that are related to FAW population dynamics. We used the negative binomial models to test for effect of main crops type, cropping systems and crop phenology on abundance of FAW. We also analysed the effect of rainfall and the spatial and temporal distribution of FAW populations. The study showed variability across the region in terms of the proportion of main crops, cropping systems, diversity of crops used in rotation, and control methods that impact on trap and larval counts. Intercropping and crop rotation had incident rate 2-times and 3-times higher relative to seasonal cropping, respectively. The abundance of FAW adult and larval infestation significantly varied with crop phenology, with infestation being high at the vegetative and reproductive stages of the crop, and low at maturity stage. This study provides an understanding on FAW bioecology, which could be vital in guiding the deployment of FAW-IPM tools in specific locations and at a specific crop developmental stage. The outcomes demonstrate the relevance of community-based crop pest monitoring for awareness creation among smallholder farmers in SSA.

Improving estimation of in-season crop water use and health of wheat genotypes on sodic soils using spatial interpolation techniques and multi-component metrics

Crop water use can be a useful indicator of in-season crop conditions including health and greenness on sodic soils. However, in-field manual measurements of crop water use can be tedious, time and labour-intensive and may also exhibit large spatial variability, and inefficient for surveying large areas. Here we propose a novel approach to estimate in-field crop water use of wheat using spatial interpolation techniques at critical crop development stages (tillering and close to flowering) on a moderately sodic and a highly sodic site in southern Queensland, Australia. The six spatial interpolation techniques; ordinary kriging, empirical Bayes kriging, inverse distance weighting, spline, local polynomial interpolation, and radial basis function were employed on ground-measured crop water use data and compared to accurately estimate the spatial distribution of crop water use. Initially, the comparison was made using root mean square error, mean absolute error, and coefficient of determination values using cross-validation. For a more clear comparison and to account for complexities of site-specific crop water use distribution, the standardized, multi-component model performance efficiency metrics, i.e. Kling-Gupta efficiency and spatial efficiency were adopted and tested over cross-validation techniques. Results showed that Kling-Gupta efficiency was slightly better at selecting the optimum interpolation models for crop water use estimation at a field scale than the spatial efficiency metric. Spline and local polynomial interpolation were relatively better estimators of crop water use for both the sites at tillering, while the radial basis function and spline were superior close to flowering. The estimated crop water use was positively and closely associated with seasonal GreenSeeker® normalized difference vegetation index data (R2 = 0.49 and 0.39 at tillering; and R2 = 0.71 and 0.62 at close to flowering, for the moderately sodic and highly sodic sites, respectively). The research improves our understanding of selecting appropriate spatial interpolation methods for in-season crop water use estimation that could help detect changes in crop health due to in-field and seasonal variations of crop water use in a sodic soil environment.

2.4 GHz RF Received Signal Strength Based Node Separation in WSN Monitoring Infrastructure for Millet and Rice Vegetation

The WSN monitoring infrastructure developed for a vegetative environment may encounter network disconnectivity due to node isolation if the node deployment strategy has not accounted for the change in vegetation density at different crop development stages. This proposal develops a path loss model by analyzing the effects of vegetation height and density on signal strength between two sensor nodes communicating under the IEEE802.15.4 Wireless standard. For this, the path loss coefficients have been analyzed for 2.4 GHz RF signals through measurement campaigns at various development stages of Rice and Millet crop. The proposed path loss model controls the separation between sensor nodes to achieve a distribution that is resistant to network disconnectivity caused by node isolation. The acquired database and formulated path loss model can be used by IoT network architects and researchers in the field of precision agriculture as a benchmark for network development and comparison with the signal strength in other crops.

Winter cereal responses to dose and application timing of trinexapac‐ethyl

AbstractTrinexapac‐ethyl (TE) is a plant growth regulator commonly used in cereal production systems. It retards plant growth by inhibiting gibberellin (GA) biosynthesis, thereby reducing the risk of stem lodging. Lodging at the latter stages of crop development can compromise grain yield and quality. Thus, application of TE may protect yield and quality in winter cereals. A field study was conducted from 2014 to 2017 across the Canadian Prairies to determine the effects of TE dose and application timings on lodging, canopy architecture, grain yield, and quality of winter cereals. Trinexapac‐ethyl treatments consisted of 0.6× (60 g a.i. ha−1) and 1× (100 g a.i. ha−1), which were applied to two winter wheat (Triticum aestivum L.) cultivars, 'Flourish’ and ‘Moats’, and a fall rye (Secale cereale L.) cultivar ‘Hazlet’, at Feekes 5 and 7 growth stages. Compared with the control, TE application increased grain yield by 3–8%, reduced plant height by 5–10%, and shortened internode length. Plant height reductions were most notable when TE was applied at the 1× rate at Feekes 7. The most responsive crop was fall rye, which could be expected given its tall stature relative to the wheat cultivars. Most of the tested environments, including irrigation, did not induce heavy stem lodging; therefore, observations of positive yield responses in the absence of lodging were unexpected. Our findings suggest that there is a role for TE in winter cereal production systems, provided the magnitude of crop responses justifies the added input costs.

The synergistic action of &lt;i&gt;Azospirillum brasilense&lt;/i&gt; and effective microorganisms promotes growth and increases the productivity of green corn

In view of the current dissemination of even more sustainable techniques, which allow the producer to explore the microbial biodiversity native to the property's soil and obtain effective microorganisms (EM), the hypothesis was tested that the biopriming of corn seeds using the co-inoculation of A. brasilense + EM could promote growth and increase the productivity of green corn. Additionally, the effect of treating seeds with humic acids was evaluated. For this, a field experiment was conducted using the following treatments: A. brasilense; EM; A. brasilense + EM; humic acids (Solo Humics) and Control. Co-inoculation of A. brasilense + EM potentiated the growth-promoting effects of diazotrophic (height and stem diameter increased 30 days after sowing - DAS, fresh and dry mass of aerial part at 90 DAS and dry mass of root at 60 and 90 DAS) and increased productivity of green corn (presented the highest averages for ear weight with and without straw). The treatment of seeds with humic acids showed promising effects only in the initial stages of crop development – when the plants evaluated were at 30 DAS. However, in the final evaluation phase (90 DAS) the effect of these acids became less satisfactory than microbial inoculation. The enrichment of inoculants of A. brasilense with EM is therefore a viable alternative for promoting growth and increasing productivity in the cultivation of green maize in addition to being a low complexity technology and even cheaper than the simple use of commercial inoculants.

Field efficacy of Bt cotton containing events DAS-21023-5 × DAS-24236-5 × SYN-IR102-7 against lepidopteran pests and impact on the non-target arthropod community in Brazil.

The efficacy and non-target arthropod effects of transgenic DAS-21023-5 × DAS-24236-5 × SYN-IR102-7 Bt cotton, expressing proteins Cry1Ac, Cry1F and Vip3Aa19, was examined through field trials in Brazil. Fifteen field efficacy experiments were conducted from 2014 through the 2020 growing season across six different states in Brazil to evaluate performance against key lepidopteran pests through artificial infestations of Chrysodeixis includens (Walker), Spodoptera frugiperda (J.E. Smith,1797), Spodoptera cosmioides (Walker, 1858) and Chloridea virescens (F., 1781), and natural infestations of Alabama argillacea (Hübner) and S. frugiperda. The impact of this Bt cotton technology on the non-target arthropod community in Brazilian cotton production systems was also assessed in a multi-site experiment. DAS-21023-5 × DAS-24236-5 × SYN-IR102-7 cotton significantly reduced the feeding damage caused by S. frugiperda, S. cosmioides, C. includens, C. virescens and A. argillacea, causing high levels of mortality (greater than 99%) to all target lepidopteran pests evaluated during vegetative and/or reproductive stages of crop development. Non-target arthropod community-level analyses confirmed no unintended effects on the arthropod groups monitored. These results demonstrate the value of transgenic Bt cotton containing event DAS-21023-5 × DAS-24236-5 × SYN-IR102-7 for consideration as part of an integrated approach for managing key lepidopteran pests in Brazilian cotton production systems.

Effects of simulated hail damage and foliar-applied recovery treatments on growth and grain yield of wheat, field pea, and dry bean crops

Hailstorms can be responsible for significant economic loss to the agricultural sector in Alberta, Canada. Foliar applications of certain fungicides and nutrient blends have been advocated to promote recovery and yield of hail-damaged crops. Proper understanding of different crop and hail-related factors is required for an accurate assessment of hail damage to crops and for evaluations of hail-recovery product claims. This study was undertaken at three locations in Alberta during three growing seasons (2016–2018) to determine the effects of two levels of simulated hail severity at three different crop developmental stages, including the early growth (BBCH 30 for wheat; BBCH 14–16 for pulses), mid-growth (BBCH 39 for wheat; BBCH 60 for pulses), and late growth (BBCH 60 for wheat; BBCH 71 for pulses) stages. Plant growth and yield parameters of wheat (Triticum aestivum L.), field pea (Pisum sativum L.), and dry bean (Phaseolus vulgaris L.) crops were measured. Simulated hail damage led to reductions in height, biomass, NDVI, grain yield, and kernel weight of all three crops. Average yield decreased by 24% and 35% for wheat, 17% and 35% for dry beans, and 37% and 45% for field peas for light and heavy hail severity, respectively. Hail timing was a critical factor influencing the extent of crop damage, with hail damage during the early growth stage leading to a lesser yield reduction compared with hail damage at the mid-growth and late growth stages. Fungicides and nutrient blends applications did not significantly improve crop recovery, grain yield, or kernel weight for any of the crops in this study.

LED Enhances Plant Performance and Both Carotenoids and Nitrates Profiles in Lettuce.

Recent studies show that vegetables at early stage of development contain higher amounts of phytonutrients and minerals, and lower amounts of nitrates than at fully developed stage. Nevertheless, the effects of some spectrum light on the carotenoid content of lettuce microgreens are unknown. Three different LED lamps were checked: (i) artificial white light (T0); (ii) continuous light-emitting diodes with longer blue-wavelength (T1), and (iii) continuous light-emitting diodes with longer red-wavelength (T2). Different lettuce cvs. were grown under the above described lamps. Plants were collected after 10, 15, 35 and 50 days from planting to produce sprouts, microgreens, initial baby leaf, and baby leaf, respectively. Response to different continuous spectrum lights related to productivity and nitrate content was variable for the different plants. Accumulation of nitrates at initial stages in plant tissues was clearly lower than at final stages of crop development, ranging from 50.2 to 73.4mg 100 g1 fresh weight for T2. Lettuce consumption is preferable at microgreen stage in comparison with baby leaf stage. Nitrate amounts at microgreen stage were lower than in baby leaf stage, and this content was inversely correlated with carotenoid content, which in tissues was higher at microgreens stage influenced by LED.

Effect of planting time on the yield and quality of cherry tomato (Solanum lycopersicum var. cerasiforme).

Planting date is an important factor which directly related to crop production in a specific area. Different planting time may affect crop yield and quality due to varying climatic conditions at different stages of crop growth and development. The present experiment was laid out to investigate the effect of planting date at an interval of 15 days during winter season of 2019-20 on the yield and quality of cherry tomato. The potentiality of fruiting in the winter season was evaluated by planting on November 15, November 30, December 15, December 30 and January 14. Data on yield and quality attributes of cherry tomato like plant height, number of fruits per plant, fruit yield per plant (g), yield (t ha-1), TSS (%), pH and vitamin C contents (mg 100 g-1) were recorded. Results revealed that planting time had significant effects on the yield and quality parameters of cherry tomato. Cherry tomato performed better on 30 November planting date in respect of yield and vitamin C content due to favorable climatic conditions at different growing stages as per requirements that may lead to higher yield and quality of fruits.

Multi-layer hierarchical optimisation of greenhouse climate setpoints for energy conservation and improvement of crop yield

Energy conservation is an increasingly important issue in greenhouse production. Since higher energy input usually produces higher crop yields, crop yield and energy consumption must be carefully traded off. Generally, at any instant, the heating energy demand and crop yield depend on an interior temperature setpoint. Good, dynamically determined greenhouse climate setpoints not only improve crop yield, but also reduce the total energy consumption of the greenhouse. The greatest uncertainty in determining setpoints is the long-term weather. To deal with this uncertainty, this paper presents a multi-layer hierarchical optimisation framework for greenhouse climate setpoints. This framework has two optimisation layers with different timescales, and the whole production cycle is divided into several crop development stages, with each stage including several days. In the first layer, off-line multi-objective optimisation is carried out using historical weather data to maximise the crop yield and minimise the total energy consumption of the greenhouse heating. The aim is to optimise the mean temperature for each crop development stage. Based on the constraint of the optimal mean temperatures of the development stages, this work used a surrogate-assisted constrained single-objective method for online optimisation of the daily temperature using current short-term weather forecasts. Since the proposed method does not directly optimise the greenhouse climate setpoint, but instead optimises the mean temperature of the stages and the daily mean temperature, this work develops an effective indoor daily mean temperature serialisation method to generate the temperature setpoint series. The simulation results show that, compared to a widely used commercial system, the energy efficiency can be improved by 24.9%, 16.8% and 14.6% under real weather conditions of three example years. • Energy saving problem of greenhouse production is discussed. • A setpoint optimisation strategy of greenhouse climate is proposed. • A way to solve multi-timescale optimisation problem is presented. • Surrogate-assisted optimisation is used to optimise the daily mean temperature. • A comparison study of energy-saving performance is presented.

Impact of climate change on Swedish agriculture: Growing season rain deficit and irrigation need

Over 90% of Swedish agriculture is rainfed, and thus future climate change can pose a risk to agricultural production in coming decades. An overall increase in annual precipitation is predicted for northern Europe, but Sweden could still face an increasing need for irrigation, as shown by the drought summer of 2018. Adaptation of Swedish agriculture to include irrigated agriculture should thus be considered. To evaluate the theoretical need for irrigation, calculations were performed for different locations in Sweden, and for different soil-crop pairs at each location. In-situ weather data from a projected climate dataset created by the Swedish Meteorological and Hydrological Institute were used to evaluate changes in irrigation need over the period 1981–2050. The results showed an increasing need for irrigation of cereal crops during the early season (May–June), for two main reasons: i) A shift to an earlier start of the cropping period, leading to an earlier need for irrigation; and ii) a higher probability of dry spring weather, substantially increasing the irrigation requirement in dry years. Crops for which the growing season starts later (e.g., potatoes) showed an increasing need for irrigation during July. Crop development stages were predicted to occur earlier, leading to earlier harvesting, reducing the irrigation requirement in August. However, the calculation approach developed for this study may have underestimated the need for irrigation, which could be higher than reported here.

Modeling the response of winter wheat phenology to low temperature stress at elongation and booting stages

Accurately predicting crop development stage is key to simulating growth and yield formation in crop models. Low temperature stress is a major limitation to global wheat production and can significantly slow down wheat development rate. In a four-year environment-controlled phytotron experiments, detailed phenology datasets were obtained for low temperature stress treatments with different temperature levels and durations. Six widely-used temperature response functions (Linear, Bilinear Triangular, Trapezoidal, Bell-shaped, and Sin) for wheat phenology estimation were combined with WheatGrow model to simulate the low temperature stress effects on elongation-anthesis durations in order to test whether the effects of low temperature stress can be captured by current temperature response functions. In addition, a new algorithm for quantifying daily thermal sensitivity (DTS) was proposed and applied in the six temperature response functions to improve the prediction ability of phenology submodel under low temperature stress. The result indicates that anthesis stage was significantly delayed under low temperature stress at elongation and booting stages. All six original temperature response routines underestimated the delay of wheat development rate caused by low temperature stress, and the Linear and Triangular temperature response routines showed better performance than other four functions. A new improved DTS algorithm (DTSimproved) was proposed which can better quantify the delay of wheat development rate during low temperature stress and the recovery of development rate after low temperature stress. Model validation results show that compared with the DTSoriginal routine, all six improved phenology submodels (DTSimproved) significantly reduced the simulation error under low temperature stress, with the RMSE of elongation-anthesis duration under extreme low temperature stress (Tmin<0) decreased by 53.6% and 36.7% for cv.Yangmai16 and cv.Xumai30, respectively. Therefore, the newly improved routine for wheat phenology under low temperature stress can significantly reduce the uncertainties in model-based impact assessments under low temperature stress.