Planting Window Research Articles

Evaluating Chinese fiber hemp (Cannabis sativa L.) varieties and planting dates in North Carolina

AbstractField trials were conducted in 2021 and 2022 to evaluate the effects of planting date (mid‐March, mid‐April, and mid‐May) on 11 fiber hemp (Cannabis sativa L. <0.3% total tetrahydrocannabinol) varieties. Trials were conducted in Goldsboro, Kinston, and Salisbury, NC. Each location followed a split‐plot randomized complete block design with at least three blocks where planting date was the main‐plot and variety the sub‐plot. Varieties investigated originated from China and Australia (2021 only). Data collection included flowering time, end of season stand counts, stem height, diameter, and final retted dry straw yield. We found differences among the varieties investigated in both years; however, no distinct trend was observed across years. All varieties investigated flowered at the end of August and beginning of September, allowing for a long growing season and ability to produce abundant biomass. In general, the Chinese genetics yielded higher stem biomass compared to previously reported European genetics. Stem thickness was >7.5 mm, which is generally considered the maximum width for textile‐grade fiber production. To achieve thinner stems from the varieties investigated, harvesting prior to male‐flower initiation may be required. The crop experienced temperatures below freezing in both years with no signs of damage. Taken together, farmers seeking to plant fiber hemp in North Carolina have a wide planting window from mid‐March to mid‐May using these Chinese varieties.

Soybean response to high‐speed planting in Mississippi

AbstractMississippi soybean [Glycine max (L.) Mer.] producers are under pressure to plant as much land as possible within narrow planting windows. The 5‐year average planting progress is 45% of the total at the end of the optimal soybean planting window. New metering and seed delivery technology claims faster planting without sacrificing singulation, stand, or yield, but these tools need to be validated before recommendation. This study aimed to quantify soybean response to planting speeds using a precision planter (John Deere MaxEmerge 2 row units retrofitted with Ag Leader SureSpeed and SureForce) and a mechanical planter (John Deere 1700 ground‐driven mechanical planter equipped with eSet meters) for a total of 7 site‐years across Mississippi. In 2022, both planters were evaluated at four actual ground speeds of 7.9, 10.8, 13.5, and 16.4 km h−1 in a 2 × 4 factorial design. The experimental design was modified in 2023, where the mechanical planter served as the current farmer practice check at 9.7 km h−1and the precision planter speeds were 9.7, 14.5, and 17.7 km h−1 at research station sites and 9.7 and 14.5 km h−1 at an on‐farm site. Across sites, increased planting speed generally increased plant spacing, in‐row spacing variability, and decreased plant population. However, increased speed did not affect soybean yield. The precision planter at 17.7 km h−1 was no different from the mechanical planter in terms of soybean plant population, spacing, and yield in 2023. Results suggest soybean producers can plant soybean at 17.7 km h−1 without compromising yield.

A historical assessment of the number of days required to plant the Arkansas soybean crop

AbstractThe primary objective of this paper is to quantitatively analyze the number of acres planted per suitable fieldwork day and the total number of fieldwork days available for the complete planting of soybeans (Glycine max L.) in Arkansas. Total days to plant soybeans in each spring from 1980 to 2023 averaged about 33 days, indicating that roughly 33 days are expected, on average, from the month of April to May based on USDA‐NASS weekly crop progress and condition data. Furthermore, the average soybean planted acres is estimated at 106,736 acres per day within the study period. Recently, variations in this range appear more pronounced, likely due to the significant impact of extreme spring weather conditions. However, technological advancements have enabled soybean producers to plant crops as early as the first half of March or as late as June, contributing to the increased variability observed from year to year in recent times. Furthermore, Arkansas's optimal soybean planting window typically provides an average of 4.7 fieldwork days per week. These quantified estimates offer historical data on Arkansas's soybean planting performance and will prove highly valuable for informing future soybean planting strategies.

Exploring adaptation strategies for smallholder farmers in dryland farming systems and impact on pearl millet production under climate change in West Africa

Understanding and identifying appropriate adaptation optons for cropping systems and management practices at spatial and temporal scales is an important prerequisite for scaling. Pearl millet (Pennisetum glaucum (L) R. Br.) could be regarded as a risk-reducing measure crop under climate change when coupled with tactical agronomic management practices. In this study, we assess the impacts of adaptation strategies such as cultivar type, planting windows, and fertilizer strategies on pearl millet production under rainfed farming systems over Nigeria and Senegal using the Agricultural Production Systems Simulator (APSIM) model. The impact of climate change on millet yield was evaluated using a validated APSIM-millet module that utilized yield data collected through participatory research and extension approach (PREA) in contrasting environments. The climate model projections for the mid-century period (2040–2069) were compared against a baseline period of 1980–2009 for both locations. During the simulation, two millet varieties (improved local and dual-purpose) with two sowing regimes were considered comparing traditional farmers’ sowing window (dry sowing) and agronomic sowing window (planting based on the onset of the rainfall) at three different fertilizer levels [low (23 kg N ha−1), medium (40.5 kg N ha−1), and high (68.5 kg N ha−1) respectively]. The performance of the APSIM-millet module was found to be satisfactory as indicated by the low Root Means Square Error (RMSE) and Normalized Root Mean Square Error (NRMSE) values. The range for grain yield was between 17.7% and 25.8%, while for AGB it was between 18.6% and 21.4%. The results showed that farmers’ sowing window simulated slightly higher grain yield than the agronomic sowing window for improved local millet cultivar indicating yield increased by 8–12%. However, the projected changes in the mid-century (2040–2069) resulted in a decline in yield against baseline climate for both varieties and sowing windows, indicating the negative impact of climate change (CC) on yield productivity. The comparison between dual-purpose millet and improved local millet indicates that disseminating the improved millet variety and implementing early sowing could be an effective adaptation strategy in reducing risks and losses caused by climate change. Similarly, low magnitude impacts simulated on grain yield (< −8% in Nigeria compared to > −8% in Senegal) even though both locations are in the same agroecological zone.

Improving Decision Support Tools for Quantifying GHG Emissions from Organic Production Systems

AbstractAs food companies have adopted sustainability metrics to quantify the environmental impacts of supply chains, we need data-driven decision support tools that represent organic management practices. Decision support tools such as COMET-Farm and the Cool Farm Tool have been developed to estimate management practice impacts on soil carbon and greenhouse gas emissions from agricultural systems, but these tools have primarily been developed and used to evaluate conventional management systems. We provide an overview of the research, outreach, and educational activities used to improve these tools to better integrate organic management practices with a focus on cover crops. We summarize our previously published findings from a meta-analysis of the average potential soil carbon benefits of cover crops in temperate climates that identified planting window, biomass production, and soil texture as important predictors of cover crop soil carbon outcomes. We demonstrate how these findings were applied to improvements in process-based models and the parameterization of empirical models. In addition, we solicited feedback from organic community members on the utility of these tools and identified barriers to adoption. Finally, we evaluated both tools as resources for teaching undergraduate students about organic management systems and their impacts on greenhouse gas emissions. While both tools contain a range of customizable, organic amendment options, grazing management options still need further improvement. These improved decision support systems can help identify opportunities for enhancing the sustainability of organic systems.

Evaluation of spring-type and winter-type Brassica napus germplasm for genetic diversity in response to flea beetle herbivory in typical and atypical planting windows

Current practices of flea beetle ( Phyllotreta spp.) control in Brassica napus L. rely heavily on seed treatments and due to growing concerns regarding the safety of such treatments on non-target and beneficial insect populations, genetic resistance would be beneficial for a more balanced integrated pest management strategy. However, none of the registered B. napus. canola varieties exhibit measurable resistance to flea beetle injury. To this end, an evaluation of 14 winter-type B. napus breeding lines and 15 spring-type B. napus breeding lines for resistance to flea beetle feedings was conducted, as it was found that at least one line in each family exhibited noticeably reduced flea beetle damage compared to sister lines in a breeding nursery. The study revealed natural genetic variation within B. napus for flea beetle antixenosis which could be used by dedicated breeders to develop canola varieties with higher levels of flea beetle resistance. Data indicated that host plant resistance did not vary between feeding by newly emerged adult flea beetles in the fall and the overwintered adults in the spring in either winter-type or spring-type canola, as well as for adult feeding preferences. This indicates that favourable genes identified in in either habitat-type could be used interchangeably to confer resistance even though the flea beetle life cycle is different for each planting period, while either overwintered adults or newly emerged adults can be used to evaluate feeding damage.

Planting date and dicamba‐based herbicide programs influence soybean production in the Southern Great Plains

AbstractThe interplay of management decisions involving soybean (Glycine max L.) planting date, herbicide programs, and herbicide application timings is critical to optimize soybean performance and weed control in Southern Great Plains soybean production systems. This research sought to evaluate soybean yield potential and the level of weed control as influenced by early‐, delayed‐, and late‐ planting dates and various combinations of preemergence (PRE), early‐postemergence (EPOST), and mid‐postemergence (MPOST) weed management programs. A field study was established in Bixby, OK in 2017 and 2018 under irrigated conditions and in Perkins, OK in 2017 under dryland conditions, consisting of three planting windows (early, delayed, and late) of XtendFlex soybean, with or without a PRE (chlorimuron + flumioxazin + pyroxasulfone + glyphosate + dicamba) combined with EPOST or EPOST + MPOST (glyphosate + dicamba) versus no in‐season applications. The gap in late‐planted soybean yield potential, compared to early‐planted soybean, was exacerbated in the dryland systems (1346 kg ha−1) versus an irrigated system (2311 kg ha−1). Use of PRE provided 60% weed control until MPOST and increased yields by 657 kg ha−1 and 457 kg ha−1 for delayed and late‐planted soybean, respectively. Late‐planted soybean with EPOST + MPOST provided up to 50% weed control, but lack of biomass production for cultural control reduced weed control by 29% compared to early‐ and delayed‐planted soybean. From an agronomic management standpoint, the time of soybean planting is influential on the success of weed control measures and soybean yields in double‐cropping system in the Southern Great Plains, particularly with late‐planted soybean.

Onset of Rainfall and Cumulative Analysis for Sorghum Cultivation in Baringo County

Sorghum is an essential food security crop in the majority of the ASALs regions, such as Baringo County. This study investigated the critical relationship between rainfall levels and the initiation of sorghum planting, with the aim of identifying the threshold at which rainfall is considered sufficient for germination and optimal growth. This study used historical meteorological data from 1990 to 2022, field experiments, statistical analysis, and sorghum growth patterns to discern the trigger points for planting, which are essential for ensuring successful cultivation. This study uncovered alterations in rainfall onset and seasonal rainfall accumulation. The planting window in Baringo County varied significantly, with some dates falling above and below the average onset values of April 4<sup>th</sup> for the long rainfall season and September 24<sup>th</sup> for the short rainfall season. A short rainy season is not ideal for sorghum planting, as it typically receives less than 300 mm of rainfall, which is insufficient for sorghum production. The optimal planting time for sorghum is usually late March and early April. The study found that 36.4% of the long rainy season years had high production, 42.4% had normal production, and only 21% had low or no productivity. The years 2000 and 2018 experienced minimum and maximum rainfall amounts of 198.45 mm and 941.9 mm, respectively.

Analysis of Potential Cropping Seasons of Cayenne Pepper (Capsicum frustescens L.) Based on Water Balance in Alfisol Dryland, Tuban Regency, East Java, Indonesia

Dryland agriculture is crucial for understanding how to effectively manage land water for the crops. Water balance analysis plays a pivotal role in comprehending the hydrological cycle and water availability for crop production. The Tuban Regency is one of the fifth largest cayenne pepper-producing areas in East Java, Indonesia, particularly in Grabagan and Bancar Districts. However, for sustainable growth, it is imperative to extend cultivation to other sub-districts within Tuban Regency. In the cultivation of cayenne pepper, attention to soil water availability is important due to its susceptibility to drought, directly impacting vegetative growth and overall plant production. This research aims to establish a planting pattern for cayenne pepper based on water balance analysis in Alfisol drylands within Montong, Kerek, and Singgahan Districts of Tuban Regency. The study, conducted from July to September 2023, employed Thornthwaite and Mather water balance analysis,drought index assessment, and day without rain analysis. The research findings reveal variations inwater balance conditions within the study areas, with Montong and Kerek Districts experiencing a land water surplus for three months and a nine-month deficit. Singgahan District, on the other hand, encountered a surplus for four months and a deficit for eight months. The drought index indicates a high level, peaking in September for Montong (87%), Kerek (91%), and Singgahan (87%) Districts. Cayenne pepper plants exhibit the potential for annual cultivation in Alfisol drylands of Montong, Kerek, and Singgahan Districts, with a growing duration of six months. The optimal planting window spans from December to May, followed by potentially a second planting in June and July for crops with a minimum available water value exceeding 19% or those with a shorter harvest life. From August to November, the land lies fallow due to a soil water availability that is close to 0% and a 27% risk of days without rain in the extreme drought category, rendering the soil unsuitable for growing crops.

In‐field climatic factors driving Sclerotinia head rot progression across different sunflower planting dates

AbstractSclerotinia head rot, caused by Sclerotinia sclerotiorum, is a major disease limiting sunflower production in tropical and subtropical agroecological zones. Sporadic outbreaks across South Africa have resulted in major losses, yet little is known about the in‐field climatic factors driving this infection. Short‐interval, staggered plantings have been proposed as a control method for Sclerotinia head rot, which help to limit the number of plants in a susceptible developmental stage during conducive environmental conditions. However, this complicates field management practices, especially if working at the fringes of a planting window due to delayed rains. This study aimed to investigate the effect of planting date on Sclerotinia head rot progression in monthly plantings across the summer period. Artificial mycelial plug inoculations were performed at the R5.9 flowering stage in an open field. Disease establishment, progression and severity were monitored at 3‐day intervals for 30 days. We show that disease establishment was delayed by low relative humidity or extreme low temperatures in the January and March planting dates where the first lesions were only observed 6 days post‐inoculation. Consistently high temperatures above 27°C also suppressed disease progression and produced low area under the disease progress curve (AUDPC) scores of 75.15 and 29.4 for the October and November planting dates, respectively. These findings suggest that regardless of season or location, selecting a planting date that ensures the sunflower bloom period aligns with the hottest, driest part of the season will probably suppress Sclerotinia head rot in regions with average summer highs above 27°C.

Relationship between weather factors and planting dates with references to growth and yield of potato (Solanum tuberosum) varieties

A field experiment was conducted during the winter season of 2016–17 and 2017–18 at the research farm of the Department of Agricultural Meteorology, College of Agriculture, Chaudhary Charan Singh Haryana Agricultural University, Hisar, Haryana to quantify the effect of different planting dates on the growth and yield of potato (Solanum tuberosum L.) cultivars. The experiment comprised 12 treatment combinations involving 4 date of sowing, viz. D1 , 8 October; D2 , 22 October; D3 , 5 November and D4 , 15 November as main plot treatment and viz. 3 varieties V1 , ‘Kufri Bahar’, V2 , ‘Kufri Pushkar’ and V3 , ‘Kufri Surya’, as sub-plot treatment in a split-plot design, replicated 4 times. The maximum tuber yield was recorded in D2 (21.9 tonnes/ha) as compared to the other sowing dates and the lowest in D4 (16.5 tonnes/ha). Among the varieties, ‘Kufri Pushkar’ had a significantly higher tuber yield (23.2 tonnes/ha) than ‘Kufri Bahar’ (18.0 tonnes/ha) and ‘Kufri Surya’ (16.6 tonnes/ha) during the crop season. Plant height, dry matter accumulation and biological yield were positively correlated with wind speed, rainfall and rainy days. The number of leaves/plant and leaf-area index (LAI) was significantly, negatively correlated with maximum and minimum temperatures, whereas it showed significant positive correlations with wind speed. Evening relative humidity was also positively correlated with LAI and tuber yield of potatoes. However, improved cultivars along with ideal planting windows at micro-level identification were the best way to mitigate the challenges posed by the climate in potatoes in near future.

Adaptations of potato production to future climate change by optimizing planting date, irrigation and fertilizer in the Agro-Pastoral Ecotone of China

Future climate change, especially rising temperature and varying precipitation will have significant impacts on potato production. Revealing the optimum planting date, irrigation schedule and fertilizer amount under future climate scenarios is critical for promoting sustainable potato production in the Agro-Pastoral Ecotone (APE). In this study, two representative stations of Wuchuan (WC) and Zhangbei (ZB) in APE were selected, firstly, we used well validated APSIM-Potato model to optimize the planting date of potato in future climate scenarios. Then the impacts of different combination of N fertilizer and irrigation on potato yield, N loss, water use efficiency (WUE), nitrogen use efficiency (NUE) and economic income were analyzed under optimal planting date. The future climate projection was provided by 13 Global Climate Models (GCMs) from the Coupled Model Inter-comparison Project phase 6 (CMIP6) under two emission scenarios of future societal development pathway (SSP) 245 and SSP585. Compared with baseline period (1981–2010), the planting windows during 2040 s (2031–2060) and 2080 s (2071–2100) were wider, and the optimal planting dates (OPDs) for rainfed potato should be arranged later under SSP245, but it should be earlier under SSP585. However, the OPDs for irrigated potato should advance under SSP245 and SSP585. Then, we analyzed the coupling effects of irrigation and nitrogen fertilizer on potato production under OPDs in future climate scenarios. Irrigation was carried out based on the soil water deficit within 1 m depth (IR, ranged from 10 mm (IR10) to 100 mm (IR1) with the interval of 10 mm) and fertilizer was set with 8 treatments (N, ranged from 0 kg ha−1 (N0) to 210 kg ha−1 (N7) with the interval of 30 kg ha−1). To achieve highest yield, maximum amount of N (N7, 210 kg ha−1) coupled with IR10 (irrigation applied if soil water deficit beyond 10 mm) should be applied for both WC and ZB station. However, these combinations would accumulatively decrease groundwater table (GDT) by 70.8–76.5 m (39.1–44.8 m) and 78.7–80.2 m (38.6–47.4 m) during 2040 s and 2080 s, and induce annual N loss by 21.6–27.3 kg ha−1 (24.7–25.3 kg ha−1) and 17.7–21.9 kg ha−1 (18.3–21.2 kg ha−1) at WC (ZB), respectively. Net income of potato under different combinations of irrigation and N fertilizer ranged from −10700 to 25,500 Yuan ha−1 and from −4100 to 26,600 Yuan ha−1 at Wuchuan and Zhangbei. To maximize the income of farmers, N4 (120 kg ha−1) coupled with IR9 (irrigation applied if soil water deficit beyond 20 mm) should be applied at the two study sites. Our results would be helpful in developing adaptable strategies for potato production to cope with future climate change in the APE.

The influence of planting window on yield stability of maize genotypes in semi-arid areas

Maize is one of the most important field crops for feed, food, and raw material in South Africa. It is the main staple food for the majority of the people impoverished households in South Africa. Maize is susceptible to drought, and erratic rainfall and extreme climate variation are major maize production constraints in South Africa. This study aimed to determine the influence of planting dates on the grain yield stability of six maize genotypes in five environments for three (2019/20 to 2021/22) consecutive seasons. The additive main effect and multiplicative interaction (AMMI) model indicated that the environment contributed 59.20 % and 47.76 % of the total variation in grain yield at planting dates one (PD1) and two (PD2), respectively. The magnitudes of the genotype x environment interaction sum of squares were 5.20 for PD1 and 12.30 for PD2 times that of the genotype (genotype) sum of squares for the grain yield (GEI). The first principal component accounted for 53.14 % (PD1) and 47.76 % (PD2) of the total variation in the dataset. The AMMI genotype superiority measure (Pi), genotype and genotype by environment interaction (GGE), yield stability index, and AMMI stability value analyses identified genotypes DKC75–65BR and DKC78–45BRGEN as stable and high yielding across environments and planting dates. Genotype DKC71–44B was the least stable at both planting dates. Bothaville (E7) for PD1 and Coligny 2021/22(E13) for PD2 had high yield potential and were favorable environments, whereas Potchefstroom 2019/20 and 2021/22 were the least favorable environments for PD1 and PD2, respectively.

Response of Yield and Agronomic Output of Bangabandhu dhan100 under Varying Sowing Window in Cold Prone Rangpur Region

Background: Selection of a suitable planting time is one of the key factors for obtaining a desirable rice grain yield. This study focuses on the effect of planting date on the key agronomic traits and provides useful information on optimal planting window to maximize grain yield of Bangabandhu dhan100 in the cold-prone Rangpur region, Bangladesh. Methods: The study was conducted at the Rangpur regional station farm of the Bangladesh Rice Research Institute from October 2021 to June 2022. The selected cultivar was seeded on eight different dates at a 15-day interval, starting on October 16. Time series data on agronomic parameters including seedling biomass, leaf number of seedlings and tiller number per plant were collected at a 15-day interval. Result: A good relationship was found between accumulated GDD (growing degree days) and the associated leaf number per plant and the highest leaf number was observed with early seeding. Similarly, seedling biomass yield depended on accumulated GDD and it was found to be higher at early seeding than late seeding. The tillering pattern of Bangabandhu dhan100 was influenced by planting dates and reached its peak at 60 days after planting for all seeding dates. The highest tiller number (368/plants) was found when the cultivar was seeded on December 1. Total biomass showed an increasing trend after planting and reached its maximum of 13.9 t/ha with December 1 seeding. Planting time significantly influenced the grain yields and the highest yields were observed during seeding between 1 and 16 December; yields gradually decreased with the advancement of seeding dates. This finding provided a good idea for the selection of an optimal planting time for Bangabandhu dhan100 to maximize grain in the Rangpur region, Bangladesh.

Assessment and Application of EPIC in Simulating Upland Rice Productivity, Soil Water, and Nitrogen Dynamics under Different Nitrogen Applications and Planting Windows

A suitable nitrogen (N) application rate (NAR) and ideal planting period could improve upland rice productivity, enhance the soil water utilization, and reduce N losses. This study was conducted for the assessment and application of the EPIC model to simulate upland rice productivity, soil water, and N dynamics under different NARs and planting windows (PWs). The nitrogen treatments were 30 (N30), 60 (N60), and 90 (N90) kg N ha−1 with a control (no N applied −N0). Planting was performed as early (PW1), moderately delayed (PW2), and delayed (PW3) between September and December of each growing season. The NAR and PW impacted upland rice productivity and the EPIC model predicted grain yield, aboveground biomass, and harvest index for all NARs in all PWs with a normalized good–excellent root mean square error (RMSEn) of 7.4–9.4%, 9.9–12.2%, and 2.3–12.4% and d-index range of 0.90–0.98, 0.87–0.94, and 0.89–0.91 for the grain yield, aboveground biomass, and harvest index, respectively. For grain and total plant N uptake, RMSEn ranged fair to excellent with values ranging from 10.3 to 22.8% and from 6.9 to 28.1%, and a d-index of 0.87–0.97 and 0.73–0.99, respectively. Evapotranspiration was slightly underestimated for all NARs at all PWs in both seasons with excellent RMSEn ranging from 2.0 to 3.1% and a d-index ranging from 0.65 to 0.97. A comparison of N and water balance components indicated that PW was the major factor impacting N and water losses as compared to NAR. There was a good agreement between simulated and observed soil water contents, and the model was able to estimate fluctuations in soil water contents. An adjustment in the planting window would be necessary for improved upland rice productivity, enhanced N, and soil water utilization to reduce N and soil water losses. Our results indicated that a well-calibrated EPIC model has the potential to identify suitable N and seasonal planting management options.

Regression Equation Model for Brinjal Pests (Solanum melongena L.) in Maharashtra Plain Zone

An experiment “Effect of weather parameters on growth, yield and insect pest infestation on brinjal varieties under different planting windows” was carried out at Faculty of Agriculture Department of Agricultural Meteorology Farm, Centre for Advanced Agricultural Meteorology, College of Agriculture, Pune during Kharif seasons of 2014 and 2015. The experiment was laid out in split plot design with three replications. The treatment comprised of three brinjal hybrids viz., V1:Phule Arjun, V2: Krishna, V3: Panchganaga as main plot and four planting windows viz., P1: 31st MW (30 July-5 August), P2: 32ndMW (6-12 August), P3:33rdMW (13-19 August) and P4: 34thMW (20-26 August) as sub plot treatments. The correlation of meteorological parameters with incidence of brinjal shoot and fruit borer was studied in 2014. The correlation of shoot and fruit borer on brinjal (0.764*and 0.796*) and (0.784* and 0.704*) with the weather parameters are presented. Whereas morning relative humidity, rainfall and bright sunshine hours showed positive correlation with shoot and fruit borer population Average number of aphids/ jassid/ whiteflies plant showed highly significant negative correlation with minimum temperature(r= -0.702*,-0.710* and 0-.800*,) respectively. During 31stMW planting windows maximum temperature showed significant negative correlation with shoot and fruit borer population(r= -0.796*).It was observed that the infestation of shoot and fruit borer started increasing from October to November and its decreased onwards meteorological week. Amongst all the brinjal hybrids, Phule Arjun hybrids found significantly superior under extended planting windows followed by Krishna and Panchganga. Planting during 31st MW (1st week of August) was observed to be most suitable and optimum for brinjal considering the growth and yield attributes. This planting window was at par with 32nd MW planting window. Linear correlation analysis for brinjal fruit yield with weather parameters was significantly positively correlated with maximum temperature and minimum temperature. Timely planting during 31st MW (P1) and 32nd (P2) recorded lower incidence of shoot and fruit borer, aphids, jassid and whiteflies. Whereas, crop planted during 34thMW (P4) recorded maximum incidence of all pests. Among the brinjal hybrids, higher incidence was recorded with Panchganaga and minimum was recorded on Phule Arjun. Among the brinjal hybrids lower incidence of shoot and fruit borer, aphids, jassids and whiteflies was recorded on hy. Phule Arjun, which was found to be tolerant. This was followed by hy. Krishna. The higher incidence of all pests was recorded hy. Panchganga, which was found to be susceptible. Pest population on brinjal shoot/fruit/Aphid/Jassid/Whiteflies had significant negative correlation with minimum temperatures, whereas, morning and evening relative humidity, wind speed, pan evaporation and bright sunshine hours showed positive correlation pests population.

Modeling the effect of soil fertility management options on maize yield stability under variable climate in a sub-humid zone in Ghana

IntroductionUncertainty in the yield of maize due to variability in weather is a major challenge to smallholder farmers in Sub Sahara Africa. This study explores the potential of combining locally available organic resources and inorganic fertilizer to increase grain yield and reduce variability in yields associated with variations in rainfall distribution.MethodsTo assess the effectiveness of this practice, the Agricultural Production Systems sIMulator (APSIM) crop model was calibrated and evaluated using maize experiments on nutrient management options. The evaluated model was used to simulate maize growth and yield using multiple-year data (1984–2018) under different planting windows for two growing seasons. The treatments were (i) control, (ii) inorganic fertilizer alone (INOFRecom), combining organic resources [empty fruit bunch of palm (EFB) and compost with inorganic fertilizer (INOF) to make up equivalent nutrients in (ii)]; (iii) EFB + INOF and (iv) Comp + INOF.ResultsThough all the soil amendments boosted grain output, the EFB + INOF treatment outperformed the other treatments in the major season with gains of between 161 and 211% and the most stable (least inter-annual variability of 27%) yield. Across the planting windows, the INOFRecom and EFB + INOF treatments achieved comparable yield increments in the minor season. Though grain yield variability was high during the minor rainy season, combining organic and inorganic fertilizers reduced inter-annual yield variability, thus, lowering uncertainty in yield due to variable inter-annual rainfall. Combining local organic resources with a reduced amount of inorganic fertilizer produced higher yields and better yield stability compared to using only inorganic fertilizer.DiscussionsThus, such soil fertility management solutions might sustain resource use and boost maize grain yield in the study area, where strategies for sustainable crop nutrition remain a critical necessity. The improved nitrogen management regimes may result in fewer environmental hazards for vulnerable rainfed agricultural systems.

Agrometeorological Indices Influenced by Varying Planting Windows and Varieties of Brinjal (Solanum melongena L.) in Maharashtra, India

An experiment was carried out at the Faculty of Agriculture Department of Agricultural Meteorology Farm, Centre for Advanced Agricultural Meteorology,College of Agriculture, Pune during Kharif seasons of 2014 and 2015.The experiment was laid out a split plot design with three replications.The treatment comprised of three brinjal hybrids viz.,V1:Phule Arjun, V2: Krishna, V3: Panchganaga as main plot and four planting windows viz., P1: 31st MW (30 July-5 August), P2: 32ndMW (6-12August), P3:33rdMW (13-19 August) and P4: 34thMW (20-26 August) as subplot treatments. Micrometeorological studies of Cumulative GDD, HTU, and PTU at the end of each growth stage showed that the numerically higher requirement was observed in hy.Phule Arjun over hy.Krishna and hy.Panchganga hybrids during both the years 2014 and 2015 experimentation period.Whereas, the lowest canopy temperature was found in hy.Phule Arjun (29.0 0C) than the rest of the brinjal hybrids. Canopy reflected PAR and transmitted PAR was higher in (191.54 and 188.62 µ mol m-2s-1) Panchganaga hybrids among the brinjal hybrids. Amongst all the brinjal hybrids, Phule Arjun hybrids were found significantly superior under extended planting windows followed by Krishna and Panchganga. Planting during 31st MW (1st week of August) was observed to be most suitable and optimum for brinjal considering the growth and yield attributes. This planting window was at par with the 32nd MW planting window. Linear correlation analysis for brinjal fruit yield with weather parameters was significantly positively correlated with maximum temperature and minimum temperature.

Maximizing winter wheat yield through planting date and seeding rate management

AbstractPlanting date and seeding rate are two of the most basic and important factors in determining yield potential in winter wheat (Triticum aestivum L.) due to their impact on stand establishment. Timely planting of winter wheat (within a few days after the Hessian fly free date) ensures sufficient time for fall growth and tillering, which are critical for maximizing yield, while adequate seeding rate is necessary to optimize the number of heads per unit area. Field experiments were conducted in Mason, MI during three growing seasons (2020–2022) utilizing five planting dates, ranging from mid‐September to mid‐November, and five seeding rates ranging from 0.8 to 2.4 million seeds acre−1. There was no interaction between planting date and seeding rate in determining yield. Yields declined by 22–48% from the earliest to the latest planting dates in response to a 33–47% reduction in the number of heads acre−1. Seeding rate did not significantly impact yield except at low seeding rates under delayed planting. Maximum yield was achieved with a seeding rate of 0.93, 1.37, 1.47, 1.54, and 1.85 million seeds acre−1 during the mid‐September, late September, mid‐October, late October, and mid‐November plantings, respectively. Overall, results demonstrated that timely planting of wheat is critical for maximizing yield, with significant yield reductions occurring when planting is delayed, regardless of the seeding rate used. Furthermore, while low seeding rates may be used within the optimal planting window without yield penalty, seeding rates should be progressively increased as planting is delayed to diminish yield loss.

Thermal Indices Requirement of Brinjal Varieties (Solanum melongena L.) under Different Planting Windows

An experiment was carried out at Faculty of Agriculture Department of Agricultural Meteorology Farm, Centre for Advanced Agricultural Meteorology, College of Agriculture, Pune during Kharif seasons of 2014 and 2015.The experiment was laid out in split plot design with three replications.The treatment comprised of three brinjal hybrids viz.,V1:Phule Arjun, V2: Krishna, V3: Panchganaga as main plot and four planting windows viz., P1: 31st MW (30 July-5 August), P2: 32ndMW (6-12August), P3:33rdMW (13-19 August) and P4: 34thMW (20-26 August) as sub plot treatments.
 Cumulative GDD, HTU and PTU at the end of each growth stages showed that numerically higher requirement was observed in hy.Phule Arjun over hy.Krishana and hy.Panchganaga hybrids during both year 2014 and 2015 experimentation period. Whereas, the lowest canopy temperature was found in hy.Phule Arjun (29.0 0C) than rest of the brinjal hybrids. Canopy reflected PAR and transmitted PAR was higher in (191.54 and 188.62 µ mol m-2s-1) Panchganaga hybrids among the brinjal hybrids. Heat unit requirement or GDD has been used for characterizing the thermal response in brinjal crop. GDD for entire crop growing period decreased with subsequent delay in planting. HTU and PTU were also decreased during later planting windows condition. GDD in different stages in that emergence (59.6 and 72.3), vegetative growth (481 and 478), 50% flowering (575 and 568), first harvesting (681 and 645), last harvesting (1178 and 1183) was observed in hybrid Phule Arjun during 2014 and 2015, respectively. Lower GDD was observed in hy.Panchaganaga during 2014 and 2015, respectively. The highest HTU observed in 31st MW planting windows in hybrids Phule Arjun (5376 and 9190.4).This was followed by hy.krishna and Panchganaga (5370 and 9086) during 2014 and 2015, respectively. Highest HTU was observed in 31st MW in hybrids Phule Arjun followed by hy.krishna and lower in panchganga.