Open AccessArticle

Historic Grain Sorghum Production, Value, Yield Gap, and Weather Relation Trends

Yared Assefa

^1,*

Johnathan D. Holman

^1,*,

Augustine K. Obour

Daniel O’Brien

³ and

P. V. V. Prasad

⁴

Department of Agronomy, Kansas State University, 4500 E. Mary St., Garden City, KS 67846, USA

Department of Agronomy, Kansas State University, Agricultural Research Center-Hays, 1232 240th Ave., Hays, KS 67601, USA

Department of Agricultural Economics, Kansas State University, NW Research Extension Center, Colby, KS 67701, USA

⁴

Feed the Future Innovation Lab for Collaborative Research on Sustainable Intensification, Kansas State University, Manhattan, KS 66506, USA

Authors to whom correspondence should be addressed.

Agronomy 2024, 14(11), 2582; https://doi.org/10.3390/agronomy14112582

Submission received: 18 September 2024 / Revised: 17 October 2024 / Accepted: 29 October 2024 / Published: 1 November 2024

(This article belongs to the Section Farming Sustainability)

Download

Browse Figures

Figure 1
Average grain sorghum total, irrigated, non-irrigated area planted and harvested from (a) 1929 to 2022, (b) 1929 to 2000, and (c) 2000 to 2022 in Kansas. "> Figure 2
Grain sorghum economic value from (a) 1949 to 2022, (b) 1949 to 1990, and (c) 1991 to 2022 in Kansas. "> Figure 3
Grain sorghum total production from (a) 1929 to 2022, (b) 1929 to 1979, and (c) 1980 to 2022 in Kansas. "> Figure 4
Grain sorghum average, irrigated, and non-irrigated yield ha−1 from (a) 1929 to 2022, (b) 1929 to 1979, and (c) 1980 to 2022 in Kansas. Throughout this paper, trend line equations with NS are not significant, with * being significant at p < 0.05, ** significant at p < 0.01, and *** significant at p< 0.001 probability level. "> Figure 5
Grain sorghum yield trend (top panel (a–c)) and yield distribution (lower panel (d–f)) for average (left panel (a,d)), irrigated (central panel (b,e)), and non-irrigated (right panel (c,f)) yield ha−1 from 1929 to 2022 at nine agricultural districts of Kansas. "> Figure 6
Average grain sorghum yield trend for non-irrigated (left panel (a,c)) and irrigated (right panel (b,d)) yield ha−1 from 1955 to 2022 (top panel (a,b)) and 2000 to 2022 (lower panel (c,d)) at Colby, Garden City, Hays, and Tribune Kansas Hybrid Sorghum Trials data. Trend line equations with NS are not significant, with * being significant at p < 0.05, ** significant at p < 0.01, and *** significant at p < 0.001 probability level. "> Figure 7
Annual yield variability and trend in (a) USDA state average, (b) KGSHT non-irrigated, and (c) irrigated grain sorghum detrended yield using differencing data from USDA and trials at Colby, Garden City, Hays and Tribune, KS. Blue cone-shaped lines indicate how lower and upper margins of yield difference change over time despite an overall trendless variation. Throughout this paper, trend line equations with NS are not significant, with * being significant at p < 0.05, ** significant at p < 0.01, and *** significant at p < 0.001 probability level. "> Figure 8
Yield gap analysis through relationship between actual (a) non-irrigated and (b) irrigated yield from Thomas, Finney, Ellis, and Greeley County USDA data and potential yield from variety trials at Colby, Garden City, Hays, and Tribune cities. Throughout this paper, trend line equations with NS are not significant, with * being significant at p < 0.05, ** significant at p < 0.01, and *** significant at p < 0.001 probability level. ">

Versions Notes

Abstract

There is limited information regarding the grain sorghum production trends from early in the millennium towards the 2020s. The main objective of this study was to quantify the grain sorghum production area, economic value, productivity, annual production variation, relationship with changing weather patterns, and yield gap and to identify future areas of intervention and research. The results indicated that the grain sorghum production area in Kansas has increased in the most recent decade (2010–2022) at an average rate of 8 thousand ha year⁻¹. With the current 1.2 million ha harvest area, Kansas continues to allocate more land area for sorghum than any other state in the USA. The average current annual economic value of sorghum in Kansas is USD 0.5 billion. The average sorghum grain productivity for recent years (2000–2022) was 4.3 Mg ha⁻¹ in Kansas. The year-to-year yield variation in the grain sorghum average for Kansas in the years 1929–1956 was ±0.5 Mg ha⁻¹ but increased to ±2 Mg ha⁻¹ for the years 1957–2022. The results also showed a 66 to 96% yield gap between the actual yield (USDA data) and potential non-irrigated yield (Kansas State Grain Sorghum Hybrid Performance Trial data). There was a significant positive correlation between the July–August precipitation and a significant negative correlation between air temperatures and sorghum yield. We conclude that there was an increasing sorghum harvest area trend in Kansas for the years 2010 to 2022. Further research that identifies more unique and important agronomic and economic advantages of sorghum, increasing productivity per unit area across different environments, communicating existing benefits, and developing crop production management best practices are essential to sustain gains in the production area.

Keywords:

sorghum; yield trend; yield gap; yield–weather relations

1. Introduction

Sorghum (Sorghum bicolor L. Moench) is produced in more than 100 countries and ranked the fifth most important cereal crop in the world [1,2]. The global total production of sorghum in 2023 was estimated to be about 60 million Mg, compared with about 1235, 785, 514, and 143 million Mg for corn or maize (Zea mays L.), wheat (Triticum aestivum L.), rice (Oryza sativa L.), and barley (Hordeum vulgare L.), respectively [3]. Over the past six decades (1960–2020), the productivity (yield per area) of all these major crops has increased significantly, albeit at lower rates in recent decades, due to advancements in technology, genetics, and fertilizer application [4,5]. However, like wheat, global research reports indicated a decline in sorghum production area for the years from 1980 to the 2010s, while the production area for corn and rice has increased significantly [6,7]. The question of whether this reported decline in the sorghum production area continued towards the 2020s is a research gap.

The USA is ranked first in sorghum production globally, contributing about 13% of global total production, followed by Nigeria (11%), Sudan (8%), Mexico (8%), and Ethiopia (7%) in 2023 [5,6]. Within the USA, sorghum ranked fourth in area and production after soybean (Glycine max L. Merril), corn, and wheat [8]. In recent years, sorghum’s planted area in the USA was about 2 million ha [9]. The grain sorghum yield increased from 0.7 Mg ha⁻¹ to above 3.5 Mg ha⁻¹ from the early 20th century to the early 21st century. Eghball and Power [10] reported a 50 kg ha⁻¹ yr⁻¹ yield increase in the USA for the years from 1930 to the 1990s. Unger and Baumhardt [11] also reported a 139% grain sorghum yield increase for the years 1956 to 1997. Grain sorghum production in the USA is concentrated around the Great Plains region, specifically called the “Sorghum belt”. This includes all or parts of Texas, Oklahoma, Colorado, Kansas, Missouri, Nebraska, Illinois, South Dakota, New Mexico, and Georgia [9,12].

In the USA, Kansas was the leading grain sorghum producing state in 2023, contributing about 55% of the total sorghum produced, followed by Texas with 21% [3]. Due to advancements in hybrid technology and increased N fertilizer application, a 50 kg ha⁻¹ yr⁻¹ yield increase in the non-irrigated grain sorghum was reported for Kansas between 1957 and 2008 [13]. However, the sorghum area has been in a decline starting from the early 1980s due to changes in government policies, improved dryland corn hybrids, and high corn prices relative to sorghum [6]. This decline in sorghum area due to replacement by newly developed drought-tolerant corn hybrids and other high value crops was a global phenomenon and not restricted only to Kansas or the USA [14,15].

Grain sorghum is a drought- and heat-tolerant crop compared to other cereals and has significant prospects as climate variability and incidents of drought or heat stress occur across the globe [16,17]. Research efforts on sorghum have significantly increased because of the recognition of the potential of sorghum as an important food and feed crop, as well as the potential for use as a biofuel crop in dryland regions. This is particularly true in regions with frequent drought and has motivated scientists to learn from the sequenced sorghum genome [18]. However, the impacts of these research efforts have not been fully evaluated, and a recent assessment of the grain sorghum production area and other trends is a research gap. Therefore, this study was initiated to analyze the current trends in grain sorghum production in Kansas, with the main objective of quantifying the trends in grain sorghum production, economic value, productivity, annual production variation, the relationship with changing weather patterns, and yield gaps, together with identifying future areas of intervention and research.

2. Materials and Methods

2.1. Data Sources and Area of Study

The data for this study were organized from two sources. The first data source was United States Department of Agriculture (USDA) grain sorghum historic survey data for the state of Kansas, across nine districts and selected counties [9]. The grain sorghum area (planted and harvested), total production, grain sales nominal value, and the average, irrigated, and non-irrigated yield per area in Kansas and four counties (Ellis, Finney, Greeley, and Thomas) for the years 1929 to 2022 were collected from USDA-NASS. Separate irrigated and non-irrigated yields were only available for the years from 1970 to 2022. From the yearly values of the grain production revenues, inflation-adjusted values were calculated by dividing the nominal value to the annual price index for gross domestic product reported by the U.S. Bureau of Economic Analysis [19].

The second source was the Kansas State University Grain Sorghum Hybrid Performance trials (KGSHPTs) conducted near Colby, Garden City, Hays and Tribune Kansas [20]. Colby is in Thomas County, and the soil at the experimental site was Keith silt loam (fine-silty, mixed, superactive, mesic Aridic Argiustolls). Garden City is in Finney County, with soil at the experimental site like that of the Colby location, i.e., Keith silt loam. Hays is in Ellis County, and the soil at the study site was a Harney silt loam (fine, smectitic, mesic Typic Argiustolls); and Tribune is in Greeley County, with Ulysses silt loam (fine-silty, mixed, superactive, mesic Aridic Haplustolls) soil at the study site. Irrigated and non-irrigated average yields of grain sorghum for the years 1955 to 2022 were collected from the KGSHPTs. The weather data for each of the locations were obtained from the Kansas Weather Data Library [21].

2.2. Statistical Analysis

The data analysis in this study was conducted in SAS 9.4 [22]. First, the statewide area, grain sales value, production, and productivity data were plotted over the years and trend was analyzed for periods that show visually recognizable changes. A trend analysis was carried out in SAS using the PROC REG procedure. Similarly, a comparison and linear trend analysis was conducted by district or by location for irrigated and non-irrigated yields for the entire dataset available and for selected periods of time. A change in the year-to-year variation over time on the statewide grain yield was also calculated by detrending the data using differencing. The detrended yield of a year was obtained by subtracting the prior-year yield data from the yield data for that year. The detrended yield was plotted and regressed to obtain the changes in the annual variation over time.

A yield gap analysis for grain sorghum in Kansas was carried out by regressing the yield reported from USDA with the yield report from the KGSHPTs for each location. The departure of the relationship between the USDA and KGSHPTs from the one-to-one line was defined as a yield gap. The research-managed trials (from the KGSHPTs) were assumed to be conducted under supervision and using the best technology available compared with average producer-managed production (from the USDA survey), with the gap between the two assumed to being the difference in potential and actual grain sorghum yield.

A correlation analysis between the grain sorghum yield reported in the KGSHPTs and weather data were conducted using PROC CORR procedure of SAS. This correlation analysis between the yield data and the in-season monthly precipitation and temperature was used to identify the time periods in grain sorghum production that were critical or sensitive to changes that affected yield. An additional correlation analysis was conducted to detect changes in the in-season monthly precipitation and temperature as years change from 1955 to 2022. A significant correlation in this second analysis identified important positive or negative changes in monthly precipitation and temperature over time. All identified significant trends or correlations are at least at the p < 0.05 level.

3. Results

3.1. Planted and Harvested Areas

Sorghum planted and harvested areas fluctuated over the study period between 1929 and 2022 (Figure 1a). The average planted and harvested areas for the first ten years from 1929 to 1939 were about 1 and 0.3 million ha, respectively. Approximately 70% of the acreage during this period was either not harvested or used as forage due to a failure to produce grain. This period was in the midst of the Great Depression with accompanying major, historic dust storms across the U.S., especially including the western states, and with low commodity prices. Planting and harvesting areas reached a peak in 1957 at about 3.3 and 2.5 million ha, respectively (Figure 1b). These areas declined and remained constant at around 1.5 million ha for the years 1960 to 2000 (Figure 1b). For the years 2000 to 2010, the sorghum planting area declined from 1.5 to 1.6 million ha in the early years of the millennium to just below 1 million ha in 2010 (Figure 1c). In recent years (2010 to 2022), the sorghum harvested area fluctuated significantly on a year-by-year basis, but overall, it increased at the rate of 8 thousand ha year⁻¹ (Figure 1c).

The average difference between planted and harvested area over the study period was about 0.4 million ha. The maximum difference between planted and harvested area was about 1.5 million ha in 1955, where more than half of the planted area (2.6 million ha) was not harvested for grain. This coincided with a dry growing season with most precipitation occurring ahead of planting that year. Furthermore, forage was in tight supply and high demand following two dry years (1953–1954), resulting in some sorghum planted for grain harvested for forage. The minimum difference between planted and harvested sorghum area was 0.04 million ha in 2010, when just less than 1 million ha areas were planted and almost all were harvested. The year 2010 had favorable moisture conditions for the state.

The percent irrigated area was much smaller than the percent non-irrigated sorghum planted area, based on the available data for years 1980 to 2009 (Figure 1). The average proportion of irrigated sorghum planted area in Kansas was 11% of the total area planted for sorghum. The maximum irrigated area planted for sorghum was 23% of the sorghum acreage in 1983. The irrigated area planted to sorghum declined over time, and in the early 2000s, only 4–6% of the total sorghum area was irrigated. In the coming years, ongoing declines in the Ogallala Aquifer in western Kansas are anticipated to cause further reduction in available irrigation water and continue the transition from irrigated to either limited irrigated or non-irrigated area. This trend in water availability is anticipated to favor drought-tolerant feed grain crops, either as grain sorghum or drought-adapted corn.

3.2. Economic Value

The average nominal value of sorghum for the state of Kansas in the first eight years (1949 to 1956), when USDA started collecting data, was about USD 40 million (Figure 2a). The value of sorghum tripled to more than USD 100 million in 1957 and remained unchanged until 1971, where the value increased 4-fold to USD 400 million (Figure 2b). The nominal value remained around USD 400 million for most of the years 1971 to 2004 until the next increase to around USD 600 million around 2005 (Figure 2c). Since 2005, the nominal value of sorghum has been approximately USD 600 million for Kansas, with a few significant exceptions in 2020 and 2021, when the sorghum value increased to over a billion dollars (Figure 2c). There was a significant gap between the inflation-adjusted value of sorghum and in the nominal value of sorghum for the years from 1957 to 1990, with the adjusted value being greater than the nominal value. From 1990 to 2022, the adjusted sorghum value has tracked closely to the nominal value, since the adjustment is made based on the recent value of the currency. Prices for grain sorghum were positively impacted by the expansion of U.S. ethanol production, which impacted corn and other crop prices beginning in fall 2006. The ethanol-driven increase in the U.S. corn price had a supportive impact on grain sorghum prices and enterprise revenue over this same period, as it is the competitive substitute feed grain.

3.3. Total Production and Productivity

The total amount of grain sorghum production changed over the years 1929 to 2022 (Figure 3). For the years 1929 through 1956, the average sorghum production in Kansas was about 532 million Mg yr⁻¹ (Figure 3b). In 1957, production increased to 3.2 billion Mg yr⁻¹, and continued to grow up to 6 billion Mg yr⁻¹ in 1979 (Figure 3b). From 1980 through 1999, total sorghum production fluctuated but averaged about 6 billion Mg yr⁻¹ (Figure 3c). Similarly, total sorghum production for the years 2000 to 2022 fluctuated but averaged a little less than 5 billion Mg yr⁻¹ (Figure 3c).

Grain sorghum productivity, defined here as yield per area, followed a similar trend with total production (Figure 4a). For the years from 1929 through 1956, the average sorghum yield in Kansas was about 0.9 Mg ha⁻¹ (Figure 4b). In 1957, sorghum productivity increased to 1.3 Mg ha⁻¹, and it significantly increased to 4.3 Mg ha⁻¹ in 1979 (Figure 4b). This yield increase was coupled with the release of newer sorghum hybrids with an enhanced ability to stand, less lodging, and other improved characteristics [12,23]. From 1980 through 1999, sorghum productivity fluctuated year-to-year and improved slightly with an average of 4.1 Mg ha⁻¹ (Figure 4c). Similarly, grain sorghum yields in 2000 to 2022 fluctuated but remained around 4.3 Mg ha⁻¹.

In the years from 1980 through 2009, when irrigated and non-irrigated grain sorghum data were available, the average irrigated sorghum yield was 6 Mg ha⁻¹ and the average non-irrigated yield was 4 Mg ha⁻¹ (Figure 4). Irrigated yields increased at the rate of 30 kg ha⁻¹ yr⁻¹ (R² = 0.40) and non-irrigated yield increased at the rate of 48 kg ha⁻¹ yr⁻¹ (R² = 0.35), for the years 1980 through 2009.

Across the nine geographic agricultural districts of Kansas, irrigated yields differ only a little (Figure 5). The non-irrigated grain sorghum yield increased from west to east across Kansas, tracking the precipitation gradient across the state. On average, the grain sorghum yield increased at the rate of 50–67 kg ha⁻¹ yr⁻¹ rate across west-to-east in Kansas (R²= 0.62 to 0.74; Figure 5a) for the years from 1940 to 2022. Irrigated yields increased at slower rate of 26 kg ha⁻¹ yr⁻¹ (Figure 5b) compared with 50–61 kg ha⁻¹ yr⁻¹ (Figure 5c) for non-irrigated yields for the years from 1970 to 2009.

3.4. Yield Trend from Hybrid Trial and Yield Variation

The irrigated and non-irrigated grain sorghum hybrid yield trends in western Kansas showed a wide range of yield increases across locations (Figure 6). Non-irrigated yields increased at the rate of 33 to 76 kg ha⁻¹ yr⁻¹ rate across the four west and central Kansas sites for the years 1955 to 2022 (Figure 6a). Irrigated sorghum yields increased 1 to 52 kg ha⁻¹ yr⁻¹ across the four west and central Kansas sites for the years 1955 to 2022 (Figure 6a).

A yield trend analysis restricted to only the years 2000 to 2022, for the irrigated and non-irrigated grain sorghum hybrid in western and central Kansas, also indicated a wider range in non-irrigated yield trend across locations (Figure 6). Non-irrigated yields increased at a rate between 17 and 226 kg ha⁻¹ yr⁻¹ across the four west and central Kansas sites for the years 2000 to 2022 (Figure 6a). A non-significant and small irrigated yield increase at a rate between 33 and 63 kg ha⁻¹ yr⁻¹ was observed across the four west and central Kansas sites for the years 2000 to 2022 (Figure 5a).

The year-to-year yield variation also increased over the years when assessed using both USDA and hybrid trial data (Figure 7). The year-to-year yield variation for grain sorghum average for Kansas in the years 1929–1956 was plus or minus 0.5 Mg ha⁻¹ (Figure 7a). The year-to-year yield variation for grain sorghum increased to plus or minus 2 Mg ha⁻¹ for the years 1957–2022, averaged across Kansas based on USDA data. Variety trial yield data showed a similar increase in yield variation over the time 1955–1980 with yield variation ranging between −2.5 to 2.5 Mg ha⁻¹ to yield variation that range between−4.5 to 4.5 Mg ha⁻¹ for the years 1980–2022 (Figure 7b,c).

3.5. Yield Gap

A significant yield gap was identified between actual yield reported by the USDA for a county and yield reported in hybrid trial data within that county (Figure 8). The actual non-irrigated yield only grew 43–339 kg ha⁻¹ for a 1000 kg ha⁻¹ yield increase in the hybrid trial. That is a 66 to 96% yield gap between the actual and potential non-irrigated yield (Figure 8a). The actual irrigated yield only increased from −132 to 159 kg ha⁻¹ for a 1000 kg ha⁻¹ yield improvement in hybrid trial data. That is an 84 to 113% yield gap between actual and potential irrigated yield (Figure 8b).

3.6. Yield–Weather Relations

There was a significant positive correlation between the non-irrigated grain sorghum yield and July precipitation at all hybrid trial sites except Tribune (Table 1). Also, there was a significant positive correlation between the non-irrigated grain sorghum yield and August precipitation at Garden City and Hays hybrid trial sites (Table 1). There was a significant negative correlation between the non-irrigated grain sorghum yield and July and August temperature at the Hays hybrid trial site only (Table 1). On the other hand, there was a significant positive correlation between the non-irrigated grain sorghum yield and temperature in September at the Tribune hybrid trial site only (Table 1).

There was a significant negative correlation between the irrigated grain sorghum yield and June precipitation at the Colby hybrid trial site, likely due to delayed planting and frost before the crop was fully mature (Table 2). There was no significant correlation between the irrigated grain sorghum yield and precipitation in any of the other in-season months. There was a significant positive correlation between irrigated grain sorghum yield and June and September temperature at the Colby hybrid trial site (Table 2). On the other hand, there was a significant negative correlation between the irrigated grain sorghum yield and temperature in May, but a positive relation with August and September temperatures at the Tribune hybrid trial site (Table 2).

Over the years 1955 to 2022, there was a significant negative correlation between the June precipitation and the year at one location (Colby, Table 3). On the other hand, the October precipitation had a positive correlation with the year at one location (Tribune). There was no significant correlation between precipitation and year in any of the other in-season months. There was a significant negative correlation between the year and the temperature in April and May, but a positive correlation in September and October temperatures at one location (Garden City, Table 3). There was also a significant positive correlation between the temperature in June and September at Hays and Colby locations (Table 3). On the other hand, there was a significant negative correlation between October temperature and years at Tribune (Table 3).

4. Discussion

The first important finding of this study is that, overall, the decline in the grain sorghum planting area in Kansas stabilized, and the area has increased marginally in recent years (2010–2022). This is an important finding because it comes after concerned sorghum industry responses to the declining sorghum planted area since the 1980s [6]. One of the possible reasons for the decline since the 1980s was changes in crop insurance policies, which in some cases favored supporting corn over sorghum. Furthermore, the availability of dryland corn hybrids with similar or greater yield than sorghum, more herbicide options for corn hybrids, such as RoundupReady compared to sorghum, limited post-emergence herbicide options in sorghum, and generally higher prices for corn than grain sorghum contributed to the decline in sorghum acreage [6]. Reported declines in sorghum area for the years 1980 to 2010 were not restricted to Kansas, but also seen across the United States and Asia, with similar reasons that sorghum was replaced with greater value crops [14,15]. However, in recent years, on a few occasions, the price of sorghum was higher than corn due to export demand from China. The input costs for growing a sorghum crop have been comparatively lower than corn. Whenever the profitability (grain price and input expense) of sorghum is favorable over corn, the production of sorghum is economically encouraged. Further analysis across the USA (state-by-state) and the globe may be essential to test if our finding regarding a slow gain in sorghum area in recent years is either just occurring at the state level or also at the global level. The national average sorghum harvest area reported for the U.S. for the years 2010 to the present shows no significant changes [9]. Brauer and Baumhardt [23] predicted an increase in sorghum production in the 21st century in Kansas and surrounding areas due to enacted water policies that favor water-efficient crops compared to corn with limited irrigation production. Other possible explanations for the increased production area in recent years is related to insurance coverage adjustments to crop rotation, with mainly double-crop grain sorghum in more intensive wheat–grain sorghum–grain sorghum–fallow rotations [24]. This is because under new USDA crop insurance policies and regulations, the second grain sorghum is insurable at the same yield level as the first grain sorghum crop, thus reducing production and financial risk and encouraging more sorghum production. However, in semi-arid regions, the second crop grain sorghum has yielded about 60% of the first crop grain sorghum according to the cropping practices and technologies available in the past. With the current 1.2 million ha harvested area, Kansas continues to allocate more land area to sorghum than any other state, followed by Texas with ~0.8 million ha [23,25]. Further expansion of the sorghum production area in Kansas may be dependent on the relative economic value of sorghum relative to competitive crops, as well as the possible expansion of dryland or limit-irrigated sorghum acres because of declining levels of Ogallala Aquifer.

Furthermore, our analysis showed the average current annual economic value of sorghum to the state of Kansas is just above USD 0.5 billion dollars. Exports to countries like China, Japan, Spain, Mexico, and others are among the major drivers of the economic value of sorghum in the U.S. and other countries [26]. In recent years, about 90% of sorghum produced in the U.S. has been exported [27]. Domestic use of sorghum includes human food production (2%), and the remaining 8% for a combination of ethanol and animal feed depending on the price of alternative feedstuffs [28]. As a predominantly non-irrigated crop that is best adapted to water-limited environments, with characteristics of being both gluten free and antioxidant rich, sorghum has a great economic potential in Kansas and surrounding regions [29,30]. However, the current (about 1.4 million ha) area allocated for sorghum production in Kansas is well below that of other crops such as winter wheat (3 million ha) and corn (2 million ha) [31,32]. The price of sorghum grain has generally been 85% and 88% of the price of corn (except during times of strong export demand). This sorghum-to-corn price ratio approximates the relative livestock feed value of these two crops, indicating a need for research to improve the feed value and identify more unique and important advantages of sorghum. Increasing the demand value of sorghum relative to corn should lead to increased production. Although sorghum has a yield advantage to corn under very dry growing conditions, increasing its yield potential in higher yielding environments is needed for sorghum to compete with corn production under less limiting moisture conditions. Although some newer corn hybrids have a higher drought tolerance, under extremely dry conditions, corn will more likely produce limited to no yield as compared to sorghum. Under these extremely dry conditions corn, may provide a more favorable crop insurance payout (no yield and no harvest expenses, and collect the insurance payment), whereas medium to no sorghum yields may still have to be harvested (incurring the expense of harvest with a lower crop insurance payment).

The average grain sorghum productivity for recent years (2000–2022), 4.3 Mg ha⁻¹, which we reported here, is well below the average corn yield of about 8 Mg ha⁻¹ for the same period [32]. An up-to-date comprehensive comparative analysis of sorghum and corn may be necessary to understand the reason behind this difference. However, one of the possible reasons for the large difference in the average yield between the two crops is the fact that sorghum is grown mostly in marginal dryland fields without irrigation, but corn is mainly irrigated and grown in environments with optimum inputs [33]. The average irrigated sorghum yield in recent years of about 6 Mg ha⁻¹ is significantly different from the overall average (of both dryland and irrigated production), which is achieved with little or no effort in selecting sorghum for resource-rich environments. A higher rate of change for non-irrigated yields (33 to 76 kg ha⁻¹ yr⁻¹) compared with rate of change for irrigated sorghum yields (1 to 52 kg ha⁻¹ yr⁻¹) across west and central Kansas sites for the years 1955 to 2022 is also the result of little or no effort being required in selecting sorghum for resource-rich environments. Even though sorghum is a relatively drought-tolerant crop, drought still negatively affects sorghum development and yield [34,35]. There are many potential research opportunities for increasing heat and drought tolerance in sorghum in Kansas and around the world [35,36]. Therefore, in addition to the effort required in selecting sorghum varieties and the management of drought and heat tolerance, resources should also be allocated to advanced sorghum technologies in resource-rich environments to give producers an alternative summer crop without a significant yield loss per area. If this were accomplished, grain sorghum may compete more readily with corn across the spectrum of both resource-rich and resource-limited environmental conditions which are likely to occur in Kansas and other cropping regions.

The increasing year-to-year variation in the yield of sorghum in recent years is the other important finding in this research. One main reason for increasing the year-to-year yield variation could be the increase in yield potential from technological advances over the years; i.e., higher average yields may be at risk of large yield losses under adverse conditions. However, much of the significant yield increase occurred in the years between 1960 and the 1980s, but the year-to-year variability was greater in the recent years after 1980s, perhaps related to significant changes in weather variables reported in certain months. A similar increase in yield variability in recent years was reported for Kansas corn and wheat [31,32] as well. In line with our finding, Kukal and Irmak [37] reported that a quarter of the yield variability in the Great Plains is explained by climate variability, i.e., changes in annual temperature or precipitation, singularly or in combination. Despite the impact of climate variability on sorghum, it is relatively less sensitive and among the best options in vulnerable environments [17]. The significant positive July–August precipitation but negative correlation between these month temperatures for sorghum yield, as our analysis found, indicates the importance of availability of water and a relatively cooler temperature from the start to a significant portion of the reproductive growth of sorghum. However, we did not find a consistent change in precipitation or temperature in these two months (July and August) over the past seven decades, but we reported changes and variabilities in other months, and the results are dependent on the location. The most northwest location in Kansas, where a warm fall period extended the growing season and favored yield, preventing early frost damage. The driest locations were most responsive to in-season precipitation. Across all locations in western Kansas, grain sorghum yields were more stable compared to corn, and it is a good crop choice in semi-arid moisture limited environments.

5. Conclusions

The main objective of this study was to quantify grain sorghum production, economic value, productivity, annual production variation, yield relation with changing weather patterns, and yield gap and to identify future areas of intervention and research. The results of this study indicate that the grain sorghum area in Kansas has increased in recent years (2010–2022), gaining an average of 8 thousand ha year⁻¹. With the current 1.2 million ha harvest area, Kansas continues to allocate more land area for sorghum than any other state. The current average annual economic value of sorghum to the state of Kansas is just above USD 0.5 billion dollars. The average grain sorghum yield in recent years (2000–2022) was 4.3 Mg ha⁻¹ in Kansas. The year-to-year yield variation for grain sorghum in the years 1929–1956 was ±0.5 Mg ha⁻¹ but increased to ±2 Mg ha⁻¹ for the years 1957–2022 based on an analysis of USDA Kansas data. A 66 to 96% yield gap was identified between the actual yield (USDA data) and the potential non-irrigated yield (KGSHP). This yield gap is in part due to timely planting and optimum management of research plots that are difficult for producers to replicate when farming a large area. There was a significant positive correlation between July and August precipitation but a negative correlation between these month temperatures for sorghum yield. Of these two, precipitation had a larger impact on yield than temperature. We detected a trend of an increasing sorghum harvest area in Kansas for the years 2010 to 2022, which is driven by economics but also likely due to sorghum performing well under moisture-limited conditions relative to corn. Sorghum and corn are the primary summer crops grown in Kansas, yet some other minor crops include sunflower (Heliathus annuus L.), pearl millet (Pennisetum glaucum L. R. Br.), and cotton (Gossypium hirsutum L.). The advantages of sorghum are export demand, prices (particularly during times of strong exports), drought and heat tolerance under challenging low-resource growing conditions, and lower input costs relative to alternative crop choices such as corn. These advantages need to be explored further to better define the opportunities to grow sorghum in crop rotation. Furthermore, research on increasing the sorghum yield potential is needed for sorghum to be competitive with these alternative crops under higher-yielding environments.

Author Contributions

Conceptualization, J.D.H. and A.K.O.; methodology, Y.A.; formal analysis, Y.A.; investigation, J.D.H., A.K.O., D.O. and P.V.V.P.; data curation, J.D.H. and Y.A.; writing—original draft preparation, Y.A.; writing—review and editing, Y.A., J.D.H., A.K.O., D.O. and P.V.V.P.; visualization, Y.A.; supervision, J.D.H., A.K.O., D.O. and P.V.V.P.; project administration, J.D.H., A.K.O., D.O. and P.V.V.P.; funding acquisition, J.D.H., A.K.O. and P.V.V.P. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported in part by the Kansas Experiment Station and the United States Agency for International Development (USAID) Bureau for Food Security as part of Feed the Future Sustainable Intensification Innovation Laboratory (SIIL), Award # AID-OAA-L-14-00006. This is contribution 24-196-J of the Kansas Agricultural Experimental Station.

Data Availability Statement

Data can be made available from authors upon reasonable request.

Conflicts of Interest

The authors declare no conflicts of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.

References

George, T.T.; Obilana, A.O.; Oyenihi, A.B.; Obilana, A.B.; Akamo, D.O.; Awika, J.M. Trends and progress in sorghum research over two decades, and implications to global food security. S. Afr. J. Bot. 2022, 151, 960–969. [Google Scholar] [CrossRef]
FAO. Agricultural Production Statistics. 2023. Available online: https://openknowledge.fao.org (accessed on 10 January 2024).
USDA-FAS. Sorghum 2023 World Production. 2023. Available online: https://ipad.fas.usda.gov/cropexplorer/cropview/commodityView.aspx?cropid=0459200 (accessed on 5 February 2024).
Erenstein, O.; Jaleta, M.; Sonder, K.; Mottaleb, K.; Prasanna, B.M. Global maize production, consumption and trade: Trends and R&D implications. Food Secur. 2022, 14, 1295–1319. [Google Scholar]
Khalifa, M.; Eltahir, E.A. Assessment of global sorghum production, tolerance, and climate risk. Front. Sustain. Food Syst. 2023, 7, 1184373. [Google Scholar] [CrossRef]
Mundia, C.W.; Secchi, S.; Akamani, K.; Wang, G. A regional comparison of factors affecting global sorghum production: The case of North America, Asia and Africa’s Sahel. Sustainability 2019, 11, 2135. [Google Scholar] [CrossRef]
Dalton, T.J.; Hodjo, M. Trends in global production, consumption, and utilization of Sorghum. In Sorghum in the 21st Century: Food–Fodder–Feed–Fuel for a Rapidly Changing World; Springer: Singapore, 2020; pp. 3–15. [Google Scholar] [CrossRef]
Mayor, L.; Demarco, P.; Lira, S.; Fang, Y.; Abadie, T.; Gambin, B.L.; Hammer, G.; Ciampitti, I.; Cooper, M.; Messina, C. Retrospective study in US commercial sorghum breeding: I. Genetic gain in relation to relative maturity. Crop Sci. 2023, 63, 501–510. [Google Scholar] [CrossRef]
USDA-NASS. Crop Production 2022 Summary. 2022. Available online: https://www.nass.usda.gov/Quick_Stats/index.php (accessed on 15 January 2024).
Eghball, B.; Power, J.F. Fractal description of temporal yield variability of 10 crops in the United States. Agron. J. 1995, 87, 152–156. [Google Scholar] [CrossRef]
Unger, P.W.; Baumhardt, R.L. Factors related to dryland grain sorghum yield increases, 1939 through 1997. Agron. J. 1999, 91, 870–875. [Google Scholar] [CrossRef]
Demarco, P.A.; Mayor, L.; Rotundo, J.L.; Prasad, P.V.V.; Morris, G.P.; Fernandez, J.A.; Tamagno, S.; Hammer, G.; Messina, C.D.; Ciampitti, I.A. Retrospective study in US commercial sorghum breeding: II. Physiological changes associated to yield gain. Crop Sci. 2023, 63, 867–878. [Google Scholar] [CrossRef]
Assefa, Y.; Staggenborg, S.A. Grain sorghum yield with hybrid advancement and changes in agronomic practices from 1957 through 2008. Agron. J. 2010, 102, 703–706. [Google Scholar] [CrossRef]
Rakshit, S.; Hariprasanna, K.; Gomashe, S.; Ganapathy, K.N.; Das, I.K.; Ramana, O.V.; Dhandapani, A.; Patil, J.V. Changes in area, yield gains, and yield stability of sorghum in major sorghum-producing countries, 1970 to 2009. Crop Sci. 2014, 54, 1571–1584. [Google Scholar] [CrossRef]
Laingen, C. A spatiotemporal analysis of sorghum in the United States. Pap. Appl. Geogr. 2015, 1, 307–311. [Google Scholar] [CrossRef]
Chadalavada, K.; Kumari, B.R.; Kumar, T.S. Sorghum mitigates climate variability and change on crop yield and quality. Planta 2021, 253, 113. [Google Scholar] [CrossRef] [PubMed]
Hossain, M.S.; Islam, M.N.; Rahman, M.M.; Mostofa, M.G.; Khan, M.A.R. Sorghum: A prospective crop for climatic vulnerability, food and nutritional security. J. Agric. Food Res. 2022, 8, 100300. [Google Scholar] [CrossRef]
Habyarimana, E.; Gorthy, S.; Baloch, F.S.; Ercisli, S.; Chung, G. Whole-genome resequencing of Sorghum bicolor and S. bicolor× S. halepense lines provides new insights for improving plant agroecological characteristics. Sci. Rep. 2022, 12, 5556. [Google Scholar] [CrossRef]
Economic Research. Table 1.1.4. Price Indexes for Gross Domestic Product. 2023. Available online: https://fred.stlouisfed.org/release/tables?eid=12970&rid=53Initiative (accessed on 4 February 2024).
Kansas State University. Grain Sorghum Crop Performance Test; Agricultural Experiment Station and Cooperative Extension Service. Report of Progress. Kansas State University: Manhattan, KS, USA, 2022. Available online: https://www.agronomy.k-state.edu/outreach-and-services/crop-performance-tests/grain-sorghum/ (accessed on 3 February 2024).
Kansas State University. Weather Data Library. K-State Research and Extension. 2023. Available online: https://www.ksre.k-state.edu/wdl/ (accessed on 20 February 2024).
SAS Institute. SAS/STAT User’s Guide, (Version 9.4); SAS Institute: Cary, NC, USA, 2012. [Google Scholar]
Brauer, D.; Baumhardt, R.L. Future Prospects for Sorghum as a Water-Saving Crop. Sorghum State Art Future Perspetives 2019, 58, 375–397. [Google Scholar]
USDA-RAM. Double Cropping Initiative. 2023. Available online: https://www.rma.usda.gov/en/Topics/Double-Cropping-Initiative (accessed on 26 January 2024).
Getachew, G.; Putnam, D.H.; De Ben, C.M.; De Peters, E.J. Potential of sorghum as an alternative to corn forage. Am. J. Plant Sci. 2016, 7, 1106–1121. [Google Scholar] [CrossRef]
O’Brien, D. Domestic and international sorghum marketing. Sorghum State Art Future Perspetives 2019, 58, 477–502. [Google Scholar]
Macke, Y. Foreign Demand Fuels U.S. Corn and Sorghum Exports. USDA, International Agricultural Trade Report. 2021. Available online: https://fas.usda.gov/data/foreign-demand-fuels-us-corn-and-sorghum-exports (accessed on 29 January 2024).
National Sorghum Producers. Sorghum 101. 2024. Available online: http://sorghumgrowers.com/sorghum-101/ (accessed on 29 January 2024).
Hariprasanna, K.; Rakshit, S. Economic importance of sorghum. In The Sorghum Genome; Springer: Singapore, 2016; pp. 1–25. [Google Scholar]
Frankowski, J.; Przybylska-Balcerek, A.; Stuper-Szablewska, K. Concentration of Pro-Health Compound of Sorghum Grain-Based Foods. Foods 2022, 11, 216. [Google Scholar] [CrossRef]
Holman, J.D.; Obour, A.K.; O’Brien, D.; Assefa, Y. Historic Winter Wheat Yield, Production, and Economic Value Trends in Kansas, the “Wheat State”. Crop Sci. 2024, 64, 925–941. [Google Scholar] [CrossRef]
Holman, J.D.; Obour, A.K.; O’Brien, D.; Assefa, Y. Historic Corn Yield, Production, and Economic Value Trends in Kansas. Agron. J. 2024, 116, 1428–1439. [Google Scholar] [CrossRef]
Staggenborg, S.A.; Dhuyvetter, K.C.; Gordon, W.B. Grain sorghum and corn comparisons: Yield, economic, and environmental responses. Agron. J. 2008, 100, 1600–1604. [Google Scholar] [CrossRef]
Craufurd, P.Q.; Peacock, J.M. Effect of Heat and Drought Stress on Sorghum (Sorghum bicolor). II. Grain Yield. Exp. Agric. 1993, 29, 77–86. [Google Scholar]
Djanaguiraman, M.; Perumal, R.; Jagadish, S.V.K.; Ciampitti, I.A.; Welti, R.; Prasad, P.V.V. Sensitivity of sorghum pollen and pistil to high-temperature stress. Plant Cell Environ. 2018, 41, 1065–1082. [Google Scholar] [CrossRef] [PubMed]
Rodriguez, D.; Serafin, L.; de Voil, P.; Mumford, M.; Zhao, D.; Aisthorpe, D.; Auer, J.; Broad, I.; Eyre, J.; Hellyer, M. Agronomic adaptations to heat stress: Sowing summer crops earlier. Field Crops Res. 2024, 318, 109592. [Google Scholar] [CrossRef]
Kukal, M.S.; Irmak, S. Climate-driven crop yield and yield variability and climate change impacts on the US Great Plains agricultural production. Sci. Rep. 2018, 8, 3450. [Google Scholar] [CrossRef]

Figure 4. Grain sorghum average, irrigated, and non-irrigated yield ha⁻¹ from (a) 1929 to 2022, (b) 1929 to 1979, and (c) 1980 to 2022 in Kansas. Throughout this paper, trend line equations with NS are not significant, with * being significant at p < 0.05, ** significant at p < 0.01, and *** significant at p< 0.001 probability level.

Figure 5. Grain sorghum yield trend (top panel (a–c)) and yield distribution (lower panel (d–f)) for average (left panel (a,d)), irrigated (central panel (b,e)), and non-irrigated (right panel (c,f)) yield ha⁻¹ from 1929 to 2022 at nine agricultural districts of Kansas.

Figure 6. Average grain sorghum yield trend for non-irrigated (left panel (a,c)) and irrigated (right panel (b,d)) yield ha⁻¹ from 1955 to 2022 (top panel (a,b)) and 2000 to 2022 (lower panel (c,d)) at Colby, Garden City, Hays, and Tribune Kansas Hybrid Sorghum Trials data. Trend line equations with NS are not significant, with * being significant at p < 0.05, ** significant at p < 0.01, and *** significant at p < 0.001 probability level.

Figure 7. Annual yield variability and trend in (a) USDA state average, (b) KGSHT non-irrigated, and (c) irrigated grain sorghum detrended yield using differencing data from USDA and trials at Colby, Garden City, Hays and Tribune, KS. Blue cone-shaped lines indicate how lower and upper margins of yield difference change over time despite an overall trendless variation. Throughout this paper, trend line equations with NS are not significant, with * being significant at p < 0.05, ** significant at p < 0.01, and *** significant at p < 0.001 probability level.

Figure 8. Yield gap analysis through relationship between actual (a) non-irrigated and (b) irrigated yield from Thomas, Finney, Ellis, and Greeley County USDA data and potential yield from variety trials at Colby, Garden City, Hays, and Tribune cities. Throughout this paper, trend line equations with NS are not significant, with * being significant at p < 0.05, ** significant at p < 0.01, and *** significant at p < 0.001 probability level.

Table 1. Correlation between non-irrigated grain sorghum yield and growing season precipitation and temperature from 1955 to 2022 across locations.

Location		April	May	Jun	Jul	Aug	Sep	Oct
	Growing season precipitation
Colby	r	0.13	0.23	−0.21	0.37	0.04	−0.07	0.04
Colby	p	0.327	0.0812	0.1043	0.0036	0.7902	0.6003	0.7813
Garden City	r	0.09	0.19	0.00	0.33	0.39	0.03	0.08
Garden City	p	0.5038	0.1478	0.9728	0.01	0.002	0.8495	0.526
Hays	r	0.05	0.14	−0.02	0.40	0.28	−0.23	−0.06
Hays	p	0.7122	0.3121	0.9079	0.0017	0.0357	0.0791	0.6684
Tribune	r	0.08	0.04	−0.14	0.15	0.16	−0.02	0.27
Tribune	p	0.5917	0.7861	0.3407	0.2936	0.266	0.8892	0.0597
	Growing season temperature
Colby	r	−0.07	0.00	0.17	−0.18	−0.15	0.08	−0.02
Colby	p	0.5983	0.9704	0.1934	0.1623	0.2582	0.5392	0.8802
Garden City	r	0.00	−0.09	0.07	−0.13	−0.14	0.12	0.06
Garden City	p	0.9787	0.4966	0.57	0.3406	0.2706	0.3486	0.6262
Hays	r	−0.22	0.00	−0.06	−0.31	−0.32	0.18	−0.05
Hays	p	0.093	0.9994	0.6539	0.0171	0.0131	0.187	0.6928
Tribune	r	−0.05	−0.23	0.26	0.27	0.05	0.34	−0.10
Tribune	p	0.7249	0.1031	0.0689	0.0598	0.7369	0.0172	0.49

Table 2. Correlation between irrigated grain sorghum yield and growing season precipitation and temperature from 1955 to 2022 across locations.

Location		April	May	Jun	Jul	Aug	Sep	Oct
	Growing season precipitation
Colby	r	0.23	0.02	−0.28	−0.22	−0.28	0.04	−0.13
Colby	p	0.1085	0.8945	0.0499	0.123	0.0512	0.7898	0.3637
Garden City	r	0.02	−0.19	−0.06	0.16	0.12	0.12	0.16
Garden City	p	0.8639	0.1541	0.6293	0.2179	0.371	0.3596	0.2276
Tribune	r	0.14	−0.11	−0.16	0.12	−0.07	0.03	0.06
Tribune	p	0.3006	0.4076	0.2449	0.3663	0.6213	0.809	0.6762
	Growing season temperature
Colby	r	0.06	0.10	0.36	−0.05	0.19	0.28	0.11
Colby	p	0.6956	0.4812	0.0111	0.7386	0.1862	0.0485	0.4355
Garden City	r	0.19	0.11	0.20	−0.04	−0.19	−0.09	−0.14
Garden City	p	0.159	0.419	0.1208	0.7416	0.1533	0.4889	0.2761
Tribune	r	−0.18	−0.28	−0.29	−0.09	0.33	0.42	0.25
Tribune	p	0.1733	0.0351	0.0296	0.5145	0.0134	0.001	0.0653

Table 3. Correlation between years (from 1955 to 2022) with grain sorghum growing season precipitation and temperature to detect a linear trend in weather variables over time. Correlation coefficient (r) and p-value (p).

Location		April	May	Jun	Jul	Aug	Sep	Oct
	Growing season precipitation
Colby	r	0.19	0.08	−0.29	−0.01	0.16	−0.14	0.11
Colby	p	0.1162	0.5395	0.0173	0.9161	0.1846	0.244	0.3658
Garden City	r	0.11	−0.13	−0.08	0.00	0.06	0.00	0.08
Garden City	p	0.3613	0.3034	0.5042	0.9882	0.6058	0.975	0.5145
Hays	r	0.09	0.12	−0.24	−0.01	0.21	−0.20	0.09
Hays	p	0.4928	0.324	0.0541	0.9207	0.0816	0.1012	0.4867
Tribune	r	0.15	−0.02	−0.03	0.12	0.15	−0.11	0.27
Tribune	p	0.2362	0.8742	0.8013	0.3377	0.2287	0.3817	0.0296
	Growing season temperature
Colby	r	0.05	−0.02	0.32	0.07	−0.06	0.29	−0.14
Colby	p	0.6907	0.902	0.0077	0.57	0.6231	0.0178	0.268
Garden City	r	−0.29	−0.32	−0.18	−0.23	0.03	0.41	0.30
Garden City	p	0.0164	0.0073	0.1562	0.0629	0.7965	0.0006	0.0136
Hays	r	0.05	0.00	0.34	0.15	−0.02	0.33	−0.13
Hays	p	0.6714	0.9942	0.0056	0.2405	0.8776	0.0062	0.2987
Tribune	r	−0.12	−0.19	0.17	0.01	−0.10	0.20	−0.28
Tribune	p	0.3315	0.1165	0.1648	0.9647	0.4313	0.1111	0.0214

Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

© 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).

Share and Cite

MDPI and ACS Style

Assefa, Y.; Holman, J.D.; Obour, A.K.; O’Brien, D.; Prasad, P.V.V. Historic Grain Sorghum Production, Value, Yield Gap, and Weather Relation Trends. Agronomy 2024, 14, 2582. https://doi.org/10.3390/agronomy14112582

AMA Style

Assefa Y, Holman JD, Obour AK, O’Brien D, Prasad PVV. Historic Grain Sorghum Production, Value, Yield Gap, and Weather Relation Trends. Agronomy. 2024; 14(11):2582. https://doi.org/10.3390/agronomy14112582

Chicago/Turabian Style

Assefa, Yared, Johnathan D. Holman, Augustine K. Obour, Daniel O’Brien, and P. V. V. Prasad. 2024. "Historic Grain Sorghum Production, Value, Yield Gap, and Weather Relation Trends" Agronomy 14, no. 11: 2582. https://doi.org/10.3390/agronomy14112582

APA Style

Assefa, Y., Holman, J. D., Obour, A. K., O’Brien, D., & Prasad, P. V. V. (2024). Historic Grain Sorghum Production, Value, Yield Gap, and Weather Relation Trends. Agronomy, 14(11), 2582. https://doi.org/10.3390/agronomy14112582

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Menu