Seasonal Variations In Yield Research Articles

Early-Season forecasting of citrus block-yield using time series remote sensing and machine learning: A case study in Australian orchards

This study presents a comprehensive evaluation of seasonal, locational, and varietal variations in canopy reflectance responses in 315 commercial citrus blocks from three major growing regions in Australia. The dataset includes three different citrus types (Mandarin, Navel, Valencia) and 26 varieties. The aim is to utilize this combined information to better understand yield variation and develop improved forecasting models. Landsat satellite data spanning from October 2006 to February 2021 (1419 tiles) were used to derive reflectance values, and calculate four vegetation indices (NDVI, GNDVI, LSWI, and GCVI), for each citrus block. These indices were then analyzed alongside corresponding yield data, which consisted of 3660 individual yield records dating back to 2007. Two temporal resolutions were incorporated as predictors: spatio-temporal vegetation index time series (TS) aggregated every two months and annual time series of historical block-yield records. Six statistical and machine learning algorithms were calibrated using a leave-one-year-out cross-validation approach (LOYO CV) and validated for one-year forward prediction over a five-year period (2017–2021). The results highlight significant yield variations across years, alternate bearing patterns, and spatio-temporal changes in reflectance profiles influenced by seasonal conditions, varietal characteristics, and locations. The support vector machine (SVM) algorithm with a radial basis function kernel consistently outperformed other algorithms, indicating a non-linear relationship between citrus yield and predictors. The SVM model achieved an RMSE of 15.5 T ha−1, R2 of 0.88, MAE of 12.1 T ha−1, and MAPE of 29% in predicting block-yield across farms, varieties, and seasons. These prediction accuracy metrics demonstrate an improvement over current forecasting methods. Notably, the proposed approach utilizes freely available imagery, provides forecasts between two to nine months before harvest, and eliminates the need for infield counting of fruit load for image calibration. This approach provides an improved method for understanding seasonal yield variation and quantifying citrus block-yield, offering valuable insights for growers in harvest logistics, labor allocation, and resource management.

Seasonal Variations in Yield and Biochemical Composition of the Mediterranean Saltbush (Atriplex halimus L.) Under Saline Agriculture in Semi-Arid Regions

Seasonal Variations in Yield and Biochemical Composition of the Mediterranean Saltbush (Atriplex halimus L.) Under Saline Agriculture in Semi-Arid Regions

Seasonal Variation in the Essential Oil Yield and Composition of Cinnamomum parthenoxylon (Jack) Meisner.

Cinnamomum parthenoxylon (Jack) Meisner is an important natural aromatic plant because its leaves are rich in essential oil. Linalool chemotype C. parthenoxylon was used as the research material in the present study. The leaf essential oil yield, the main chemical components, and their content were measured every month from January to December 2018 to study the seasonal variation in the yield and chemical components of C. parthenoxylon leaf essential oil. The results revealed that the essential oil yield and the main chemical component linalool in the essential oil of C. parthenoxylon leaves showed significant differences among months. The leaf essential oil yield and linalool content decreased to the lowest in March and increased rapidly from April to May. The leaf essential oil yield was the highest in May, and a relatively high yield was maintained from April to August. The linalool content in leaf essential oil was stable in other months except March. The leaf essential oil yield of C. parthenoxylon had a very significant positive correlation with monthly rainfall and monthly average temperature. Intense rainfall and high monthly average temperature were conducive to the synthesis and accumulation of C. parthenoxylon leaf essential oil. This study provided a theoretical basis for cultivating C. parthenoxylon as a raw material for spices and determining the best harvest time.

Risk of Rice Cultivation under Current and Future Environment and Market

Risk is an inevitable feature of agriculture globally, and it might increase over time in the future. The study assesses the risk of rice cultivation in the three seasons under current and future conditions. The software programme @Risk version 7.6 was used to simulate the risk-return trade of rice cultivation in the three seasons in Bangladesh. The likelihood of having negative net income for the Aus (90%) and Boro (80%) rice was very high under the current market and environmental conditions. Besides, the chance of obtaining negative net income was notable for T. Aman (33%). Both the yield and price variation significantly contributed to the fluctuation of returns of rice production. However, with the current seasonal variation in yield, the probability of having negative net income for paddy rice was very low under the farmers’ expected price (Aman: 22.5 BDT kg-1, Boro: 25 BDT kg-1 and Aus: 24 BDT kg-1). The result indicates that only access to the fair price of the rough rice can ensure the economic sustainability of the rice production. Likewise, chances of having a negative net income of paddy rice in 2030 will be zero under the extrapolated yield (Aman: 5.3 kg ha-1, Boro: 6.3 kg ha-1 and Aus: 4.8 kg ha-1) and price (Aman: 31.75 BDT kg-1, Boro: 30.75 BDT kg-1 and Aus: 30 BDT kg-1). The findings indicate that rice cultivation in the three seasons will be economically sustainable, subject to achieving the expected genetic gain and ensuring access to the projected price. Thus, policy supports are needed to ensure farmers' access to a fair price, improve management practice, and strengthen research to enhance genetic gain for sustainable rice farming under future conditions. Bangladesh Rice J. 25 (1) : 101-110, 2021

Seasonal variation in yield, nutritive value, and antioxidant capacity of leaves of alfalfa plants grown in arid climate of Saudi Arabia

In addition to its high nutritional value, alfalfa (Medicago sativa L.) has several health benefits including antioxidant, neuroprotective, antimicrobial, antiulcer, hypocholesterolemic, hypolipidemic, and estrogenic effects. We aimed to assess the nutritional value and antioxidant capacity of alfalfa leaves at different times of the year in arid regions. Alfalfa was harvested in autumn, winter, spring, and summer and fresh yield and leaf:stem ratio were measured. Leaves were collected to determine their nutritional value and antioxidant capacity using two different extracts viz.: absolute ethanol or distilled water. Fresh yield and leaf:stem ratio were highest in spring (20 t ha-1 and 57.6%, respectively), followed equally by winter and autumn, and were lowest in summer (10.75 t ha-1 and 51.6%, respectively). The autumn cut had the highest crude protein (33.52%) and crude fat content (3.79%) and the lowest content of crude fiber (13.95%) and acid detergent fiber (16.55%), which are good indicators of suitability for human nourishment. However, leaves collected in autumn were characterized by lower digestibility values (86.2%) compared to the other cuts. Antioxidant capacity of leaves harvested in autumns and extracted with either ethanol or distilled water was examined in terms of total polyphenols, total flavonoids, DPPH scavenging capacity, and reducing power. Ethanol extract showed higher antioxidant capacity in terms of total phenol and total flavonoid contents (6.41 and 4.88 mg gallic acid equivalents g-1 DW, respectively). These results suggest that autumn is the most appropriate season to cut alfalfa leaves for human nutritional purposes.

Water productivity improvement in summer maize – A case study in the North China Plain from 1980 to 2019

Improving water productivity (WP) in grain production (WPg) is critical for maintaining food supply in regions with water shortage. A long-term field experiment from 1980 to 2019 was used to investigate the changes in WPg and its influencing factors for summer maize in the North China Plain (NCP). The results showed that grain yield increased from 5.1 t ha−1 to 8.8 t ha−1 and WPg from 1.35 kg m−3 to 2.36 kg m−3 during the past four decades under full irrigation condition. Overall, a 75% increase in yield and a 73% increase in WPg were achieved. Further analysis indicated that in 1980 s and 1990 s, the improvements in yield and WPg were mainly associated with a significant increase in biomass production which was related to the increase in fertilizer use and the improvement in soil fertility. In 2000 s and 2010 s, the increase in yield and WPg was due to a significant increase in harvest index (HI) which was related to the introduction of modern hybrid maize. Overall, increased HI contributed to 65% of the WPg increase for the past 40 years. The results also indicated that during the recent years, large seasonal yield variation was observed which was related to some deteriorating weather factors such as the reduced sunshine hours and the large variation in temperature. Based on the linear positive correlation of grain yield with WPg, management practices that can minimize the negative effects of weather on grain production would favor an improved WPg in future.

Meteorological and Climate Modelling Services Tailored to Viticulturists

Grape production is likewise inherently interconnected to climate and weather, and, although grapes may grow worldwide, premium wine-grape production occurs in Mediterranean-like climate ranges. Changes in climate and weather patterns are threatening premium wine-grapes, directly affecting the European wine industry. This is because grapevines are extremely sensitive to their surrounding environment, with seasonal variations in yield much higher than other common crops, such as cereals. With a view to making South European wine industry resilient to climate change, VISCA (Vineyards Integrated Smart Climate Application) project has deployed a Climate Service (CS) Decision Support System (DSS) tool that provides to wine producers with well-founded information to be able to apply correctly adaptation strategies on specific grape varieties and locations, and to achieve optimum production results (e.g., yield and quantity). In this paper we show the meteorological, seasonal and climatic models and data sets used to answer the viticulturist needs; from short-term and mid-term forecast to seasonal forecast and climate projections.

Seasonal variations in yield, fatty acids, amino acids and proximate compositions of sea urchin (Paracentrotus lividus) Roe

Sea urchin (Paracentrotus lividus) roes are popular delicacy to human. In this study, seasonal variations in the yield, fatty acid, amino acid and proximate compositions of sea urchin roe were studied. The average yield was 5.45 ± 2.21%. Protein, crude fat, moisture, ash and carbohydrate contents were 12.03 ± 1.26%, 3.05 ± 0.50%, 79.87 ± 1.43%, 2.25 ± 0.24%, and 2.80 ± 2.41%, respectively. The fatty acids of C16:0, C20:5 n3 and C22:2 n6 were the important fatty acids, whereas the major amino acids were glutamic acid (non-essential, NE), glycine (NE), aspartic acid (NE), lysine (essential, E) and arginine (NE). The E/NE ratio was 0.58 ± 0.01 and fatty acids were rich in PUFA. It was concluded that sea urchin roes are rich sources of unsaturated fatty acids, proteins and amino acids, which are the essential components of human nutrition.

Seasonal variation in yield and chemical composition of Moroccan Thymbra capitata (L.) Cav. essential oil and its corresponding hydrolat extracted essential oil

The aim of the present work was to study the variation in yield and chemical composition of the pure essential oil (EO) and essential oil dissolved in its corresponding hydrolat (HEO) of Thymbra capitata (L.) Cav. of Morocco according to its stage of growth. The results obtained revealed that the yield of essential oil increases with the growth of the plant to reach its maximum at post-flowering stage (2.90%). On the other hand, the yield of dissolved essential oil in the corresponding hydrolats peaked at the flowering stage (0.53%) and then dropped. The analysis of these oils was performed by the GC-MS and showed that carvacrol was the major compound of this plant during its growth stage. The highest carvacrol content was noted at the flowering stage for EO (84.26%) and at the pre-flowering stage for HEO (98.54%). However, the evolution of concentration of p -cymene (3.84-6.01%) and g- terpinene (3.45-5.68%) in EO seems to be the opposite of carvacrol. Moreover, these two monoterpene hydrocarbons are absent or almost absent in HEO.

Selecting Traits to Reduce Seasonal Yield Variation of Summer Maize in the North China Plain

Core Ideas Seasonal yield variation was up to 47 and 42% under deficit and full irrigation, respectively. Seed weight was the main yield component affecting the annual yield variation. Diurnal temperature range and daily reference ET were positively related to grain yield during grain‐fill. Smaller upper‐leaf angle, more aboveground biomass, high harvest index, and early tasseling were desirable traits. Due to the short growth duration of summer maize, which is planted after winter wheat harvest to form the annual double cropping system in the North China Plain (NCP), maize yield is significantly affected by weather conditions. This study examined the seasonal yield variation and the effects of weather factors on yield and yield components of summer maize under full irrigation (FI) and deficit irrigation (DI) conditions during 2008 to 2016 using a local popular cultivar ‘Zhengdan 958’. In addition, eight cultivars in 2010 to 2012 and 16 cultivars in 2013 to 2016 were tested to examine crop responses to weather factors. Results indicated that seasonal yield variation was up to 47% of the average yield of the nine seasons. Grain kernel weight was the main yield component affecting annual yield variation under FI. Further analysis showed that daily maximum temperature (Tmax), diurnal temperature range (DTR), and daily reference evapotranspiration (ET0) were each positively related to grain kernel weight from blister stage to maturity. Results from the cultivar tests showed that the yield difference among the cultivars was up to 35% of the average grain yield. Selecting cultivars with higher yield potential in each season could decrease the seasonal yield variation up to 32%. Cultivars with smaller leaf angle of upper leaves, higher final aboveground biomass, higher harvest index, and an earlier tasseling date would likely lead to more stable, higher yields for short season maize in the NCP.

Temporal yield variability in subtropical table grape production

Inconsistent yield between seasons for table grape cultivars grown in subtropical climates in Australia presents a challenge to the industry in terms of marketing and economic sustainability. The pattern of this yield inconsistency has not been described. Marketable fruit yields of three cultivars (Red Globe (RG), Menindee Seedless (MS) and Flame Seedless (FS)) were acquired over 14 seasons, and individual vine yields of MS were collected for a four-season period from a vineyard in the Central Highlands of Queensland, Australia. Cultivars FS and RG did not show an alternate bearing pattern. Yields of MS varied up to four-fold in consecutive seasons. An alternate yielding pattern as measured by the indicators of an alternate bearing index (I) and associated probability calculated using a resampling process was evident in 7 (2009–2015) of the 14 monitored seasons. Individual vine yield over the four-season period 2014–2017 was irregular and 90% variation in vine yields was due to the variation in the number of bunches per vine. The seasonal yield variation of MS was partly explained (R2 = 0.31, P < 0.05) by the mean monthly temperature in October of the year preceding harvest. This result is ascribed to the effect of high temperature during inflorescence initiation and early development which occurs in October in the Central Highlands of Queensland.

Seasonal changes in dry matter yield from Karst pastures as influenced by morphoclimatic features.

Pastures are strongly affected by local environmental variables in terms of their species richness, plant composition and herbage production. A multi-site monitoring study was conducted over three years to investigate the influence of morphoclimatic factors on the seasonal variations in dry matter (DM) yield from Karst pastures. Seven sites located on the Italian and Slovenian Karst regions were investigated that differed in terms of their geological and geomorphological features, as well as their soil types. At each site, the daily DM yield (kg ha-1 d-1) was determined using Corral-Fenlon method which permits to simulate herbage utilization from grazing herds. The morphoclimatic features were also analysed, with the aim to evaluate the link between seasonal DM yield and geomorphological and environmental factors. Generalized non-linear mixed models were built to study the observed seasonal variations in DM yield, using day of the year (DOY), growing degree days (GDD), and cumulative rainfall. Furthermore, environmental descriptors were included in the model in order to evaluate their effects on DM yield. The seasonal variations in yield showed two growing periods (spring and late summer), which were described by Gaussian curves. For the spring growing period, the model improved when the interaction between soil granulometry and growing degree days corresponding to the curve peak was taken into account. This confirms the influence of soil type and air temperature on pasture yield. For the late summer growing period, the interaction between the sand classes and the number of rainy days from the beginning of the period to the peak of the curve improved the model. The curve parameters of our models are correlated with environmental descriptors depending on the lithology and particle size of soils. The results are essential for the optimization of pasture management and avoiding degradation due to over- or under-grazing.

Performance of New Released Winter Wheat Cultivars in Yield: A Case Study in the North China Plain

Genetic gains play important roles in crop yield improvement. This study used the observation data from two cultivar test sites under limited irrigation and without irrigation for 11 seasons from 2002 to 2013 in the North China Plain (NCP) to examine the yield and yield characters of newly released winter wheat (Triticum aestivum L.) cultivars as compared with the control (CK). Large seasonal yield variation of – 40 to 37% was observed due to the fluctuations in the weather condition. The average yield of newly released cultivars (NRs) was similar to that of the same control cultivar at the two sites during the 11 seasons, indicating that NRs had characters that responded to seasonal weather variation similarly and they might not be better in offsetting the negative climatic effects on grain production as compared with the CK. However, there were always cultivars that out‐performed the control in yield around 10% for the 11 seasons, indicating the possible genetic gains in using new cultivars. The number of seeds per area played a critical role in determining the final yield of winter wheat, which was significantly affected by the weather conditions during the seedling and vegetative growing stages. Selecting cultivars with high vitality at seedling stage was important in this region. Under rain‐fed conditions, the significant positive correlation (P &lt; 0.01) of percentage of the roots in deep soil with the final yield indicated the selection and breeding for root traits could result in a yield benefit. Two sites of cultivar test was used to analyse the possible genetic gains. Average yield of new released cultivars was the same with the control cultivar. Cultivars performed better usually had a higher seed numbers per area. Cultivars performed better under rain‐fed condition had a prolific root system. Weather factors of temperature and sunshine hours being significantly related to yield.

Assessing the contribution of weather and management to the annual yield variation of summer maize using APSIM in the North China Plain

Long-term field experimental data provides a good opportunity to evaluate the effects of different management practices and weather factors on maize yield. An 11-year field experiment (2003–2013) with the same maize cultivar and two short-term experiments including different sowing dates and plant densities were conducted at Luancheng Agro-ecological Experimental Station in the North China Plain (NCP). The measured pheonological development, biomass and grain yield were used to calibrate and validate the APSIM-maize model. The results showed that APSIM-maize model could capture the biomass and grain yield of summer maize under the various management practices and weather conditions. After calibration and validation, five scenarios were simulated using the APSIM model. The simulated results showed that weather factors including sunshine hours and the diurnal temperature range during the grain fill stage had the positive effects on maize yield. For different management practices, plant density was the most important factor which affected the maize yield. The optimal plant density was approximate 8.6plants/m2. Maize yield would be decreased with the sowing dates delayed after the middle of June. Meanwhile, earlier sowing before the end of May also reduced the grain production. The optimized sowing date and plant density could reduce the seasonal yield variation of maize caused by the weather factors. The findings of this study suggest that the maize plant density should be properly increased and sowing time should be optimized according to the harvesting of its previous crop.

Factors controlling inflorescence primordia formation of grapevine: their role in latent bud fruitfulness? A review

The grapevine (Vitis vinifera L.) is a widely cultivated species of major economic importance for wine production. The quality and quantity of grapes are criteria of prime importance to the wine industry, but they are highly variable from year to year. Unlike many perennial plants, cluster formation unfolds in two seasons: season 1 takes place in the bud until dormancy, and season 2 starts after budbreak in the following year. Season 1 corresponds to the initiation and differentiation of inflorescence primordia, controlled by many exogenous and endogenous factors, which explains up to 60% seasonal variation in yield. Season 2 consists of flowering and fruit development, which explains, respectively, 30% and 10% of seasonal variation in yield. It is therefore essential to understand the impact of these factors to better control the yield. This review aims to summarize past and present knowledge concerning the physiology of latent buds relating to their fruitfulness, and to assess the impact of environmental, hormonal, and regulation factors on the final yield. Avenues of further research to understand physiological, biochemical and molecular regulatory mechanisms of initiation and differentiation of clusters will be then proposed.

Seasonal Variation in Yield and Composition of Essential Oil from Satureja cuneifolia Ten. Growing Wild in Lebanon

Seasonal variation in chemical composition of essential oils obtained from fresh aerial parts of S. cuneifolia was determined by GC and GC-MS. The fresh plant materials were collected before and after flowering, and during beginning and maturation fruit stage from two different locations. Thirty five components were identified; carvacrol (20.4-52.1 %), p-cymene (9.1-30.2 %) and γ-terpinene (5.9-23.9 %) were the main components. In general, the qualitative composition of the components appeared to be relatively stable but carvacrol, p-Cymene and γ-terpinene showed variability. We also note that phenolics and monoterpene hydrocarbons were the major components. All the essential oils were found to be rich in carvacrol reaching the highest rate (52.1 %) during full blooming stage, while the highest percentage of thymol ranging (18.7 %) was reached only in the sample of essential oil from S. cuneifolia collected in the region of Ehden.

Crop model usefulness in drylands of southern Africa: an application of DSSAT

Crop models are useful tools for simulating impacts of climate and agricultural practices on crops. Models have to demonstrate the ability to simulate actual crop growth response in particular environments before application. Data limitations in southern Africa frequently hinder adequate assessment of crop models before application. The DSSAT model was used to test the usefulness of crop models under data-limited dryland conditions of southern Africa by validation using data from experimental trial reports and district-wide crop yield estimates. Two crops each were selected in three locations to represent varying cropping and physical conditions in southern Africa, i.e. maize and sorghum (Mohale's Hoek, Lesotho and Big Bend, Swaziland) and maize and groundnut (Lilongwe, Malawi). DSSAT performs well in simulating crop yields obtained from experimental trials. District-wide simulated mean crop yields were acceptable (relative difference ranged from −12.2% to +2.36%). However, the model's capture of seasonal yield variation for some locations and crops was uncertain due to climate extremes. It was concluded that satisfactory crop model testing before application is possible and that DSSAT crop models are useful even under data-limited conditions.

Defining agro-ecological regions for field crops in variable target production environments: A case study on mungbean in the northern grains region of Australia

The northern grains region (NGR) of Australia, which includes the state of Queensland and the northern half of the New South Wales, has highly variable climate leading to heightened production risk for all rainfed crops. Characterisation of the production environment of this region can assist in exploration of potential opportunities for reducing this risk. In this case study on mungbean (Vigna radiata L. Wilczek.) we demonstrate how this region could be characterised using the Agricultural Production Systems sIMulator (APSIM) model. The model was first evaluated for variety Crystal grown widely in the region, and then applied to simulate a water stress index (the daily supply and demand ratio) and yield from 1889 to 2012 at 28 locations. The model was run using location specific as well as three generic soils of 136, 166 and 204mm plant available water holding capacities (PAWC). Two complementary characterisations were performed using the simulated output, one based on clustering of supply demand ratio averaged for every 100°Cd to and from flowering, and another on clustering of percentile rankings of seasonal yield variation at different locations. Clustering of supply demand ratio revealed four drought patterns (i.e., target production environments) which commenced at different times from flowering. Seasonal frequencies of these drought patterns, which differed due to major location effects and relatively smaller soil effects, accounted for significant (∼84%) variation in simulated yield. Clustering of percentile ranks corresponding to simulated yield in different seasons identified seven meaningful yield clusters. Location memberships of these yield clusters were geographically contiguous and were only slightly influenced for the lowest PAWC generic soil. All locations within these yield clusters showed a tendency to have similar seasonal drought patterns and their frequencies. Locations within different yield clusters could therefore be considered as part of distinct agro-ecoregions. These model defined agro-ecoregions could be used as selection environments for their dominant target production environment(s) to develop new genotypes and their agronomy for better adaptation and yield under variable climatic conditions.

Contribution of cultivar, fertilizer and weather to yield variation of winter wheat over three decades: A case study in the North China Plain

Long-term field measured yield data provides good opportunity to assess the impacts of climate and management on crop production. This study used the yield results from a long-term field experiment (1979–2012) at Luancheng Experimental Station in the central part of the North China Plain (NCP) to analyze the seasonal yield variation of winter wheat (Triticum aestivum L.) under the condition of sufficient water supply. The yield change of winter wheat over the last 33 growing seasons was divided into three time periods: the 1980s, the 1990s, and the years of 2001–2012. The grain yield of winter wheat during the 1980s was relative stable. During the 1990s, the annual yield of this crop was continuously increased by 193kg/ha/year (P<0.01). While for the past 12 years, yield of winter wheat was maintained at relative higher level, but with larger seasonal yield variation than that back in 1980s. CERES-Wheat model was calibrated and was used to verify the effects of management practices on grain yield. Seven scenarios were simulated with and without improvements in management. The simulated results show that the yield of winter wheat was decreased by 5.3% during 1990s and by 9.2% during the recent 12 seasons, compared with that during 1980s, under the scenario that the yield of winter wheat was solely affected by weather. Seasonal yield variation caused by weather factors was around −39% to 20%, indicating the great effects of weather on yearly yield variation. Yield improvement by cultivars was around 24.7% during 1990s and 52.0% during the recent 12 seasons compared with that during 1980s. The yield improvement by the increase in soil fertility and chemical fertilizer input was 7.4% and 6.8% during the two periods, respectively. The initial higher soil fertility and chemical fertilizer input might be the reasons that the responses of crop production to the further increase in chemical fertilizer were small during the simulation period. Correlation analysis of the grain yield from the field measured data with weather factors showed that sunshine hours and diurnal temperature difference (DTR) were positively, and relative humidity was negatively related to grain yield of winter wheat. The climatic change trends in this area showed that the DTR and sunshine hours were declining. This type of climatic change trend might further negatively affect winter wheat production in the future.

Adaptation potential of the novel oilseed crop, Honesty ( Lunaria annua L.), to the Scottish climate

This paper reports on the adaptation potential of the biennial novel crop, Honesty ( Lunaria annua L.), to the Scottish climate. L. annua is being developed as a crop because of interest, by the oleochemical industry, in fatty acids contained within its seed, notably erucic and nervonic acids. Optimum sowing rate of the seed in these trials was approximately 15 kg ha −1 in rows spaced 0.5 m apart giving a spring plant population of approximately 20 plants m −2. Crops gave best yields when sown around mid May to mid June. A sowing date after mid July is unlikely to produce a harvestable crop. It should be possible to achieve yields approaching 2 t ha −1 in a commercial situation in Scotland, with this figure comparable to yields attained in trials in Southern England and the Netherlands. However, large seasonal variations in yield may be observed, as was the case here. A fatty acid content approaching 30% of the seed dry weight should be possible, with around 23% of this being oleic acid, 46% erucic acid and 20% nervonic acid. A major hurdle to commercialisation of L. annua is its biennial nature, although annual cultivars are being developed.