Leaf senescence regulates grain yield. However, the modulation of leaf senescence in sorghum under legume-based intercrop systems and nitrogen (N) fertilization is not known. The objective of the study was to investigate the effect of intercropping two sorghum (Gadam and Serena) and cowpea (K80, M66) varieties and sole cropping systems and different fertilizer N rates (0, 40, and 80 kg·N·ha⁻¹) on the time course of postflowering sorghum leaf senescence and understand how senescence modulates grain yield. The experiment was laid out in a randomized complete block design with a split-plot arrangement with three replications. Leaf senescence was assessed from flowering to maturity at (a) whole-plant level by the visual scoring of green leaves and (b) flag leaf scale by measuring leaf greenness with a SPAD 502 chlorophyll meter. A logistic function in SigmaPlot was fitted to estimate four traits of leaf senescence, including minimum and maximum SPAD (SPADmin, SPADmax), time to loss of 50% SPADmax (EC50), and the rate of senescence. Irrespective of the cowpea variety, intercropping reduced sorghum grain yield by 50%. The addition of N increased yield by 27% but no effect was detected between 40 and 80 kg·N ha⁻¹. Intercropping delayed leaf senescence at the whole plant by 0.2 leaves plant⁻¹ day⁻¹ but reduced SPADmax of the flag by 8 SPAD units and rate of senescence by 4 SPAD units day⁻¹ compared with sole crop system. Fertilizer N delayed leaf senescence () at whole-plant and flag leaf scales. Cropping System × nitrogen modulated senescence at whole-plant and flag leaf scales and sorghum grain yield but marginally influenced other traits. While EC50 did not correlate with grain yield, faster rates of senescence and leaf greenness were associated with high yield under the sole crop system. Overall, N was the main factor in driving sorghum leaf senescence while the intercropping effect on senescence was nonfunctional. Effects of competition in sorghum-legume intercropping and source-sink relationships on the patterns of leaf senescence deserve further investigation. 1. Introduction Intercropping and best management practices of fertilizer nitrogen can increase crop yield in dryland environments [1, 2]. However, previous studies on intercropping and nitrogen use only emphasized crop growth and yield with limited information on leaf senescence. Senescence is closely associated with the photosynthetic capacity and chlorophyll content of the leaf, and it increases toward crop maturity due to declining trends of photosynthesis and chlorophyll contents of the leaf after flowering [3]. In cereal crops, leaf senescence patterns profoundly impact grain yield and quality by regulating source-sink relationships for nutrient demand [3, 4]. Five traits are used to describe the leaf senescence patterns, and they include the maximum and minimum leaf greenness, the start of senescence, time to loss of 50% of peak leaf greenness, and the rate of senescence [5, 6]. Prolonged leaf greenness has been correlated with higher grain yield in sorghum (Sorghum bicolor (L.) Moench) [5, 7], wheat (Triticum L.) [8], and maize (Zea mays L.) [6]. In addition, a delayed but rapid rate of leaf senescence has been shown to increase wheat grain mass [9]. Manipulation of these traits of senescence could potentially increase grain yield of sorghum in drylands, where both rainfall amount and frequency decline as crops mature [10]. Cereal-legume intercropping is a sustainable agricultural practice of simultaneously growing at least two crops on the same land [2]. The principle objective of intercropping is to increase crop productivity from a unit area where available growth resources are efficiently utilized [11]. In comparison with sole crop systems, intercropping improves crop diversification, increases crop yield and stability, especially under low-input conditions, and improves soil fertility and conservation, as well as weed control [12–14]. Further, intercropping and other practices such as mulching have been reported to regulate senescence through increased net photosynthetic duration and prolonged leaf greenness in proso millet [3, 15]. In spite of the wide adoption of intercropping in tropical environments, the practice has some limitations. For instance, an earlier study established that sorghum and cowpea grain yield grown in sole exceeded yields of counterparts in an intercrop system [16]. Additionally, a study on sorghum-cowpea intercropping reported that sole sorghum exceeded 31% of the intercropped sorghum yield [2]. This is because of interspecific competition for resources like soil nutrients, sunlight, and water in the intercropped sorghum [1]. Further, cereals like sorghum are nutrient-exhaustive crops, and the legume may not meet all the N requirement of cereal without external fertilizer N supply [16]. However, while the influence of intercropping on sorghum growth and yield has been reported in previous studies, intercropping influence on senescence traits in cereal like sorghum has not been widely understood; hence, establishing intercropping effect on sorghum leaf senescence could help correlate with grain yield. Nitrogen regulates the patterns of senescence in many crops, including sorghum [17]. This is attributed to source-sink relations which impacts N remobilization from senescing leaves to the reproductive structures, thus, impacting leaf senescence [4]. Under moisture stress conditions, prolongation of leaf greenness has been demonstrated to improve grain yield, stem mass, and lodging resistance [5]. In cereals like maize, the maximum leaf greenness before flowering has been correlated with grain yield and yield traits under normal conditions [6]; however, evidence of how nitrogen fertilizer influence leaf senescence in sorghum under intercrop system remains limited. The flag leaf in cereal plays a pivotal function in the provision of photosynthates during grain filling in cereal [18–20]. A decline in the photosynthetic rate of the flag leaf has been reported which leads to a significant yield decrease in monocarpic crops such as rice [20], wheat [21], and barley [22], irrespective of the environment, normal or dryland environment [23]. However, there exists limited evidence on the impact of N on the pattern of sorghum leaf senescence at flag leaf and whole-plant scale and its association with grain yield. Intercropping and nitrogen addition have been shown to regulate the patterns of leaf senescence in many crops, for example, in proso millet [3, 15], Maize [5, 6, 24], sorghum [5], and wheat [7], but the responsible mechanisms are only partially understood. Therefore, understanding physiological processes such as senescence and their association with grain yield would help in the sorghum yield improvement process. Thus, the objective of the study was to investigate the time course of postflowering leaf senescence of sorghum under intercrop and sole cropping systems and different fertilizer N rates and understand how senescence modulates grain yield. This study hypothesized that intercropping sorghum with cowpea and higher fertilizer N rates could delay leaf senescence and increase the grain yield of sorghum. 2. Materials and Methods 2.1. Sites Description Two field experiments were simultaneously conducted under rainfed conditions at the Kenya Agricultural and Livestock Research Organization (KALRO) stations in Katumani and Igoji during the 2018/2019 short rains. Katumani is located 01° 35′S, 37° 14′E and 1575 meters above sea level (masl) while Igoji 0°11′13″ S, 37°40′10″ E and 1770 masl [25]. Katumani is in upper mid-land zone four (UM4) with a mean annual temperature of 19°C [25]. The mean annual rainfall in this site is 655 mm. Soils of Katumani are ferral chromic luvisols [26]. Igoji is in upper mid-land zone two (UM2) and has a mean annual temperature of 20°C [25]. The mean annual rainfall is 1580 mm, and the soils of Igoji are deep well-drained volcanic soil [25]. Rainfall distribution in both sites occurs in two seasons where long rains fall between March and July while short rains are received between October and December [10]. In Katumani, the short rains season is drier (288 mm) compared with Igoji which receives 370 mm. Daily minimum and maximum rainfall and temperature data from the onset of the flowering of sorghum to physiological maturity were collected from weather stations in both sites. Monthly means were computed for both parameters. Prior to sowing the crops, soils were sampled at 0–30 cm depth and analyzed. A Mehlich double acid method was used to analyze the soils for P, K, Na, Ca, Mg, Mn, Fe, Zn, and Cu. The total organic carbon (C) % was analyzed using the colorimetric method while the total nitrogen (N) % was determined using the Kjeldahl method [27]. A digital pH meter (Oakton Instruments (888-462-5866) https://www.4oakton.com/) was used to measure the soil pH in a ratio of 1 : 1 soil-water suspension (w/v) [27]. The ammonium acetate method was used to analyze cation exchange capacity (CEC) [27]. 2.2. Treatments and Experiment Design In both sites, the effects of cropping system (intercrop and sole) with two varieties of sorghum and cowpea and three rates of fertilizer nitrogen (0, 40, and 80 kg·N·ha⁻¹) were evaluated. In the intercrop system, a row of cowpea was sown between two rows of sorghum. Locally adapted Gadam and Serena sorghum varieties were used as test crops while cowpea varieties comprised Machakos 66 (M66) and Katumani 80 (K80). The yield potential of Gadam and Serena is 4.5 and 2.3 t·ha⁻¹, respectively, while that of M66 and K80 is 1.8 t·ha⁻¹ [28]. The seed for both crops was sourced from Katumani Seed Unit at the KALRO research station. Fertilizer N was supplied from urea (46% N) and applied to the sidebands on the planting rows of both sorghum and cowpea in fractions of a third (⅓) at sowing and two-thirds (⅔) top-dressed at tillering stage of sorghum growth. All treatment plots received 60 kg·P·ha⁻¹ of basal fertilizer in the form of triple superphosphate (0-45-0) that was applied to the sidebands on the planting rows of both crops. The field experiments were laid out in a randomized complete block design (RCBD) with a split-plot arrangement with three replications. Factorial combinations of sorghum-cowpea intercropping or sole crop formed the main plots while N rate formed the subplots. The main plots measured 24 m × 8 m and subplots were 12 m × 4 m. The main plots were separated by a 1 m path and the subplot by a 0.5 m path while treatment blocks were separated by a 2 m path. Primary tillage was done a week prior to the onset of the rains followed by secondary tillage during the 2018/2019 short rains season in both experimental sites. The planting was manually done by placing seeds in holes of 5 cm deep opened using a machete. Crops were planted at the onset of rains at 10 kg·ha⁻¹ seed rate for both sorghum and cowpea. In the sole crop system, sorghum was sown 75 cm between rows and 20 cm within plants while cowpea was sown 60 cm between rows and 30 cm within plants. In the intercrop component, sorghum was sown 90 cm between rows and a row of cowpea between two rows of sorghum with a spacing of 20 cm from plant to plant. In both crops, three seeds were planted in each hole and later thinned to one plant per hole to achieve a sorghum density of 6.7 plants·m⁻² in the sole crop system and 5.6 plants·m⁻² in the intercrop system. Cowpea plant density was 5.6 plants m⁻² in the sole crop system and 3.7 plants m⁻² in an intercrop system. Preemergence weed control was done using Roundup® (glyphosate) immediately after sowing. Experiments were kept weed-free through hand weeding. Insect pests, mainly thrips and aphids in cowpea and stem borers in sorghum, were controlled with Thunder® (Imidacloprid 100 g/L + Betacyfluthrin 45 g/L) at 120 mL acre⁻¹. Sorghum was guarded against birds feeding on the grains at grain filling until harvesting. 2.3. Data Collection 2.3.1. Grain Yield and Yield Traits Sorghum panicles were harvested using a knife at maturity in a net plot area of 16 m² and air-dried. Prior to threshing, the sorghum panicle length and width of 10 air-dried panicles plot⁻¹ were measured using a tape measure in centimeters and the average value was determined. Further, the weight of the 10 panicles was weighed using a digital weighing scale, and the mean weight was computed in grams. The panicles were then threshed and cleaned, and a moisture meter was used to determine the grain moisture. The grain weight was then adjusted to 12.5% moisture content similar to Sibhatu and Belete [2]. Thousand sorghum seeds plot⁻¹ were counted using a seed counter and weighed in grams. 2.3.2. Measurement of Leaf Senescence A phenological scale was used to determine sorghum flowering as 50% shedding of pollen. Similar to Kitonyo et al. [6], assessment of senescence at whole-plant level was scored visually from a few days after flowering through to maturity by recording the number of green leaves plant⁻¹ (leaves that presented more than 50% green leaf area) using a predetermined interval of 10 days. The number of leaves which presented over 50% green leaf area was recorded at 10, 20, 30, 40, and 50 days after flowering for five plants, and the means were computed. The leaf senescence of the flag leaf of the tagged plants was measured using a SPAD 502 chlorophyll meter [6]. Chlorophyll content of sorghum flag leaf was measured with a predetermined interval of 10 days after flowering to physiological maturity. For each sorghum plant, three SPAD units were collected at different points of the flag leaf at the tip, middle, and bottom, and an average value was determined for each plant and for the whole plot. 2.3.3. Analysis of Leaf Senescence SPAD data from the measurement of the flag leaf senescence was subjected to a logistic regression function in SigmaPlot version 10.0 (Systat Software, Inc., San Jose California USA, https://www.systatsoftware.com) to fit the time course of leaf senescence from 10 days of sorghum flowering through to maturity. Similar to Christopher [5] and Kitonyo et al. [6], the function estimated four parameters of leaf senescence, including the peak leaf greenness (SPADmax), time to the loss of 50% of SPADmax (EC50), and minimum leaf greenness at maturity (SPADmin), while the slope of the curve gave the rate of leaf senescence (RS as SPAD units day⁻¹) (Equation 1). The logistic function was fitted for each plot and traits of leaf senescence were subjected to analysis of variance. 2.4. Data Analysis Data were subjected to analysis of variance by GenStat 14th Edition at a 5% probability level. All the measured variables’ residuals were normally distributed; hence, transformations were not required. Treatment means were compared and separated using the least significant difference (LSD) test at a probability level of 5% [29]. Relationships between the traits of leaf senescence and grain yield and yield traits were examined by correlation analysis. 3. Results 3.1. Postflowering Weather Conditions and Initial Soil Fertility 3.1.1. Weather Weather conditions from the onset of flowering until physiological maturity are shown in Table 1. Data was consistent with the long-term average for both sites, where rainfall tapers and temperatures increase as the crop matures. Despite long-term data showing that Katumani is drier than Igoji, the mean temperatures between the two sites were relatively similar. In addition, rainfall distribution between the two sites varied significantly where Igoji was drier than Katumani a few weeks after flowering to physiological maturity. Months Igoji Katumani Jan-19 Feb-19 Mar-19 Apr-19 Jan-19 Feb-19 Mar-19 Apr-19 Average temperature (°C) 35.0 39.0 155.0 398.0 16.8 3.8 8.4 3.0 Monthly rainfall (mm) 19.9 20.5 21.1 20.5 19.4 21.1 21.6 22.0
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